ROI From Use Of Global Control Plane For Expanding VDI Environments

ROI From Use Of Global Control Plane For Cloud VDI Environments

ROI From Use Of Global Control Plane For Expanding VDI Environments

The following is a new Industry Trends Perspective White Paper Report titled ROI From Use Of Global Control Plane For Expanding VDI Environments.

ROI From Use Of Global Control Plane For Expanding VDI Environments

This new StorageIO report looks at ROI From Use Of Global Control Plane For Expanding VDI environments. Using a Pro-Forma analysis this report provides a financial economic model comparison with Return on Investment (ROI) cost savings analysis for managing cloud based virtual desktop infrastructures (VDI) environments.

Cloud File Data Storage Consolidation and Economic Comparison Model

IT data infrastructure resource (servers, storage, I/O network, hardware, software, services) decision-making involves evaluating and comparing technical attributes (speeds, feeds, features) of a solution or service. Another aspect of data infrastructure resource decision-making involves assessing how a solution or service will support and enable a given application workload, along with associated management costs from a Performance, Availability, Capacity, and Economic (PACE) perspective.

Keep in mind that all application workloads have some amount of PACE resource requirements that may be high, low or various permutations, along with associated management costs. Performance, Availability (including data protection along with security) as well as Capacity are addressed via technical speeds, feeds, functionality along with workload suitability analysis.

Management costs are a function of initial and recurring tasks to support a given function or service such as VDI. The cost of management includes staff salary, along with amount of time needed to perform various tasks. The E in PACE resource decision-making is about the Economic analysis of various costs associated with different solution approaches.

ROI From Use Of Global Control Plane For Expanding VDI Environments

The above image is an example from the White Paper Report titled ROI From Use Of Global Control Plane For Expanding VDI Environments.

In the example shown above, 36 month OpEx cost (and time) savings are shown using traditional cloud based VDI management tools, technologies and techniques vs. a modern cloud platform integrated global control plane solution. Leveraging a cloud platform integrated global control plane solution such as NetApp VDS among others, management costs can be reduced for initial and recurring tasks from $2,587,394 to $968,041 for 1,001 users.

In addition to the cost savings shown above, note the reduction in management hours of 21,653 over 36 months which could be used for doing other work, or reducing your OpEx spend. Of course your savings will vary based on what tasks, time per task, admin cost among other considerations.

The shift from Capital Expenditures (e.g. CapEx) IT data infrastructure spending to Operational Expenditures (e.g. OpEx) focus particular with IT clouds has resulted in increased OpEx budget demands. Increased spending is more than simply moving IT spend from the CapEx to OpEx columns in budgets. OpEx increases are a cumulation of increased cloud services and data infrastructure spend, along with management (initial and recurring) costs.

The good news is that there are OpEx opportunities to reduce, or, stretch your IT budget to do more while boosting productivity, performance, and effectiveness without compromise. By looking at how to use new technologies in new ways, including leverage cloud platform integrated global control planes for management of VDI (and other functions), initial and recurring OpEx management costs can be reduced.

Read more in this Server StorageIO Industry Trends  Report here.

Where to learn more

Learn more about ROI From Use Of Global Control Plane For Expanding VDI Environments, Clouds and Data Infrastructure related trends, tools, technologies and topics via the following links:

Application Data Value Characteristics Everything Is Not the Same
PACE your Infrastructure decision-making, it’s about application requirements
Cloud conversations: confidence, certainty, and confidentiality
Industry adoption vs. industry deployment, is there a difference?
Ten tips to reduce your cloud compute storage costs 
Don’t Stop Learning Expand Your Skills Experiences Everyday 
ToE NVMeoF TCP Performance Reduce Costs
Data Infrastructure Server Storage I/O Tradecraft Trends
Data Infrastructure Overview, Its What’s Inside of Data Centers
Data Infrastructure Management (Insight and Strategies)
Data Protection Diaries (Archive, Backup, BC, BR, DR, HA, Security)
NetApp VDS with Global Control Plane Cloud VDI Management

Additional learning experiences along with common questions (and answers), as well as tips can be found in Software Defined Data Infrastructure Essentials book.

Software Defined Data Infrastructure Essentials Book SDDC

What this all means

In addition, looking at your IT data infrastructure cloud spend can also help you to boost the effectiveness, productivity and return on investment while reducing your OpEx spend, or doing more with it. Leveraging financial pro-forma analysis as a tool in conjunction with your technology feature function, speeds, feeds comparisons enables informed decision making.

When comparing and making data infrastructure resource decisions, consider the application workload PACE characteristics. Shift or expand your focus from simply looking at costs from a efficiency utilization perspective to also include performance, productivity, and effectiveness of your IT OpEx spending.

Keep in mind that PACE means Performance (productivity), Availability (data protection), Capacity and Economics. This includes making decisions from a technical feature, functionality (speeds and feeds) capacity as well as how the solution supports your application workload. Leverage resources including tools to perform analysis including ROI From Use Of Global Control Plane For Expanding VDI Environments approaches.

Ok, nuff said, for now.

Cheers GS

Greg Schulz – Microsoft MVP Cloud and Data Center Management, previous 10 time VMware vExpert. Author of Software Defined Data Infrastructure Essentials (CRC Press), Data Infrastructure Management (CRC Press), as well as Cloud and Virtual Data Storage Networking (CRC Press), The Green and Virtual Data Center (CRC Press), Resilient Storage Networks (Elsevier) and twitter @storageio. Courteous comments are welcome for consideration. First published on https://storageioblog.com any reproduction in whole, in part, with changes to content, without source attribution under title or without permission is forbidden.

All Comments, (C) and (TM) belong to their owners/posters, Other content (C) Copyright 2006-2024 Server StorageIO and UnlimitedIO. All Rights Reserved. StorageIO is a registered Trade Mark (TM) of Server StorageIO.

Driving ROI with Cloud Storage Consolidation Seminars

Driving ROI with Cloud Storage Consolidation Seminars

Driving ROI with Cloud Storage Consolidation Seminars

Driving ROI with Cloud Storage Consolidation Seminars

Join me in a series of in-person seminars driving ROI with cloud storage consolidation for unstructured file data.

driving roi with cloud storage consolidation seminars
Various Data Infrastructure options from on-prem to edge to cloud and beyond

These initial seminars are being held at Amazon Web Services (AWS) locations April 30 in New York City, May 1 in Chicago and May 2 in Houston Amazon. At each of these three cities, I will be joined by experts from NetApp, Talon and AWS as we look at issues, trends and what can be done today (including hands on demos) driving ROI with cloud storage consolidation for unstructured file data.

What The Seminars Are About

These seminars look at how remove cost and complexity while boosting productivity for distributed sites with unstructured data and NAS file servers. The seminars look at making informed decisions balancing technical considerations with a business return on investment (ROI) model, along with return on innovation (the other ROI) from boosting productivity. It’s not about simply cutting costs that can create chaos or compromise elsewhere, it’s about removing complexity and cost while boosting productivity with smart cloud storage consolidation for unstructured file data.

distributed file server cloud storage consolidation

Distributed File Server Cloud Storage Consolidation ROI Economic Comparison

During these seminars I will discuss various industry and customer trends, challenges as well as solutions, particular for environments with distributed file servers for unstructured file data. As part of my discussion, we will look at both technical, as well as ROI business based model for distributed file server cloud storage consolidation based on the Server StorageIO white paper report titled Cloud File Data Storage Consolidation and Economic Comparison Model (Free PDF download here).

Where When and How to Register

New York City Tuesday April 30, 2019 9:00AM
Amazon Web Services
7 West 34th St.
6th Floor
Learn more and register here.

Chicago Illinois  Wednesday May 1, 2019 9:00AM
Amazon Web Services
222 West Adams Street
Suite 1400
Learn more and register here

Houston Texas Thursday May 2, 2019 9:00AM
Amazon Web Services
825 Town and Country Lane
Suite 1000
Learn more and register here

Where to learn more

Learn more about world backup day, recovery and data protection along with other related topics via the following links:

Additional learning experiences along with common questions (and answers), as well as tips can be found in Software Defined Data Infrastructure Essentials book.

Software Defined Data Infrastructure Essentials Book SDDC

What this all means

Making informed decisions for data infrastructure resources including cloud storage consolidation and distributed file servers involves technical, application workload as well as business economic analysis. Which of the three (technical, application workload, financial) is more important for enabling a business benefit will depend on your perspective, as well as area of focus. However, all the above need to be considered in the balance as part of making an informed data infrastructure resource decision. That is where a discussion about a business financial ROI model (pro forma if you prefer) comes into play as part of cloud storage consolidation, including for distributed file server of unstructured file data.

I look forward to meeting with attendees and hope to see you at the events April 30th in New York City, May 1 in Chicago, and Houston May 2nd as we discuss driving ROI with cloud storage consolidation at these seminars.

Ok, nuff said, for now.

Cheers GS

Greg Schulz – Multi-year Microsoft MVP Cloud and Data Center Management, ten-time VMware vExpert. Author of Data Infrastructure Insights (CRC Press), Software Defined Data Infrastructure Essentials (CRC Press), as well as Cloud and Virtual Data Storage Networking (CRC Press), The Green and Virtual Data Center (CRC Press), Resilient Storage Networks (Elsevier) and twitter @storageio. Also visit www.picturesoverstillwater.com to view various UAS/UAV e.g. drone based aerial content created by Greg Schulz. Courteous comments are welcome for consideration. First published on https://storageioblog.com any reproduction in whole, in part, with changes to content, without source attribution under title or without permission is forbidden.

All Comments, (C) and (TM) belong to their owners/posters, Other content (C) Copyright 2006-2024 Server StorageIO and UnlimitedIO. Visit our companion site https://picturesoverstillwater.com to view drone based aerial photography and video related topics. All Rights Reserved. StorageIO is a registered Trade Mark (TM) of Server StorageIO.

Fall 2018 Dutch Data Infrastructure Industry Trends Decision Making Seminars

Fall 2018 Dutch Data Infrastructure Industry Trends Decision Making Seminars

Fall 2018 Dutch Data Infrastructure Industry Trends Decision Making Seminars

Fall 2018 Dutch Data Infrastructure Industry Trends Decision Making Seminars.

There is still time to register for the fall 2018 Dutch data infrastructure industry trends decision-making seminars November 27th and 28th. The workshops are being organized by Brouwer Storage Consultancy of Holland and will be held in Nijkerk.

On Tuesday, November 27th, there will be an advanced education workshop seminar covering data infrastructure industry trends and technology update presented by myself. On Wednesday, November 28th, there will be a deeper dive workgroup seminar session addressing data infrastructure related strategy, planning, and decision-making.

xxxx

Data Infrastructures Industry Trends November 27

Whats New, Whats the buzz, what you need to know about, From Speeds and Feeds, Slots and Watts to Whos doing what, from interesting to What’s relevant for your environment.

This one-day seminar is a new and improved version of the popular speeds and feeds session where we look at what’s new and emerging in the industry as well as applicable to your environments. You will be updated about the latest trends and emerging data infrastructure technologies to support digital transformation, little and big data analytics, AI/ML/DL, GDPR, data protection, edge/fog compute, and IoT among others. From legacy to the software-defined cloud, container converged and virtual to composable. The seminar is a mix of presentation and engaging discussion as we look into details of favorite or new technologies for both those who are old-school, new-school and current or future school.

Part I – Industry Trends, Applications, and Workload
Part II – Server Compute, Memory, I/O, hardware and software
Part III – Storage and Data protection for on-prem and cloud
Part IV – Bringing it all together, managing and decision making

Topics to be covered include among others:

  • What these trends, tools, technologies mean for different environments of various size.
  • Tips on evaluating legacy and startup or newer vendors as well as technologies.
  • Updates on vendors, services, technologies, products you may or may not have heard of.
  • Cloud (public/private/multi-cloud/hybrid) compute, storage and management.
  • Containers (including docker, windows, kubernetes, FaaS, serverless, lambda).
  • Converged and hyper-converged; Gen-Z and composable; NVMe and NVMeoF.
  • Persistent Memory (PMEM), Storage Class Memory (SCM), 3D XPoint, NAND Flash SSD.
  • Legacy vs. software-defined, appliances, storage systems, block, NAS file, object, table.
  • Bulk cloud data migration appliances, storage for the edge, file sync and share.
  • Role and importance of context (what’s applicable, what something means).
  • Who’s doing what, what to look for today for the future.

This seminar is for those involved with ICT/IT servers, storage, storage, I/O networking, and associated management activities including data protection, of legacy, as well as software-defined cloud, containers, converged hyper-converged and virtualization. This seminar is for professionals who manage, architect or are otherwise involved with data infrastructure related topic strategy and acquisitions.

Data Infrastructures Deep Dive Decision Making November 28

Enabling Informed Strategy and Decision Making, moving from what are the tools, trends and technologies evolving to what to use, when, where, why, how, along with strategy, planning, decision-making, and ongoing management.

If the answer is a cloud, converged, container, composable, edge, fog, digital transformation, on-prem, hybrid, software-defined, what were or are the questions to plan as well as prepare for deployment today, along with in the future? This workshop format seminar provides answers to fundamental questions, with essential insight into software-defined data infrastructures (SDDI) and software-defined data centers (SDDC). For ICT/IT professionals (architects, strategists, administrators, managers) currently or planning on being involved with servers, storage, I/O networking, hardware, software, converged, containers, cloud backup/data protection, and associated topics, this seminar is for you.

Clouds converged, and containers will be a primary focus along with related themes and topics that you need to know more about. Don’t be scared of clouds, be prepared, and this includes for on-prem, public, hybrid and multi-cloud. As part of our deeper dive decision-making strategy focus, we look at cloud cost considerations including are you paying too much or not enough (e.g., are you depriving your applications of performance to save money?). We will explore various decision-making and strategy topics spanning AWS, Microsoft Azure, Azure Stack, Windows and Hyper-V, VMware (including on AWS) and OpenStack, is it still open for business?

Additional topics, trends, themes include:

  • Everything is not the same across cloud services, converged, or containers.
  • Different environments have various data infrastructure resource needs.
  • How to balance legacy on-prem application needs with emerging technology options.
  • Different comparison criteria for smaller environments remote office vs. Larger enterprise
  • Do it yourself (DiY) vs. Turnkey software vs. Bundled tin wrapped software solution
  • Strategy, planning, decision-making, and ongoing management

How To Register For Seminar Workshops

Learn more about fall 2018 Dutch Server StorageIO Data Infrastructure Tuesday trends workshop seminar here (PDF), and Wednesday deeper dive decision-making workshop session here (PDF).

To register and obtain more information, contact event organizers Brouwer Storage consultancy at +31-33-246-6825 or +31-652-601-309 and info at brouwerconsultancy.com.

Where to learn more

Learn more about Data Infrastructure and related trends, tools, technologies and topics via the following links:

Additional learning experiences along with common questions (and answers), as well as tips can be found in Software Defined Data Infrastructure Essentials book.

Software Defined Data Infrastructure Essentials Book SDDC

What this all means

Everything is not the same across different organizations, environments, application workloads, data, technology, tools, trends. These two one day interactive workshop seminars provide timely insight into what’s going on in the data infrastructure related industry, along with common IT organization challenges as well as how to address them. Moving from the what to what to use when, where, why, how along with alternatives, gaining insight and awareness to avoid flying blind enables effective strategy, decision-making, planning and ongoing management. Learn more and sign up for Fall 2018 Dutch Data Infrastructure Industry Trends Decision Making Seminars, see you in Nijkerk.

Ok, nuff said, for now.

Cheers Gs

Greg Schulz – Microsoft MVP Cloud and Data Center Management, VMware vExpert 2010-2018. Author of Software Defined Data Infrastructure Essentials (CRC Press), as well as Cloud and Virtual Data Storage Networking (CRC Press), The Green and Virtual Data Center (CRC Press), Resilient Storage Networks (Elsevier) and twitter @storageio. Courteous comments are welcome for consideration. First published on https://storageioblog.com any reproduction in whole, in part, with changes to content, without source attribution under title or without permission is forbidden.

All Comments, (C) and (TM) belong to their owners/posters, Other content (C) Copyright 2006-2024 Server StorageIO and UnlimitedIO. All Rights Reserved. StorageIO is a registered Trade Mark (TM) of Server StorageIO.

Microsoft Azure Data Box Disk Impressions #blogtobertech

Microsoft Azure Data Box Disk Test Drive Impressions #blogtobertech

Microsoft Azure Data Box Disk Test Drive Impressions #blogtobertech

Data Box Disk Test Drive Impressions is the last of a four-post series looking at Microsoft Azure Data Box. View Part 1 Microsoft announced Azure Data Box updates, Part 2 Microsoft Azure Data Box Family, and Part 3 Microsoft Azure Data Box Disk Test Drive Review.

Overall, I liked the Azure Data Box experience along with a range of options to select the best fit solution for my needs. A common trend among the major cloud service providers such as AWS, Microsoft Azure and Google is that one size fits all approach solution does not meet different customer needs.

The only things that I did not like about and would like to see improved with Azure Data Box are two items one at the beginning, the other at the end of the process. Granted with Data Box Disks still in preview, there is time for those items to be addressed before general availability, and I have passed on the feedback to Microsoft.

At the beginning of the process, things are pretty straightforward with good tools along with resources to help you navigate which type of Data Box to order, how to order, specify your account details and other information.

What I did not like with the up front experience was after the quick ordering and notification process, the time delay of a week or more until notified when a Data Box would be arriving. Granted I was not in a rush and Microsoft did indicate that it could take about ten days to be informed of availability, this is something that should be done quickly as resources become available. Another option is for Microsoft to add an ordering option for priority or low-priority in the future.

The other experience that I did not like was at the very end, in that perhaps its stuck in an email spam trap (checked, could not find it), the final notification could be better. Not only a final email note saying your data is copied, but also a reminder of where your block or page blobs were copied to (e.g., what your setup when ordering).

Monitoring the progress of the process, I knew when Data Box drives arrived at Microsoft, copy started and completed including with error status. Having gotten used to receiving update notifications from Azure, not receiving one at the end saying congratulations your data has been copied, check here for any errors or other info, as well as a reminder where the data was copied to would be useful.

Likewise, a follow-up note from Microsoft saying that the Azure Data Box drives used as part of the transfer were securely erased along with a certificate of digital destruction would be useful for compliance purposes.

As mentioned above, overall, I found the Data Box Disk experience very positive and a great way to move bulk data faster than what could be done with available networks. My next step is now to migrate some of the transferred data to cold long-term archive storage, and some others to Azure Files, with some staying in block blobs. There are also a couple of VHD and VHDX that will be moved and attached to VMs for additional testing.

Where to learn more

Learn more about Microsoft Azure Data Box, Clouds and Data Infrastructure related trends, tools, technologies and topics via the following links:

Additional learning experiences along with common questions (and answers), as well as tips can be found in Software Defined Data Infrastructure Essentials book.

Software Defined Data Infrastructure Essentials Book SDDC

What this all means

For those who have a need to move large amounts of data including structured, unstructured, semi-structured, little or big data to a cloud resource, solutions such as Azure Data Box may be in your future. Likewise, for those looking to support remote and edge workloads from AI, ML, DL inferencing, to large-scale data pre-processing, data collection and acquisition, video, telemetry, IoT among others Data Box type solutions may be in your future. Overall I found Microsoft Azure Data Box Disk Impressions Favorable and was able to address a project I had on the to-do list for some time.

Ok, nuff said, for now.

Cheers Gs

Greg Schulz – Microsoft MVP Cloud and Data Center Management, VMware vExpert 2010-2018. Author of Software Defined Data Infrastructure Essentials (CRC Press), as well as Cloud and Virtual Data Storage Networking (CRC Press), The Green and Virtual Data Center (CRC Press), Resilient Storage Networks (Elsevier) and twitter @storageio. Courteous comments are welcome for consideration. First published on https://storageioblog.com any reproduction in whole, in part, with changes to content, without source attribution under title or without permission is forbidden.

All Comments, (C) and (TM) belong to their owners/posters, Other content (C) Copyright 2006-2024 Server StorageIO and UnlimitedIO. All Rights Reserved. StorageIO is a registered Trade Mark (TM) of Server StorageIO.

Microsoft Azure Data Box Disk Test Drive Review #blogtobertech

Microsoft Azure Data Box Test Drive #blogtobertech

Microsoft Azure Data Box Test Drive #blogtobertech

Microsoft Azure Data Box Test Drive is part three of four series looking at Data Box. View Part 1 Microsoft announced Azure Data Box updatesPart 2 Microsoft Azure Data Box Family, and Part 4 Microsoft Azure Data Box Disk Impressions.

Getting Started

The workflow for using Data Box involves selecting with the type of Data Box to use via the Microsoft Azure portal (here), or Data Box Family page (here).

Getting Started via the Microsoft Azure Data Box Family Page image via Microsoft.com
Getting Started via the Microsoft Azure Data Box Family Page image via Microsoft.com

First step of ordering a Data Box is to specify your Azure subscription, type of operation (e.g., import data into Azure, or export out), source country/region and destination Azure region.

Selecting Data Box from Azure Portal
Selecting Data Box from Azure Portal

The next step is to determine what type of Data Box, in this test I choose 40 TB Data Box Disks. Make a note of fees to avoid any surprises.

Selecting Data Box Disks (40 TB) From Azure Portal
Selecting Data Box Disks (40 TB) From Azure Portal

After selecting the type of Data Box, fill in storage account information using an existing resource, or create new ones as needed. Make a note of these selections as you will need them after the copy is done as this is where your data will be located.

Specify Azure Storage Account Information Where Data Will Transfer To
Specify Azure Storage Account Information Where Data Will Transfer To

Once the order is placed, an email is received confirming the order and also being a preview, indicating that it might take ten days to hear a status update or availability of the devices.

Email notification received after the order is placed
Email notification received after the order is placed

After about ten days, I was contacted by Microsoft via an email (not shown) confirming the amount of data to be copied to determine how many disks would be needed. Once this was confirmed with Microsoft, a status update was noted on the Azure dashboard.

Azure Data Box Dashboard Status after order placed
Azure Data Box Dashboard Status after order placed

After a few days, a box arrived with the Data Box disks, cables and return shipping labels enclosed. Also received was an email notification indicating the disks had arrived.

Email notice Data Box has arrived on site
Email notice Data Box has arrived on site (on-prem if you prefer)

The following is the physical box that contains the Data Box disks that I received from Microsoft.

The shipping box with Data Box Disks arrives
The shipping box with Data Box Disks arrives

Once you get the Data Box, go to the Azure portal for Data Box and access the tools. There are tools and commands for Windows as well as Linux that are needed for accessing and unlocking the disks. This is where you also obtain device IDs. You will also need to have the access key phrase you specified in an earlier step as part of placing the order.

Access Data Box Software Tools and Keys from Azure Portal
Access Data Box Software Tools and Keys from Azure Portal

Inside the shipping box was a pair of 8 TB SATA SSDs, SATA to USB cables, along with return shipping labels.

Contents inside the shipping box, two Data Box 8 TB disks
Contents inside the shipping box, two Data Box 8 TB disks

From the Azure portal, access the device IDs that will be needed along with passphrase for obtaining and unlocking the Data Box disks. You will also want to download the tools as well as follow other instructions on the portal for accessing disks.

Azure Data Box tools, device IDs and Keys
Azure Data Box tools, device IDs and Keys

The Windows system I used for testing is a virtual machine hosted on a VMware vSphere ESXi 6.7 host. After physically attaching the Data Box Disks to the VM host, a virtual or software attachment was done by adding USB devices to the VM.

Virtual Attach of Data Box Disks to VMware vSphere ESXi host and guest VM
Virtual Attach of Data Box Disks to VMware vSphere ESXi host and guest VM

Once the VM had the Data Box disks attached and mapped, they appeared to Windows. After downloading the Data Box software tools and unlocking the devices, they were ready to copy data to. Note that the disks appear as a regular Windows device once unlocked. Simply using bit locker does not unlock the drives, you need to use the Data Box tools. Speaking of Windows disks, there are a couple of folders on the Data Box disk when shipped including one for Block Blob and Page Blob along with verification items.

View of Data Box Disks (8 TB each) after attaching to Windows system
View of Data Box Disks (8 TB each) after attaching to Windows system

Note that you are given several days as part of the base transfer cost, then extra days apply. Since I had a few extra days, I used some of the excess capacity to do some staging and reorganization of data before the actual copy.

Data copy is done using your choice of tools, for example, Robocopy among many others. I used a combination of Robocopy, Retrospect among others. Also, note that for most data place them in the folder or directory structure of your choice in the Block Blob folder. Page Blobs are for VHDX to be used with virtual machines on Azure. After spending a few days to copy the data I wanted to move along with performing verification, it was time to pack up the devices.

As a reminder, blobs are analogous to and what Microsoft Azure refers to instead of objects (e.g., object storage). Also remember that Azure blobs include block, page (512-byte page aligned for VHDX) and append (similar to other vendors object storage). Microsoft Azure in addition to blobs, supports file (SMB and NFS) access, along with table (database) and queue storage services.

The following shows the return label attached to the shipping box that contains the Data Box disks and cables. I also included a copy of the shipping label inside the box just in case something happened during shipment. Once prepared for delivery, I took the box to a local UPS store where I received a shipment receipt (not shown). Later that day I also received an email from Microsoft indicating the shipment was in-progress.

Data Box disks packaged with return receipt (was in the box)
Data Box disks packaged with return receipt (was in the box)

The Azure portal shows status of Data Box shipment being sent to Microsoft, along with a follow-up email notification.

Azure Data Box portal status
Azure Data Box portal status

Email notification of Data Box on the way to Microsoft.

Notice data box is on the way to Azure
Notice data box is on the way to Azure

After a few days’ ways, checking the Azure Portal shows the Data Box arrived at Microsoft and copied operations underway. Remember the storage account you specified back in the early steps is where you will look for your data. This is something I think Microsoft can improve on by providing a link, or some reminder of where the data is being copied to in the status. Likewise, a copy completion email notice would be handy after getting used to the other alerts previous in the process.

Azure Data Box portal showing disk copy operation status
Azure Data Box portal showing disk copy operation status

Looking at the Azure storage account specified during the ordering process in the Blob storage resources the contents of the Data Box Disks can be found.

Contents of Data Box disks copied into specified Azure Blobs and storage account
Contents of Data Box disks copied into specified Azure Blobs and storage account

The following shows folders that I had copied from on-prem systems to the Data Box now located in the proper Azure Block Blobs. Not shown are Page blobs where I moved some VHDXs.

xMission accomplished, data folders now stored in Azure block blobs
Mission accomplished, data folders now stored in Azure block blobs

Where to learn more

Learn more about Microsoft Azure Data Box, Clouds and Data Infrastructure related trends, tools, technologies and topics via the following links:

Additional learning experiences along with common questions (and answers), as well as tips can be found in Software Defined Data Infrastructure Essentials book.

Software Defined Data Infrastructure Essentials Book SDDC

What this all means

Overall the test drive of the Azure Data Box Disk solution was positive, and look forward to trying out some of the other Data Box solutions, both offline and online options in the future. Continue reading Part 4 Microsoft Azure Data Box Disk Impressions as part of this series including Microsoft Azure Data Box Disk Test Drive Review.

Ok, nuff said, for now.

Cheers Gs

Greg Schulz – Microsoft MVP Cloud and Data Center Management, VMware vExpert 2010-2018. Author of Software Defined Data Infrastructure Essentials (CRC Press), as well as Cloud and Virtual Data Storage Networking (CRC Press), The Green and Virtual Data Center (CRC Press), Resilient Storage Networks (Elsevier) and twitter @storageio. Courteous comments are welcome for consideration. First published on https://storageioblog.com any reproduction in whole, in part, with changes to content, without source attribution under title or without permission is forbidden.

All Comments, (C) and (TM) belong to their owners/posters, Other content (C) Copyright 2006-2024 Server StorageIO and UnlimitedIO. All Rights Reserved. StorageIO is a registered Trade Mark (TM) of Server StorageIO.

Microsoft Azure Data Box Family #blogtobertech

Microsoft Azure Data Box Family #blogtobertech

Microsoft Azure Data Box Family #blogtobertech

Microsoft Azure Data Box Family is part two of a four-part series looking at Data Box. View Part 1 Microsoft announced Azure Data Box updates, Part 3 Microsoft Azure Data Box Disk Test Drive Review, Part 4 Microsoft Azure Data Box Disk Impressions.

Microsoft Azure Data Box Overview

Microsoft has several Data Box solutions available or in the preview to meet various customer needs. These include both online as well as offline solutions that include hardware (except Data Box Gateway), software tools and cloud services.

Data Box Online

Microsoft has two online Data Box offerings that provide real-time access of Azure cloud storage resources from on-prem including remote, edge locations. The online Data Box solutions include Edge and Gateway both with local on-prem storage.


Data Box Edge image via Microsoft.com

Data Box Edge (Preview)

Currently, in preview, Data Box Edge is a 1U appliance that combines hardware along with software resources for deployment on-prem at the edge or remote locations. Data Box Edge places locally converged compute and storage resources as an appliance along with connectivity to Azure cloud-based resources.

Intended workloads and applications for Data Box Edge include remote AI, ML, and DL inferencing, data processing or pre-processing before sending to Azure Cloud, function as an edge compute, data protection and data transfer platform (e.g., cloud storage gateway) with local compute. Data Box Edge is similar in functionality and focuses on other cloud service provider solutions such as AWS Snow Ball Edge (SBE). Management tools include Data Box Edge resource Azure portal for management from a web UI, create and manage resources, devices, shares.

Other Data Box Edge attributes include:

  • Supports Azure Blob or Files via SMB and NFS storage access protocols
  • Dual Intel Xeon processors each with 10 CPU cores, 64GB RAM
  • 2 x 10 Gbps SFP+ copper cables, 2 x 1 Gbps RJ45 cables
  • 8 NVMe SSD (1.6 TB each), no HA, 12.8 TB total raw cap
  • 2 x 1 GbE (one for management, one for user access)
  • 2 x 25 GbE (can operate at 10 GbE) and 2 x 25 GbE ports
  • Local web UI for management and configuration

Data Box Gateway (Preview)

Also in Preview, Data Box Gateway is a virtual machine (VM) based software defined appliance that runs on VMware vSphere (ESXi) or Microsoft Hyper-V hypervisors. The functionality of Data Box Gateway is that of a cloud storage gateway providing access to Azure Blob (Page and Block) or Files (NAS) via SMB or NFS protocols. Learn more about both Data Box Edge and Data Box Gateway here including pricing here.

Data Box Offline Solutions

Microsoft has several offline Data Box offerings including previously available and new in preview models. Offline Data Box solutions enable large amounts of data to be moved from on-prem primary, remote and edge locations to Azure cloud storage resources. Bulk data movement operations can be one-time or recurring in support of big data migration of energy, research, media & entertainment and other large volumes of data.

Other bulk movement includes for archive, backup, BC/DR, virtual machine and application migration among others. Use Data Box Offline solutions when large amounts of data need to be moved from on-prem to Azure cloud faster than what available networks will support promptly.

Offline Data Box solutions include:

  • Data Box Heavy (Preview) 1 PB Storage, 800 TB usable
  • Data Box 100 TB (80 TB usable)
  • Data Box Disk (Preview) 40 TB (35 TB Usable)


Data Box Heavy 1 PB (Preview) image via Microsoft.com

Data Box Heavy 1 PB (Preview)

  • Appliance with Up to 800 TB usable capacity per order
  • One system per order
  • Supports Azure Blob or Files
  • Copy data to up to 10 storage accounts
  • 1 x 1/10 Gbps RJ45 connector, 4 x 40 Gbps QSFP+ connectors
  • AES 256-bit encryption
  • Copies data using NAS SMB and NFS protocols


Data Box 100TB image via Microsoft.com

100 TB Data Box

  • An appliance that supports 80 TB usable storage capacity
  • Supports Azure Blob or Files
  • Copies data to 10 storage accounts
  • 1 x 1/10 GbE RJ45 connector
  • 2 x 10 GbE SFP+ connector
  • AES 256-bit encryption
  • Storage access and copy via SMB and NFS NAS protocols

Case of Data Box Disks image via Microsoft.com

Data Box Disk 40 TB (Preview)

  • Up to 35 TB usable capacity per order
  • Up to 5 SSDs per order
  • This is what I tested (2 x 8 TB)
  • Supports Azure Blob storage (Block and Page)
  • Copies data to a single storage account
  • USB/SATA II, III server I/O interface (comes with SATA to USB connector cables)
  • AES 128-bit encryption
  • Copy data with standard tools

Where to learn more

Learn more about Microsoft Azure Data Box, Clouds and Data Infrastructure related trends, tools, technologies and topics via the following links:

Additional learning experiences along with common questions (and answers), as well as tips can be found in Software Defined Data Infrastructure Essentials book.

Software Defined Data Infrastructure Essentials Book SDDC

What this all means

Which Microsoft Azure Data Box is the best? That depends on your needs and requirements.

Microsoft along with other major cloud service providers continue to evolve their data migration services. Realizing that customers who need, want, or have to get data to the cloud also need to remove barriers, solutions such as Azure Data Box are a step in eliminating cloud barriers while addressing cloud concerns. Continue reading Part 3 Microsoft Azure Data Box Disk Test Drive Review and Part 4 Microsoft Azure Data Box Disk Impressions as part of Microsoft Azure Data Box Family.

Ok, nuff said, for now.

Cheers Gs

Greg Schulz – Microsoft MVP Cloud and Data Center Management, VMware vExpert 2010-2018. Author of Software Defined Data Infrastructure Essentials (CRC Press), as well as Cloud and Virtual Data Storage Networking (CRC Press), The Green and Virtual Data Center (CRC Press), Resilient Storage Networks (Elsevier) and twitter @storageio. Courteous comments are welcome for consideration. First published on https://storageioblog.com any reproduction in whole, in part, with changes to content, without source attribution under title or without permission is forbidden.

All Comments, (C) and (TM) belong to their owners/posters, Other content (C) Copyright 2006-2024 Server StorageIO and UnlimitedIO. All Rights Reserved. StorageIO is a registered Trade Mark (TM) of Server StorageIO.

Microsoft announced Azure Data Box updates #blogtobertech

Microsoft announced Azure Data Box updates – #blogtobertech

Microsoft announced Azure Data Box updates - #blogtobertech

Microsoft announced Azure Data Box is the first in a series of four posts looking at Data Box including a test drive experience. View Part 2 Microsoft Azure Data Box Family, Part 3 Microsoft Azure Data Box Disk Test Drive Review, Part 4 Microsoft Azure Data Box Disk Impressions.

Microsoft Azure Data Box Family Page image via Microsoft.com
Microsoft Azure Data Box Family Page image via Microsoft.com

At Ignite in Microsoft announced Azure Data Box updates, which means its time for a test drive and review. Microsoft has several Data Box solutions available or in the preview to meet various customer needs. These include both online as well as offline solutions that include hardware (except Data Box Gateway), software tools and cloud services. In general, Data Box enables bulk movement and migration of data from on-prem environments to Azure cloud storage including blobs (e.g., objects) and files (e.g., NAS accessible) resources.

Whats The Need for Data Movement Appliance Service

Some might ask the question why do you need a Microsoft Azure Data Box when there are fast networks? Good question, assuming you have fast networks that can move large amounts of bulk data promptly. Microsoft supports traditional Internet-based access to Azure cloud resources for data migration, along with higher speed Express Route service similar to Amazon Web Service (AWS) Direct Connect among other options.

On the other hand, if you need to move a large amount of data that would take weeks, months or longer sending over expensive networks, then solutions like Data Box are an option. Microsoft is not alone or unique having data storage migration or movement services. AWS has Snowball, Snowball Edge with compute, as well as the truck size Snowmobile for large-scale data movement. Google also has their Transfer services including Google Transfer Appliance.

Who is Azure Data Box for?

Azure Data Box is for those who need to migrate data to Azure cloud storage and other services on a one-time or recurring basis. Another scenario is for those who need to have on-prem storage and optional compute at remote or edge locations in support of data acquisition, media & entertainment, energy exploration, AI, ML, DL inferencing, local data processing, pre-processing before sending to cloud among other workloads.

Yet other scenarios for those who need to move large amounts of data online, off-line, or in disconnected also known as submarine mode where a connection to the internet is not always available. Bulk data movement also applies for one-time, as well as recurring data protection such as archive, backups, BC/DR, as well as data shipping, virtual machine farm relocation, SQL Server data migration to cloud, data center consolidation among many other scenarios.

What is Azure Data Box

Azure Data Box is a combination of hardware, software, cloud services that support data migration (on-line and off-line) from on-prem environments including remote or edge to Azure cloud storage resources. There are different Data Box solutions available or in the preview to meet various needs from performance, capacity, functionality, without as well as without compute. In addition to being used for data migration, there are also Data Box solutions (e.g., Edge) that converge compute and storage for deployment at remote or edge locations.

Data Box Gateway is a software-defined virtual machine appliance that deploys on VMware and Microsoft (e.g., Hyper-V) hypervisors. Off-line Data Box solutions scale from single 8TB SSD disks to PB of capacity with various functionality.

As a reminder, blobs are analogous to and what Microsoft Azure refers to instead of objects (e.g., object storage). Also remember that Azure blobs include block, page (512-byte page aligned for VHDX) and append (similar to other vendors object storage). Microsoft Azure in addition to blobs, supports file (SMB and NFS) access, along with table (database) and queue storage services.

Where to learn more

Learn more about Microsoft Azure Data Box, Clouds and Data Infrastructure related trends, tools, technologies and topics via the following links:

Additional learning experiences along with common questions (and answers), as well as tips can be found in Software Defined Data Infrastructure Essentials book.

Software Defined Data Infrastructure Essentials Book SDDC

What this all means

Azure Data Box type solutions and services are becoming more common as well as diverse. With the addition of compute in some of these solutions to support remote edge workloads, the lines may blur with some of the converged and hyper-converged infrastructure (HCI) solutions. Likewise, keep an eye to see how cloud service providers leverage solutions like Data Box Edge to further place their reach out to the edge enabling fog (e.g., cloud at the edge) among other converged functionality. Continue reading Part 2 Microsoft Azure Data Box Family, Part 3 Microsoft Azure Data Box Disk Test Drive Review, and Part 4 Microsoft Azure Data Box Disk Impressions as part of Microsoft announced Azure Data Box updates.

Ok, nuff said, for now.

Cheers Gs

Greg Schulz – Microsoft MVP Cloud and Data Center Management, VMware vExpert 2010-2018. Author of Software Defined Data Infrastructure Essentials (CRC Press), as well as Cloud and Virtual Data Storage Networking (CRC Press), The Green and Virtual Data Center (CRC Press), Resilient Storage Networks (Elsevier) and twitter @storageio. Courteous comments are welcome for consideration. First published on https://storageioblog.com any reproduction in whole, in part, with changes to content, without source attribution under title or without permission is forbidden.

All Comments, (C) and (TM) belong to their owners/posters, Other content (C) Copyright 2006-2024 Server StorageIO and UnlimitedIO. All Rights Reserved. StorageIO is a registered Trade Mark (TM) of Server StorageIO.

Cloud File Data Storage Consolidation and Economic Comparison Model #blogtobertech

Cloud File Data Storage Consolidation and Economic Comparison Model #blogtobertech

Cloud File Data Storage Consolidation and Economic Comparison Model

The following is a new Industry Trends Perspective White Paper Report titled Cloud File Data Storage Consolidation and Economic Comparison Model.

Cloud File Data Storage Consolidation and Economic Comparison Model

This new report looks at Distributed File Server and Consolidated Cloud Storage Economic Comparison with a fundamental economic comparison model for remote (on-prem) distributed file-servers and cloud storage consolidation decision-making. IT data infrastructure resource (servers, storage, I/O network, hardware, software, services) decision-making involves evaluating and comparing technical attributes (speeds, feeds, features) of a solution or service. Another aspect of data infrastructure resource decision-making involves assessing how a solution or service will support and enable a given application workload from a Performance, Availability, Capacity, and Economic (PACE) perspective.

Cloud File Data Storage Consolidation and Economic Comparison Model

Keep in mind that all application workloads have some amount of PACE resource requirements that may be high, low or various permutations. Performance, Availability (including data protection along with security) as well as Capacity are addressed via technical speeds, feeds, functionality along with workload suitability analysis. The E in PACE resource decision-making is about the Economic analysis of various costs associated with different solution approaches.

Read more in this Server StorageIO Industry Trends and Perspective (ITP) Report.

Where to learn more

Learn more about Clouds and Data Infrastructure related trends, tools, technologies and topics via the following links:

Additional learning experiences along with common questions (and answers), as well as tips can be found in Software Defined Data Infrastructure Essentials book.

Software Defined Data Infrastructure Essentials Book SDDC

What this all means

When comparing and making data infrastructure resource decisions, consider the application workload PACE characteristics. Also keep in mind that PACE means Performance (productivity), Availability (data protection), Capacity and Economics. This includes making decisions from a technical feature, functionality (speeds and feeds) capacity as well as how the solution supports your application workload. Leverage resources including tools to perform analysis including Cloud File Data Storage Consolidation and Economic Comparison Model approaches.

Ok, nuff said, for now.

Cheers Gs

Greg Schulz – Microsoft MVP Cloud and Data Center Management, VMware vExpert 2010-2018. Author of Software Defined Data Infrastructure Essentials (CRC Press), as well as Cloud and Virtual Data Storage Networking (CRC Press), The Green and Virtual Data Center (CRC Press), Resilient Storage Networks (Elsevier) and twitter @storageio. Courteous comments are welcome for consideration. First published on https://storageioblog.com any reproduction in whole, in part, with changes to content, without source attribution under title or without permission is forbidden.

All Comments, (C) and (TM) belong to their owners/posters, Other content (C) Copyright 2006-2024 Server StorageIO and UnlimitedIO. All Rights Reserved. StorageIO is a registered Trade Mark (TM) of Server StorageIO.

May 2018 Server StorageIO Data Infrastructure Update Newsletter

May 2018 Server StorageIO Data Infrastructure Update Newsletter

May 2018 Server StorageIO Data Infrastructure Update Newsletter

Volume 18, Issue 5 (May 2018)

Hello and welcome to the May 2018 Server StorageIO Data Infrastructure Update Newsletter.

In cased you missed it, the April 2018 Server StorageIO Data Infrastructure Update Newsletter can be viewed here (HTML and PDF).

May has been a busy month with a lot of data infrastructure related activity from software-defined virtual, cloud, container, converged, serverless to legacy, hardware, software, services, server, storage, I/O and networking along with data protection topics among others.

In this issue buzzwords topics include GDPR, NVMe, NVMeoF, Composable, Serverless, Data Protection, SCM, Gen-Z, MaaS:

Enjoy this edition of the Server StorageIO Data Infrastructure update newsletter.

Cheers GS

Data Infrastructure and IT Industry Activity Trends

May has been a busy month, some data infrastructure, server, storage, I/O network, hardware, software, cloud, converged, and container as well as data protection activity includes among others:

Depending on when you read this, the new global data protection regulations (GDPR) are either days away, or already in effect. For those who are not aware of GDPR other than seeing many inbox items in your email pertaining to it, here are some resources as a refresher or primer:

May Buzzword, Buzz Topic and Trends

Besides data protection and GDPR, other recent data infrastructure related news, trends, technologies and topics to keep an eye on (besides AI, ML, DL, AR/VR, IoT, Blockchain, Serverless) include Metal as a Service (MaaS) that might be familiar to some, for others, something new. Canonical has been busy for sometime now with MaaS including in Ubuntu and they are not alone with variations appearing with various managed service providers, hosting and cloud providers as well. NVMe has become a more common topic, technology, trend including for use in servers as well as over fabrics (e.g. NVMe over Fabrics) as a language for server, storage, I/O communication.

A new emerging companion to NVMe is Gen-Z which initially is a companion to PCIe. Longer term, Gen-Z could maybe possibly be a replacement, as well as for use accessing direct random access memory (DRAM) among other uses. Storage Class Memory (SCM) has been an industry conversation topic for several years now with new persistent memories (PMEM) that combine the best of traditional DRAM (Speed and write endurance) as well as persistent, higher capacity, lower cost of traditional NAND flash SSDs.

Another trend topic is that for some, ASIC, FPGA and GPU are new companions to standard commodity compute processors along with servers, yet for others it may be Dejavu as they have been being used for years (ok, decades) in some solutions. For now, two other buzzwords, buzz terms to add or refresh your data infrastructure vocabulary include distributed ledgers (aka blockchains), composable resources and ephemeral instance storage (storage on a cloud instance).

May NVMe Momentum Movement Activity

May saw a lot of NVMe related activity, from chips and components (adapters, devices) to systems spanning direct attached to NVMe over Fabric (NVMeoF). Here is a primer (or refresh) for NVMe along with various deployment options. NVMeoF includes RDMA over Converged Ethernet (RoCE) based, along with NVMe over Fibre Channel (FC-NVMe), as well as emerging NVMe over IP.

NVMe options
NVMe being used for front-end accessed via shared PCIe along with back-end devices

There are many different facets of NVMe including for use as a front-end on storage systems supporting server attachment (e.g. competes with Fibre Channel, iSCSI, SAS among others). Another variation of NVMe is as a back-end for attachment of drives or other NVMe based devices in storage systems, as well as servers.

NVMe backend
Front-end using traditional block SAN access with back-end NVMe, SAS and SATA devices

Read more about the many different options and variations of NVMe including key questions to ask or understand, deployment topology along with other related topics at thenvmeplace.com.

NVMe frontend NVMeoF
Various NVMe front-end including NVMeoF along with NVMe back-end devices (U.2, M.2, AiC)

Software Defined Data Infrastructure Activity

Amazon Web Services (AWS) continues to add new features, functionality as well as extending those as along with existing capabilities into various regions. Some recent updates include new Elastic Cloud Compute (EC2) Microsoft Windows Servers versions 1709 and 1803 Amazon Machine Images (AMIs). Other AWS updates include spot instances support for Red Hat BYOL (Bring Your Own License), VPN enhancements, X1e instances available in Frankfurt, H1 instance price reduction, as well as LightSail now in Canada, Paris, and Seoul regions.

For those who are not familiar with LightSail, they are virtual private servers (VPS) which are different from traditional EC2 instances. LightSail can be a cost-effective way for those who need to move out of general population shared hosting, yet cannot justify a full EC2 instance while requiring more than a container.

The LightSail instance also is available with various software pre-installed such as for WordPress websites among others. For example, I have used LightSail as a backup and standby WordPress site for StorageIOblog using Updraft Plus  Pro for data protection.

In other news, AWS C5d EC2 instances are available in various regions. C5d instances are available with 2, 4, 8, 16, 36 and 72 vCPUs along with up to 1800GB of NVMe based ephemeral storage for on-demand reserved or spot instances.

Note that instance-based storage is temporary meaning that it persists for the life of the instance. What this means is that if you stop and restart the instance, the data is not persistence. Instance-based storage is useful for data that can be protected or persisted to other storage including EBS (Elastic Block Storage). Usage includes batch, log and analytics processing, burst buffers, cache or workspace.

AWS also announced a new Simple Storage Service (S3) storage class a month or so ago called One Zone Availability Infrequent Access. This new storage class primarily provides a lower cost of storage with lower durability (e.g., data spread across one zone vs. multiple). Over the past couple of months, I have been migrating from S3 Infrequent Access (IA) as well as standard into One Zone Availability. Some of my active data remains in S3 Standard storage class, while cold archives are in Glacier.

A tip about migrating to One Zone Availability, as well as between other S3 storage classes is paid attention to your API calls and monthly budget. You might see an increase in S3 costs during the migration time, that then settles into the lower prices once data has been moved due to API calls (gets, puts, lists, dir). In other words, pay attention to how many API calls you are allowed per storage class per month, along with other fees beyond focusing only on cost per TByte. Read about other recent AWS news updates here.

Software-defined storage startup Cloudian announced their technology available for test drive on Google Cloud Platform as part of a continued industry trend. That trend is for storage vendors to make their storage software technology available on different cloud platforms such as AWS, Azure, Google, Softlayer among others.

Dell Technology World 2018

Dell Technologies made several announcements as part of Dell Technologies World that are covered in a series of posts here. Announcements included PowerMax the successor to VMAX, XtremIO X2 updates, new servers, workstations among many other items, read more here.

Besides the data infrastructure, cloud service providers and systems vendors, component suppliers including Cavium announced NVMe over Fibre Channel updates (here and here), along with Marvel NVMe updates here. HPE announced new thin clients and software (t430 Thin Client, HP mt44 Mobile Thin Client, HP ThinPro software), as well as updates to 3PAR and other storage solutions.

IBM announced various storage enhancements (and here) as well as a Happy 30th anniversary to the IBM Power9 based i systems. In other news, Kaseya bought backup data protection vendor Unitrends.

NVMe NAND flash Intel Optane

Micron announced the first quad layer cell (QLC) nand flash solid state device (SSD) named 52100 has begun shipping to select customers (and vendors). QLC packs or stacks 4 bits per cell. The 5200 is optimized for read-intensive workloads with up to 33% higher densities compared to previous generation TLC (triple layer cell) NAND flash. Broader market availability is expected to occur later fall 2018, 5210 form factor is 2.5” as a standard SSD or HDD, with capacities from 1.92TB to 7.68TB.

In other news, Micron also announced a $10 Billion (USD) stock repurchase plan, along with an extension of Intel 3D NAND flash memory partnership involving 3D NAND flash, as well as 96 layer 3D NAND. Meanwhile, various vendors are increasingly talking about how their systems are or will be storage class memory (SCM) ready including for use such as Micron 3D XPoint also known as Intel Optane among others.

Microsoft has placed into public preview Azure Active Directory (AAD) Storage authentication for Azure Blobs and Queues. Azure Storage Explorer is now released as version 1.0. AAD storage authentication enables organizations to implement role-based access control of Azure storage resources. Speaking of Azure, Microsoft has published several architectures, reference and other content at the Azure Virtual Datacenter portal here.

If you have not done so, check out Azure File Sync which is currently in public preview. Having been involved and using it for over a year including during private preview, Azure File Sync is an exciting, useful technology for creating a hybrid distributed file sharing with cloud tiering solutions. Learn more Azure File Sync here and here. In other news, Microsoft has announced a preview as part of the April 2018 Windows 10 build for a Hyper-V Google Android emulator support.

NetApp has had Azure based NAS storage in preview for a while now, and also announced Cloud Volumes on Google Cloud Platform (GCP). In addition to Cloud Volumes on AWS, Azure, and GCP, NetApp also announced enhanced NVMe based storage systems among other updates.

Two companies that have similar names are Opendrives (video workflow acceleration) and Opendrive (cloud storage, backup, and data protection). Meanwhile, data infrastructure startup Pavilion has received new funding as well as begun talking about their NVMe including NVMe over Fabric (NVMeOF) hardware storage system. Long-time data infrastructure converged server storage startup Pivot3 announced additional cloud workload mobility.

Pure storage made a couple of announcements including  FlashArray//X NVMe based shared accelerated storage system as well as NVIDIA (GPU powered) based AIRI Mini for AI/DL/ML.

Have you heard about Snowflake computing, aka, the cloud data warehouse solution? If not, check them out here. Another cloud-related data infrastructure vendor to look into is Upbound.io who have received additional funding for their multi-cloud management solutions.

Building off of recent VMware vSphere updates (here), and Dell Technology World here, the following is an excellent post about Instant Clone in vSphere 6.7, and VMware vSAN HCI assessment tool here.

Check out other industry news, comments, trends perspectives here.

Data Infrastructure Server StorageIO Comments Content

Server StorageIO Commentary in the news, tips and articles

Recent Server StorageIO industry trends perspectives commentary in the news.

Via SearchStorage: Comments Managing storage for IoT data at the enterprise edge
Via SearchCloudComputing: Comments Hybrid cloud deployment demands a change in security mindset
Via SearchStorage: Comments Dell EMC storage IPO, VMware merger plans still unclear
Via SearchStorage: Comments Dell EMC midrange storage keeps its overlapping arrays
Via SearchStorage: Comments Dell EMC all-flash PowerMax replaces VMAX, injects NVMe
Via IronMountain InfoGoto:  The growing Trend of Secondary Data Storage

View more Server, Storage and I/O trends and perspectives comments here.

Data Infrastructure Server StorageIOblog posts

Server StorageIOblog Data Infrastructure Posts

Recent and popular Server StorageIOblog posts include:

Dell Technology World 2018 Announcement Summary
Part II Dell Technology World 2018 Modern Data Center Announcement Details
Part III Dell Technology World 2018 Storage Announcement Details
Part IV Dell Technology World 2018 PowerEdge MX Gen-Z Composable Infrastructure
Part V Dell Technology World 2018 Server Converged Announcement Details
April 2018 Server StorageIO Data Infrastructure Update Newsletter
VMware vSphere vSAN vCenter version 6.7 SDDC Update Summary
PCIe Fundamentals Server Storage I/O Network Essentials
Have you heard about the new CLOUD Act data regulation?
Data Protection Recovery Life Post World Backup Day Pre GDPR
Microsoft Windows Server 2019 Insiders Preview
Application Data Value Characteristics Everything Is Not The Same
Data Infrastructure Resource Links cloud data protection tradecraft trends
IT transformation Serverless Life Beyond DevOps Podcast
Data Protection Diaries Fundamental Topics Tools Techniques Technologies Tips
Introducing Windows Subsystem for Linux WSL Overview
Data Infrastructure Primer Overview (Its Whats Inside The Data Center)
If NVMe is the answer, what are the questions?

View other recent as well as past StorageIOblog posts here

Server StorageIO Recommended Reading (Watching and Listening) List

Software-Defined Data Infrastructure Essentials SDDI SDDC

In addition to my own books including Software Defined Data Infrastructure Essentials (CRC Press 2017) available at Amazon.com (check out special sale price), the following are Server StorageIO data infrastructure recommended reading, watching and listening list items. The Server StorageIO data infrastructure recommended reading list includes various IT, Data Infrastructure and related topics including Intel Recommended Reading List (IRRL) for developers is a good resource to check out. Speaking of my books, Didier Van Hoye (@WorkingHardInIt) has a good review over on his site you can view here, also check out the rest of his great content while there.

Containers, serverless, kubernetes continue to gain in industry adoption, as well as customer deployments. Here is some information about Microsoft Azure Kubernetes Service (AKS). Note that AWS has Elastic Kubernetes Service (EKS), Google, VMware and Pivotal with Pivotal Kubernetes Service (PKS) among others.

Here is an interesting perspective by Ben Kepps about Serverless (e.g. life beyond Kubernetes and containers (e.g. life beyond virtualization which to some is or was life (e.g. life beyond bare metal))) as well as the all to often punditry, evangelism of something new causing something else to be dead.

SNIA has updated their Emerald aka Green energy effectiveness (focus on productivity) measurement specification (V3.01) including NAS NFS file activity (besides block). Learn more at snia.org/forums/green.

Watch for more items to be added to the recommended reading list book shelf soon.

Data Infrastructure Server StorageIO event activities

Events and Activities

Recent and upcoming event activities.

June 27, 2018 – Webinar – TBA

May 29, 2018 – Webinar – Microsoft Windows as a Service

April 24, 2018 – Webinar – AWS and on-site, on-premises hybrid data protection

See more webinars and activities on the Server StorageIO Events page here.

Data Infrastructure Server StorageIO Industry Resources and Links

Various useful links and resources:

Data Infrastructure Recommend Reading and watching list
Microsoft TechNet – Various Microsoft related from Azure to Docker to Windows
storageio.com/links – Various industry links (over 1,000 with more to be added soon)
objectstoragecenter.com – Cloud and object storage topics, tips and news items
OpenStack.org – Various OpenStack related items
storageio.com/downloads – Various presentations and other download material
storageio.com/protect – Various data protection items and topics
thenvmeplace.com – Focus on NVMe trends and technologies
thessdplace.com – NVM and Solid State Disk topics, tips and techniques
storageio.com/converge – Various CI, HCI and related SDS topics
storageio.com/performance – Various server, storage and I/O benchmark and tools
VMware Technical Network – Various VMware related items

Connect and Converse With Us

Storage IO RSS storageio linkedin storageio facebook Server StorageIO on twitter @StorageIO   Google+  Server StorageIO email storageio youtube  storageio instagram

Subscribe to Newsletter – Newsletter Archives StorageIO.comStorageIOblog.com

What this all means and wrap-up

Data Infrastructures are what exists inside physical data centers spanning cloud, converged, hyper-converged, virtual, serverless and other software defined as well as legacy environments. So far this spring there has been a lot of data infrastructure related activity, from new technology announcements, to events, trends among others. Enjoy this edition of the Server StorageIO Data Infrastructure update newsletter and watch for more NVMe, Gen-Z, cloud, data protection among other topics in future posts, articles, events, and newsletters.

Ok, nuff said, for now.

Gs

Greg Schulz – Microsoft MVP Cloud and Data Center Management, VMware vExpert 2010-2018. Author of Software Defined Data Infrastructure Essentials (CRC Press), as well as Cloud and Virtual Data Storage Networking (CRC Press), The Green and Virtual Data Center (CRC Press), Resilient Storage Networks (Elsevier) and twitter @storageio. Courteous comments are welcome for consideration. First published on https://storageioblog.com any reproduction in whole, in part, with changes to content, without source attribution under title or without permission is forbidden.

All Comments, (C) and (TM) belong to their owners/posters, Other content (C) Copyright 2006-2024 Server StorageIO and UnlimitedIO. All Rights Reserved. StorageIO is a registered Trade Mark (TM) of Server StorageIO.

Application Data Volume Velocity Variety Everything Is Not The Same

Application Data Volume Velocity Variety Everything Not The Same

Application Data Volume Velocity Variety Everything Is Not The Same

Application Data Volume Velocity Variety Everything Not The Same

This is part four of a five-part mini-series looking at Application Data Value Characteristics everything is not the same as a companion excerpt from chapter 2 of my new book Software Defined Data Infrastructure Essentials – Cloud, Converged and Virtual Fundamental Server Storage I/O Tradecraft (CRC Press 2017). available at Amazon.com and other global venues. In this post, we continue looking at application and data characteristics with a focus on data volume velocity and variety, after all, everything is not the same, not to mention many different aspects of big data as well as little data.

Application Data Value Software Defined Data Infrastructure Essentials Book SDDC

Volume of Data

More data is growing at a faster rate every day, and that data is being retained for longer periods. Some data being retained has known value, while a growing amount of data has an unknown value. Data is generated or created from many sources, including mobile devices, social networks, web-connected systems or machines, and sensors including IoT and IoD. Besides where data is created from, there are also many consumers of data (applications) that range from legacy to mobile, cloud, IoT among others.

Unknown-value data may eventually have value in the future when somebody realizes that he can do something with it, or a technology tool or application becomes available to transform the data with unknown value into valuable information.

Some data gets retained in its native or raw form, while other data get processed by application program algorithms into summary data, or is curated and aggregated with other data to be transformed into new useful data. The figure below shows, from left to right and front to back, more data being created, and that data also getting larger over time. For example, on the left are two data items, objects, files, or blocks representing some information.

In the center of the following figure are more columns and rows of data, with each of those data items also becoming larger. Moving farther to the right, there are yet more data items stacked up higher, as well as across and farther back, with those items also being larger. The following figure can represent blocks of storage, files in a file system, rows, and columns in a database or key-value repository, or objects in a cloud or object storage system.

Application Data Value sddc
Increasing data velocity and volume, more data and data getting larger

In addition to more data being created, some of that data is relatively small in terms of the records or data structure entities being stored. However, there can be a large quantity of those smaller data items. In addition to the amount of data, as well as the size of the data, protection or overhead copies of data are also kept.

Another dimension is that data is also getting larger where the data structures describing a piece of data for an application have increased in size. For example, a still photograph was taken with a digital camera, cell phone, or another mobile handheld device, drone, or other IoT device, increases in size with each new generation of cameras as there are more megapixels.

Variety of Data

In addition to having value and volume, there are also different varieties of data, including ephemeral (temporary), persistent, primary, metadata, structured, semi-structured, unstructured, little, and big data. Keep in mind that programs, applications, tools, and utilities get stored as data, while they also use, create, access, and manage data.

There is also primary data and metadata, or data about data, as well as system data that is also sometimes referred to as metadata. Here is where context comes into play as part of tradecraft, as there can be metadata describing data being used by programs, as well as metadata about systems, applications, file systems, databases, and storage systems, among other things, including little and big data.

Context also matters regarding big data, as there are applications such as statistical analysis software and Hadoop, among others, for processing (analyzing) large amounts of data. The data being processed may not be big regarding the records or data entity items, but there may be a large volume. In addition to big data analytics, data, and applications, there is also data that is very big (as well as large volumes or collections of data sets).

For example, video and audio, among others, may also be referred to as big fast data, or large data. A challenge with larger data items is the complexity of moving over the distance promptly, as well as processing requiring new approaches, algorithms, data structures, and storage management techniques.

Likewise, the challenges with large volumes of smaller data are similar in that data needs to be moved, protected, preserved, and served cost-effectively for long periods of time. Both large and small data are stored (in memory or storage) in various types of data repositories.

In general, data in repositories is accessed locally, remotely, or via a cloud using:

  • Object and blobs stream, queue, and Application Programming Interface (API)
  • File-based using local or networked file systems
  • Block-based access of disk partitions, LUNs (logical unit numbers), or volumes

The following figure shows varieties of application data value including (left) photos or images, audio, videos, and various log, event, and telemetry data, as well as (right) sparse and dense data.

Application Data Value bits bytes blocks blobs bitstreams sddc
Varieties of data (bits, bytes, blocks, blobs, and bitstreams)

Velocity of Data

Data, in addition to having value (known, unknown, or none), volume (size and quantity), and variety (structured, unstructured, semi structured, primary, metadata, small, big), also has velocity. Velocity refers to how fast (or slowly) data is accessed, including being stored, retrieved, updated, scanned, or if it is active (updated, or fixed static) or dormant and inactive. In addition to data access and life cycle, velocity also refers to how data is used, such as random or sequential or some combination. Think of data velocity as how data, or streams of data, flow in various ways.

Velocity also describes how data is used and accessed, including:

  • Active (hot), static (warm and WORM), or dormant (cold)
  • Random or sequential, read or write-accessed
  • Real-time (online, synchronous) or time-delayed

Why this matters is that by understanding and knowing how applications use data, or how data is accessed via applications, you can make informed decisions. Also, having insight enables how to design, configure, and manage servers, storage, and I/O resources (hardware, software, services) to meet various needs. Understanding Application Data Value including the velocity of the data both for when it is created as well as when used is important for aligning the applicable performance techniques and technologies.

Where to learn more

Learn more about Application Data Value, application characteristics, performance, availability, capacity, economic (PACE) along with data protection, software-defined data center (SDDC), software-defined data infrastructures (SDDI) and related topics via the following links:

SDDC Data Infrastructure

Additional learning experiences along with common questions (and answers), as well as tips can be found in Software Defined Data Infrastructure Essentials book.

Software Defined Data Infrastructure Essentials Book SDDC

What this all means and wrap-up

Data has different value, size, as well as velocity as part of its characteristic including how used by various applications. Keep in mind that with Application Data Value Characteristics Everything Is Not The Same across various organizations, data centers, data infrastructures spanning legacy, cloud and other software defined data center (SDDC) environments. Continue reading the next post (Part V Application Data Access life cycle Patterns Everything Is Not The Same) in this series here.

Ok, nuff said, for now.

Gs

Greg Schulz – Microsoft MVP Cloud and Data Center Management, VMware vExpert 2010-2017 (vSAN and vCloud). Author of Software Defined Data Infrastructure Essentials (CRC Press), as well as Cloud and Virtual Data Storage Networking (CRC Press), The Green and Virtual Data Center (CRC Press), Resilient Storage Networks (Elsevier) and twitter @storageio. Courteous comments are welcome for consideration. First published on https://storageioblog.com any reproduction in whole, in part, with changes to content, without source attribution under title or without permission is forbidden.

All Comments, (C) and (TM) belong to their owners/posters, Other content (C) Copyright 2006-2024 Server StorageIO and UnlimitedIO. All Rights Reserved. StorageIO is a registered Trade Mark (TM) of Server StorageIO.

Application Data Access Lifecycle Patterns Everything Is Not The Same

Application Data Access Life cycle Patterns Everything Is Not The Same(Part V)

Application Data Access Life cycle Patterns Everything Is Not The Same

Application Data Access Life cycle Patterns Everything Is Not The Same

This is part five of a five-part mini-series looking at Application Data Value Characteristics everything is not the same as a companion excerpt from chapter 2 of my new book Software Defined Data Infrastructure Essentials – Cloud, Converged and Virtual Fundamental Server Storage I/O Tradecraft (CRC Press 2017). available at Amazon.com and other global venues. In this post, we look at various application and data lifecycle patterns as well as wrap up this series.

Application Data Value Software Defined Data Infrastructure Essentials Book SDDC

Active (Hot), Static (Warm and WORM), or Dormant (Cold) Data and Lifecycles

When it comes to Application Data Value, a common question I hear is why not keep all data?

If the data has value, and you have a large enough budget, why not? On the other hand, most organizations have a budget and other constraints that determine how much and what data to retain.

Another common question I get asked (or told) it isn’t the objective to keep less data to cut costs?

If the data has no value, then get rid of it. On the other hand, if data has value or unknown value, then find ways to remove the cost of keeping more data for longer periods of time so its value can be realized.

In general, the data life cycle (called by some cradle to grave, birth or creation to disposition) is created, save and store, perhaps update and read with changing access patterns over time, along with value. During that time, the data (which includes applications and their settings) will be protected with copies or some other technique, and eventually disposed of.

Between the time when data is created and when it is disposed of, there are many variations of what gets done and needs to be done. Considering static data for a moment, some applications and their data, or data and their applications, create data which is for a short period, then goes dormant, then is active again briefly before going cold (see the left side of the following figure). This is a classic application, data, and information life-cycle model (ILM), and tiering or data movement and migration that still applies for some scenarios.

Application Data Value
Changing data access patterns for different applications

However, a newer scenario over the past several years that continues to increase is shown on the right side of the above figure. In this scenario, data is initially active for updates, then goes cold or WORM (Write Once/Read Many); however, it warms back up as a static reference, on the web, as big data, and for other uses where it is used to create new data and information.

Data, in addition to its other attributes already mentioned, can be active (hot), residing in a memory cache, buffers inside a server, or on a fast storage appliance or caching appliance. Hot data means that it is actively being used for reads or writes (this is what the term Heat map pertains to in the context of the server, storage data, and applications. The heat map shows where the hot or active data is along with its other characteristics.

Context is important here, as there are also IT facilities heat maps, which refer to physical facilities including what servers are consuming power and generating heat. Note that some current and emerging data center infrastructure management (DCIM) tools can correlate the physical facilities power, cooling, and heat to actual work being done from an applications perspective. This correlated or converged management view enables more granular analysis and effective decision-making on how to best utilize data infrastructure resources.

In addition to being hot or active, data can be warm (not as heavily accessed) or cold (rarely if ever accessed), as well as online, near-line, or off-line. As their names imply, warm data may occasionally be used, either updated and written, or static and just being read. Some data also gets protected as WORM data using hardware or software technologies. WORM (immutable) data, not to be confused with warm data, is fixed or immutable (cannot be changed).

When looking at data (or storage), it is important to see when the data was created as well as when it was modified. However, you should avoid the mistake of looking only at when it was created or modified: Instead, also look to see when it was the last read, as well as how often it is read. You might find that some data has not been updated for several years, but it is still accessed several times an hour or minute. Also, keep in mind that the metadata about the actual data may be being updated, even while the data itself is static.

Also, look at your applications characteristics as well as how data gets used, to see if it is conducive to caching or automated tiering based on activity, events, or time. For example, there is a large amount of data for an energy or oil exploration project that normally sits on slower lower-cost storage, but that now and then some analysis needs to run on.

Using data and storage management tools, given notice or based on activity, which large or big data could be promoted to faster storage, or applications migrated to be closer to the data to speed up processing. Another example is weekly, monthly, quarterly, or year-end processing of financial, accounting, payroll, inventory, or enterprise resource planning (ERP) schedules. Knowing how and when the applications use the data, which is also understanding the data, automated tools, and policies, can be used to tier or cache data to speed up processing and thereby boost productivity.

All applications have performance, availability, capacity, economic (PACE) attributes, however:

  • PACE attributes vary by Application Data Value and usage
  • Some applications and their data are more active than others
  • PACE characteristics may vary within different parts of an application
  • PACE application and data characteristics along with value change over time

Read more about Application Data Value, PACE and application characteristics in Software Defined Data Infrastructure Essentials (CRC Press 2017).

Where to learn more

Learn more about Application Data Value, application characteristics, PACE along with data protection, software defined data center (SDDC), software defined data infrastructures (SDDI) and related topics via the following links:

SDDC Data Infrastructure

Additional learning experiences along with common questions (and answers), as well as tips can be found in Software Defined Data Infrastructure Essentials book.

Software Defined Data Infrastructure Essentials Book SDDC

What this all means and wrap-up

Keep in mind that Application Data Value everything is not the same across various organizations, data centers, data infrastructures, data and the applications that use them.

Also keep in mind that there is more data being created, the size of those data items, files, objects, entities, records are also increasing, as well as the speed at which they get created and accessed. The challenge is not just that there is more data, or data is bigger, or accessed faster, it’s all of those along with changing value as well as diverse applications to keep in perspective. With new Global Data Protection Regulations (GDPR) going into effect May 25, 2018, now is a good time to assess and gain insight into what data you have, its value, retention as well as disposition policies.

Remember, there are different data types, value, life-cycle, volume and velocity that change over time, and with Application Data Value Everything Is Not The Same, so why treat and manage everything the same?

Ok, nuff said, for now.

Gs

Greg Schulz – Microsoft MVP Cloud and Data Center Management, VMware vExpert 2010-2017 (vSAN and vCloud). Author of Software Defined Data Infrastructure Essentials (CRC Press), as well as Cloud and Virtual Data Storage Networking (CRC Press), The Green and Virtual Data Center (CRC Press), Resilient Storage Networks (Elsevier) and twitter @storageio. Courteous comments are welcome for consideration. First published on https://storageioblog.com any reproduction in whole, in part, with changes to content, without source attribution under title or without permission is forbidden.

All Comments, (C) and (TM) belong to their owners/posters, Other content (C) Copyright 2006-2024 Server StorageIO and UnlimitedIO. All Rights Reserved. StorageIO is a registered Trade Mark (TM) of Server StorageIO.

Data Infrastructure Resource Links cloud data protection tradecraft trends

Data Infrastructure Resource Links Server Storage I/O Network

data infrastructure resource links server storage I/O cloud data protection tradecraft links

By Greg Schulzwww.storageioblog.com April 28, 2018

Various data infrastructure resource links.

SDDC Data Infrastructure

The following are a collection of server storageioblog data infrastructure resource links.

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April 2015 Server Storageio Update Newsletter

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Microsoft Windows Server Azure Nano Life Cycle Updates

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Emcworld 2016 Emc Hybrid And Converged Clouds Your Way

Server Storageio 2016 Update Newsletter

Server Storageio Industry Trends Perspectives Report Wekaio Matrix

Data Quantum Revenues Continue Grow

Chelsio Storage Ip Networks Enable Data Infrastructures

Post Holiday It Shopping Bargains Dell Buying Exanet

Predictions Did Mayans Have It Right Or Did We Read It Wrong

Overview Review Microsoft Refs Reliable File System

Gaining Server Storage Io Insight Microsoft Windows Server 2016

How Many Degrees Separate You And Your Information

Inaugural Storageio Newsletter

Spring 2010 Storageio Newsletter

Storage Comments From The Field And Customers In The Trenches

Virtual Storage And Social Media What Did Emc Not Announce

Are Social Media And Networking A Waste Of Time

Congratulations To New And Returning 2012 Vmware Vexperts

Hitting The Road Again

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Trains Going Green Ah Well Maybe Blue

Happy Earth Day 2009

Mirror Mirror On The Wall Who Is The Greenest Of Them All

Green Virtual Servers Storage And Networking 2008 Beijing Olympics

Hot Storage Topics Converge On Chicago Next Week

John Carpenters Escape From New York Back From Storage Decisions Ny 2008

Does Dell Have A Cloudy Cloud Strategy Story Part I

Dell Updates Storage Center Operating System 7 Scos 7

Lenovo Buys Ibms Xseries Aka X86 Server Business Emc

Cloud And Virtual Data Storage Networking Book Vmworld 2011 Debut

Cloud And Virtual Data Storage Networking Book Released

Server Storageio September 2015 Update Newsletter

Some Windows Server Storage Io Related Commands

Server Storageio November 2015 Update Newsletter

Dell Emc Azure Stack Hybrid Cloud Solution

Msp Business Journal Names Greg Schulz An Eco Tech Warrior

Continuing Education And Refresher Time Raid And Luns

Many Different Implementations Of Raid

Wide World Of Archiving Life Beyond Compliance

Comfort Zones Stating What Might Be Obvious To Some

The Differences Between Singapore And Houston In May

Do Disk Based Vtls Draw Less Power Than Tape

More On Fibre Channel Over Ethernet Fcoe

Green Hype Or Reality

Thank You Gartner For Generating Awareness For My New Book

Why Xiv Is So Important To Ibms Storage Business

Das Sas Fcoe Green Efficient Storage And Io Podcast Faqs

Cmg Enabling The Green And Virtual Data Center

It Belt Tightening And Stratigies For It Economic Sustainment

Vendors Who Dont Want To Be Virtualized

Did Someone Forget To Tell Dell That Tape Is Dead

Ssd Activity Continues To Go Virtually Round And Round

All Work And No Play Ok How About An Education Half Day

Industry Trend And Perspective Seagate Changes Disk Drive Warranties

Just For Fun Of Flying

Raid Data Protection Remains Relevant

Protecting And Storing Personal Digital Documents

Is There Still Innovation For It And Storage

Io Virtualization Iov Revisited

Shifting Industry Trend From Purchase To Leasing

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Us Epa Looking For Industry Input On Energy Star For Storage

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Ibm Out Oracle In As Buyer Of Sun

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Data Center Io Bottlenecks Performance Issues And Impacts

Clarifying Clustered Storage Confusion

Green It Confusion Continues Opportunities Missed

Clouds Are Like Electricity Dont Be Scared

Hp Buys One Of The Seven Networking Dwarfs And Gets A Bargain

Should Everything Be Virtualized

Optimize Data Storage For Performance And Capacity Efficiency

Justifying Green It And Home Hardware Upgrades With Energystar

How To Win Approval For Upgrades Link Them To Business Benefits

What Is The Future Of Servers

Ssd And Storage System Performance

Green It And Virtual Data Centers

Emc Storage And Management Software Getting Fast

Its Us Census Time What About It Data Centers

Nas Nasa And Nascar Do They Have Anything In Common

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Happy Earth Day 2010

Who Or What Is Your Sphere Of Influence

Apple Ipad Is It A Business Itool Or Itoy

Cloud Conversations Nirvanix Shutdown Caused Cloud Confidence Concerns

Industry Trends And Perspectives Raid Rebuild Rates

Industry Trends And Perspectives Storage Virtualization And Virtual Storage

Industry Trends And Perspectives Converged Networking And Io Virtualization Iov

Industry Trends And Perspectives Tiered Storage Systems And Mediums

Initial Virtumania Appearance Episode 14 With Fellow Vexperts

Industry Trends And Perspectives Tiered Hypervisors And Microsoft Hyperv

Vmware Vexpert 2010 Thank You Im Honored To Be Named A Member

Industry Trends And Perspectives Blog Series

My Favorite Late Summer Reading Material

Supreme Court Rules Sarbox Intact Oversight Board Changes

While Hp And Dell Make Counter Bids Exclusive Interview With 3par Ceo David Scott

End To End E2e Systems Resource Analysis Sra For Cloud And Virtual Environments

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Storageio Momentus Hybrid Hard Disk Drive Hhdd Moments

Buzzword Bingo 1 0 Are You Ready For Fall Product Announcemnts

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Securing Data At Rest Self Encrypting Disks Seds

Buzzword Bingo And Acronym Update V2 011

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Storageio Going Dutch Seminar For Storage And Io Professionals

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Dell Storage Forum 2011 Revisited

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Time In And Around Clouds

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Industry Trends And Perspectives Public And Private It Clouds

Dude Is Dell Going To Buy Brocade

Spring May 2012 Storageio News Letter

Data Migration Tips

Cloud Conversation Thanks Gartner For Saying What Has Been Said

December 2012 Storageio Update News Letter

January 2013 Server And Storageio Update Newsletter

Behind The Scenes Santa Claus Global Cloud Story

Emc Vmax 10k Looks Like High End Storage Systems Are Still Alive Part Iii

Many Faces Of Storage Hypervisor Virtual Storage Or Storage Virtualization

February 2013 Server And Storageio Update Newsletter

Xtremio Xtremsw And Xtremsf Emc Flash Ssd Portfolio Redefined

Some Things Keep Going Around Seagate Ships 2 Billion Hdds

Where Has The Fcoe Hype And Fud Gone With Poll

A Pivotal Or Cloudy Moment For Emc And Vmware

March Metrics And Measuring Social Media

Are Your Analyst Blogger Media Or Press Requests Being Read

March 2013 Server And Storageio Update Newsletter

Pressure Cooker Good

Hp Moonshot 1500 Software Defined Capable Compute Servers

Netapp And Akorri An E2e Cross Technology Domain Sra Play

Full Rss Archive Feeds Are Now Available For Storageioblog

2013 Server Storageio Update Newsletter

Morning Summer Storms Walking Midwest

Ibm Buys Softlayer Software Defined Infrastructures Clouds

Upgrading Lenovo X1 Windows 7 Samsung 840 Ssd

Geek Gadgets Kill A Watt Meter

Green Storage Practical Ways To Reduce Power Consumption

Data Proteciton For Virtual Environments At Vmware Vmworld

From Ilm To Iim Is This A Solution Sell Looking For A Problem

Industry Trends And Perspectives Tape Disk And Dedupe Coexistence

Ilm Has It Losts Its Meaning

Is Ibm Xiv Still Relevant

Data Proteciton For Virtual Environments

Spc And Storage Benchmarking Games

Server And Storage Virtualization Life Beyond Consolidation

Epa Draft 3 Of Energy Star For Computer Server Specification

Cloud Virtual Server Storage Io Technology Tiering

Disruptive Updates

Virtual Cloud Availability Shared Responsibility Common Sense

Storage Performance

Will 6gb Sas Kill Fibre Channel

Poll Whats Do You Think Of It Clouds

Closing The Green Gap Green Washing May Be Endangered However Addressing Real Green Issues Is Here To Stay

Catch Of The Day Or Post Of The Day

Availability Or Lack There Of Lessons From Our Frail Aging Infrastructure

Cisco Wins Fcoe Pre Season And Primaries Now For The Main Event

Power Cooling Floor Space Environmental Pcfe And Green Metrics

Tape Talk Changing Role Of Tape

Sas Disk Drives Appearing In Larger Mid Range Arrays

Blog Post March Metric Madness Fun With Simple Math

Hard Product Vs Soft Product

Optical Storage Oppourtunities Or Obsolence

Storage Efficiency And Optimization The Other Green

Smb Capacity Planning Focusing On Energy Conservation

Whats Your Take On Ftc Guidelines For Bloggers

Technology And Traveling

Clouds And Data Loss Time For Cdp Commonsense Data Protection

Epa Energy Star For Data Center Storage Update 2

From Bits To Bytes Decoding Encoding

Industry Trends And Perspectives 6gb Sas And Das Are Not Dumb A Storage

As The Hard Disk Drive Hdd Continues To Spin

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Are Hard Disk Drives Hdds Getting To Big

2011 Summer Momentus Hybrid Hard Disk Drive Hhdd Moment

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Getting Sasy The Other Shared Storage Option For Disk And Ssd Systems

Supporting It Growth Demand During Economic Uncertain Times

Inaugural Ssd Show

Care Coraid Content Conversation

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Depends

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A Storage Io Momentus Moment

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Pue Are You Managing Power Energy Or Productivity

Emc Vnx Mcx Storage Io Work

The New Green Gaining Realistic Economic Efficiencys Now

Closing The Green Gap Wsradio Internet Radio Interview

Determining Computer Or Server Energy Use

Epa Energy Star For Data Center Storage Update

Saving Money With Green It Time To Invest In Information Factories

Webcast E2e Awareness And Insight For It Environments

Ibm Server Side Storage Io Ssd Flash Cache Software

Part Ii Emc Evolves Enterprise Data Protection Enhancements

Cisco Buys Whiptail Continuing Storage Storage Io Flash Cash Cache Dash

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Raid Relevance Revisited

Have You Heard Of 2drs Data Protection Technology

July 2010 Odds And Ends Perspectives Tips And Articles

Has Ssd Put Hard Disk Drives Hdds On Endangered Species List

Seagate Proof Life Enterprise Hdd Enhancements

Seagate To Say Goodbye To Cayman Islands Hello Ireland

Cloud Conversations Gaining Cloud Confidence From Insights Into Aws Outages

Have Vtls Or Vxls Become Zombies Declared Dead Yet Still Alive

Tiered Communication And Media Venues

Are You On The Storageio It Data Infrastructure Industry Links Page

Green Storage Is Alive And Well Energy Star Enterprise Storage Stakeholder Meeting Details

Tape Talk Time

Back To School Dedupe School

Storageio V20 11 2011 Events Seminars And Web Casts Schedule

Getting Caught Up And Holiday Shopping

Performance Availability Storageioblog Featured Itke Guest Blog

The New Green It Efficient Effective Smart And Productive

Dude Is Dell Doing A Disk Deal Again With Compellent

Intelligent Power Management Ipm And Second Generation Maid 20 On The Rise

2010 And 2011 Trends Perspectives And Predictions More Of The Same

Mainframe Cmg Virtualization Storage And Zombie Technologies

Vmworld 2010 Virtual Roads Clouds And Inxs Devil Inside

Green Power And Cooling Tools And Calculators

Green It Green Gap Tiered Energy And Green Myths

Vmworld 2013 Vmware Server Storage Io Networking Update Day 1

Part Ii Xtremio Xtremsw And Xtremsf Emc Flash Ssd Portfolio Redefined

Datadynamics Storagex 70 File Data Management Migration Software

Whats Your Take On Open Virtualization Alliance And Vmware

September October Server Storageio Update Newsletter

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Open Data Center Alliance Odca Bmw Private Cloud Strategy

Happy 20th Birthday Microsoft Windows Server Get Ready Windows Server 2016

Server Storageio March 2016 Update Newsletter

Netapp Ef540 Something Familiar Something New

Data Footprint Reduction Part 1 Life Beyond Dedupe And Changing Data Lifecycles

Emc Vipr Software Defined Object Storage Part Ii

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Breaking Vmware Esxi 55 Acpi Boot Loop Lenovo Td350

Storageio In The News

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Matt Vogt Computex Talks Vmware Vcops Podcast

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Storage Virtualization In Band Vs Out Of Band Debates To Be Resurrected

Snow Fun And Information Technology They Do Mix

Technology Tiering Servers Storage And Snow Removal

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Summer Weddings Emcdatadomain And Hpibrix

Server Storage Io Intel Nuc Nick Knack Notes Second Impressions

Emc Vfcache Respinning Ssd And Intelligent Caching Part Ii

Hds Claus Mikkelsen Talking Storage Snw Fall 2012

How To Write Publish And Promote A Book Or Blog

Oracle Xsigo Vmware Nicira Sdn And Iov Io Io Its Off To Work They Go

Open Data Center Alliance Odca Publishes Two New Cloud Usage Models

Nand Flash Sata Ssd Ddr3 Dimm Slot

Server Storageio February 2016 Update Newsletter

Server Storageio January 2016 Update Newsletter

June 2017 Server Storageio Data Infrastructures Update Newsletter

Ibms Storwize Or Wise Storage The V7000 And Dfr

Re Visiting If Ibm Xiv Is Still Relevant With V7000

Part I Puresystems Something Old Something New Something From Big Blue

Part V Puresystems Something Old Something New Something From Big Blue

Part Iv Puresystems Something Old Something New Something From Big Blue

Part Ii Puresystems Something Old Something New Something From Big Blue

Microsoft Azure Cloud Software Defined Data Infrastructure Reference Architecture Resources

Happy 100th Birthday Or Anniversary Wishes

Azure Stack Tp3 Overview Preview Review Part Ii

Data Protection Diaries Data Protection

March2014 Storageio Newsletter Cisco Cloud Vmware Vsan

June 2014 Server Storageio Update Newsletter

Chat With Cash Coleman Talking Cleardb Cloud Database And Johnny Cash

April 2014 Server Storageio Update Newsletter

Acadia Vce Vmware Cisco Emc Virtual Computing Environment

Storageio Spring Keynote And Speaking Tour V2008

Server Storageio April 2016 Update Newsletter

Cloud Conversations Loss Of Data Access Vs Data Loss

Hpe Buying Server Storage Io Data Infrastructures

January 2017 Server Storageio Update Newsletter

Top Vblog 2017 Voting Open

Data Infrastructure Tradecraft Trends

Converged Ci Hyperconverged Hci Mean Storage Io

Popular Viewed Storageioblog Posts 2016

March 2017 Server Storageio Update Newsletter

Top Storage World Decade

Back To School Shopping Dude Dell Digests 3par Disk Storage

Does Ibm Power7 Processor Announcement Signal Storage Upgrades

Do You Know Hds Or What It Means

Is The New Hds Vsp Really The Mvsp

Hds Mid Summer Storage Converged Compute Enhancements

Object Storage News Trends Cloud Bulk Storage

Hds Buys Bluearc Any Surprises Here

June 2015 Server Storageio Update Newsletter

Server Storageio Holiday Seasons 2016

Do Software Vendors Eliminate Or Move Location Of Vendor Lock In

Vendor Lockin Responsibiity

Spam Of A Different Kind

Part Iii Puresystems Something Old Something New Something From Big Blue

Emc Vmax 10k Looks Like High End Storage Systems Are Still Alive

Which Enterprise Hdd Content Application Testing

Which Enterprise Hdd Content Server Test Configuration

Hdd Ssd Flash Storage Iops

Which Enterprise Hdd Use For Database Workloads

Enterprise Hdd For Content Server Different File Size

Which Enterprise Hdd General Io Performance

Enterprise Hdds Evolve For Content Server Applications

Achieve Flexible Data Protection

Additional learning experiences along with common questions (and answers), as well as tips can be found in Software Defined Data Infrastructure Essentials book.

Software Defined Data Infrastructure Essentials Book SDDC

What This All Means

SDDC Data Infrastructure

Check out the above links to data infrastructure resource links.

Ok, nuff said, for now.

Gs

Greg Schulz – Microsoft MVP Cloud and Data Center Management, VMware vExpert 2010-2017 (vSAN and vCloud). Author of Software Defined Data Infrastructure Essentials (CRC Press), as well as Cloud and Virtual Data Storage Networking (CRC Press), The Green and Virtual Data Center (CRC Press), Resilient Storage Networks (Elsevier) and twitter @storageio. Courteous comments are welcome for consideration. First published on https://storageioblog.com any reproduction in whole, in part, with changes to content, without source attribution under title or without permission is forbidden.

All Comments, (C) and (TM) belong to their owners/posters, Other content (C) Copyright 2006-2024 Server StorageIO and UnlimitedIO. All Rights Reserved. StorageIO is a registered Trade Mark (TM) of Server StorageIO.

Data Protection Diaries Access Availability RAID Erasure Codes LRC Deep Dive

Access Availability RAID Erasure Codes including LRC Deep Dive

Companion to Software Defined Data Infrastructure Essentials – Cloud, Converged, Virtual Fundamental Server Storage I/O Tradecraft ( CRC Press 2017)

server storage I/O data infrastructure trends

By Greg Schulzwww.storageioblog.com November 26, 2017

This is Part 3 of a multi-part series on Data Protection fundamental tools topics techniques terms technologies trends tradecraft tips as a follow-up to my Data Protection Diaries series, as well as a companion to my new book Software Defined Data Infrastructure Essentials – Cloud, Converged, Virtual Server Storage I/O Fundamental tradecraft (CRC Press 2017).

Software Defined Data Infrastructure Essentials Book SDDC

Click here to view the previous post Part 2 Reliability, Availability, Serviceability (RAS) Data Protection Fundamentals, and click here to view the next post Part 4 Data Protection Recovery Points (Archive, Backup, Snapshots, Versions).

Post in the series includes excerpts from Software Defined Data Infrastructure (SDDI) pertaining to data protection for legacy along with software defined data centers ( SDDC), data infrastructures in general along with related topics. In addition to excerpts, the posts also contain links to articles, tips, posts, videos, webinars, events and other companion material. Note that figure numbers in this series are those from the SDDI book and not in the order that they appear in the posts.

In this post part of the Data Protection diaries series as well as companion to Chapter 9 of SDDI Essentials book, we are going on a longer, deeper dive. We are going to look at availability, access and durability including mirror, replication, RAID including various traditional and newer parity approaches such as Erasure Codes ( EC), Local Reconstruction Code (LRC), Reed Solomon (RS) also known as RAID 2 among others. Later posts in this series look at point in time data protection to support recovery to a given time (e.g. RPO), while this and the previous post look at maintaining access and availability.

Keep in mind that if something can fail, it probably will, also that everything is not the same meaning different environments, application workloads (along with their data). Different environments and applications have diverse performance, availability, capacity economic (PACE) attributes, along with service level objectives ( SLOs). Various SLOs include PACE attributes, recovery point objectives ( RPO), recovery time objective ( RTO) among others.

Availability, accessibility and durability (see part two in this series) along with associated RAS topics are part of what enable RTO, as well as meet Faults (or failures) to tolerate ( FTT). This means that different fault tolerance modes ( FTM) determine what technologies, tools, trends and techniques to use to meet different RTO, FTT and application PACE needs.

Maintaining access and availability along with durability (e.g. how many copies of data as well as where stored) protects against loss or failure of a component device ( SSD, HDDs, adapters, power supply, controller), node or system, appliance, server, rack, clusters, stamps, data center, availability zones, regions, or other Fault or Failure domains spanning hardware, software, and services.

SDDC, SDI, SDDI data infrastructure
Figure 1.5 Data Infrastructures and other IT Infrastructure Layers

Data Protection Access Availability RAID Erasure Codes

This is a good place to mention some context for RAID and RAID array, which can mean different things pertaining to Data Protection. Some people associate RAID with a hardware storage array, or with a RAID card. Other people consider an array to be a storage array that is a RAID enabled storage system. A trend is to refer to legacy storage systems as RAID arrays or hardware-based RAID, to differentiate from newer implementations.

Context comes into play in that a RAID group (i.e., a collection of HDDs or SSD that is part of a RAID set) can be referred to as an array, a RAID array, or a virtual array. What this means is that while some RAID implementations may not be relevant, there are many new and evolving variations extending parity based protection making at least software-defined RAID still relevant

Keep context in mind, and don’t be afraid to ask what someone is referring to: a particular vendor storage system, a RAID implementation or packaging, a storage array, or a virtual array. Also keep the context of the virtual array in perspective vs. storage virtualization and virtual storage. RAID as a term is used to refer to different modes such as mirroring or parity, and parity can be legacy RAID 4, 5, or 6 along with erasure codes (EC). Note some people refer to erasure codes in the context of not being a RAID system, which can be an inference to not being a legacy storage system running hardware RAID (e.g. not software or software defined).

The following figure (9.13) shows various availability protection schemes (e.g. not recovery point) that maintain access while protecting against loss of a component, device, system, server, site, region or other part of a fault domain. Since everything is not the same with environments and applications having different Performance Availability Capacity Economic ( PACE) attributes, there are various approaches for enabling availability along with accessibility.

Keep in mind that RAID and Erasure codes along with their various, as well as replication and mirroring by themselves are not a replacement for backup or other point in time (e.g. enable recovery point) protection.

Instead, availability technologies such as RAID and erasure code along with mirror as well as replication need to be combined with snapshots, point in time copies, consistency points, checkpoints, backups among other recovery point protection for complete data protection.

Speaking of replacement for backup, while many vendors and their pundits claIm or want to see backup as being dead, as long as they keep talking about backup instead of broader data protection backup will remain alive.

SDDC SDDI RAID Parity Erasure Code EC
Figure 9.13 Various RAID, Mirror, Parity and Erasure Code (EC) approaches

Different RAID levels (including parity, EC, LRC and RS based) will affect storage energy effectiveness, similar to various SSD or HDD performance capacity characteristics; however, a balance of performance, availability, capacity, and energy needs to occur to meet application service needs. For example, RAID 1 mirroring or RAID 10 mirroring and striping use more HDDs and, thus, power, but will yield better performance than RAID 6 and erasure code parity protection.

 

Normal performance

 

Availability

Performance overhead

Rebuild overhead

Availability overhead

RAID 0 (stripe)

Very good read & write

None

None

Full volume restore

None

RAID 1 (mirror or replicate)

Good reads; writes = device speed

Very good; two or more copies

Multiple copies can benefit reads

Re-synchronize with existing volume

2:1 for dual, 3:1 for three-way copies

RAID 4 (stripe with dedicated parity, i.e., 4 + 1 = 5 drives total)

Poor writes without cache

Good for smaller drive groups and devices

High on write without cache (i.e., parity)

Moderate to high, based on number and type of drives

Varies; 1 Parity/N, where N = number of devices

RAID 5
(stripe with rotating parity, 4 + 1 = 5 drives)

Poor writes without cache

Good for smaller drive groups and devices

High on write without cache (i.e., parity)

Moderate to high, based on number and type of drives

Varies
1 Parity/N, where N = number of devices

RAID 6
(stripe with dual parity, 4 + 2 = 6 drives)

Poor writes without cache

Better for larger drive groups and devices

High on write without cache (i.e., parity)

Moderate to high, based on number and type of drives

Varies; 2 Parity/N, where N = number of devices

RAID 10
(mirror and stripe)

Good

Good

Minimum

Re-synchronize with existing volume

Twice mirror capacity stripe drives

Reed-Solomon (RS) parity, also known as erasure code (EC), local reconstruction code (LRC), and SHEC

Ok for reads, slow writes; good for static and cold data with front-end cache

Good

High on writes (CPU for parity calculation, extra I/O operations)

Moderate to high, based on number and type of drives, how implemented, extra I/Os for reconstruction

Varies, low overhead when using large number of devices; CPU, I/O, and network overhead.

Table 9.3 Common RAID Characteristics

Besides those shown in table 9.3, other RAID including parity based approaches include 2 (Reed Solomon), 3 (synchronized stripe and dedicated parity) along with others including combinations such as 10, 01, 50, 60 among others.

Similar to legacy parity-based RAID, some erasure code implementations use narrow drive groups while others use larger ones to increase protection and reduce capacity overhead. For example, some larger enterprise-class storage systems (RAID arrays) use narrow 3 + 1 or 4 + 1 RAID 5 or 4 + 2 or 6 + 2 RAID 6, which have higher protection storage capacity overhead and fault=impact footprint.

On the other hand, many smaller mid-range and scale-out storage systems, appliances, and solutions support wide stripes such as 7 + 1, 15 + 1, or larger RAID 5, or 14 + 2 or larger RAID 6. These solutions trade the lower storage capacity protection overhead for risk of a multiple drive failures or impacts. Similarly, some EC implementations use relatively small groups such as 6, 2 (8 drives) or 4, 2 (6 drives), while others use 14, 4 (18 drives), 16, 4 (20 drives), or larger.

Table 9.4 shows options for a number of data devices (k) vs. a number of protect devices (m).

k
(data devices)

m
(protect devices)

Availability;
Resiliency

Space capacity overhead

Normal performance

FTT

Comments;
Examples

Narrow

Wide

Very good;
Low impact of rebuild

Very high

Good (R/W)

Very good

Trade space for RAS;
Larger m vs. k;
1, 1; 1, 2; 2, 2; 4, 5

Narrow

Narrow

Good

Good

Good (R/W)

Good

Use with smaller drive groups;
2, 1; 3, 1; 6, 2

Wide

Narrow

Ok to good;
With larger m value

Low as m gets larger

Good (read);
Writes can be slow

Ok to good

Smaller m can impact rebuild;
3, 1; 7, 1; 14, 2; 13, 3

Wide

Wide

Very good;
Balanced

High

Good

Very good

Trade space for RAS;
2, 2; 4, 4; 8, 4; 18, 6

Table 9.4. Comparing Various Data Device vs. Protect Device Configurations

Note that wide k with no m, such as 4, 0, would not have protection. If you are focused on reducing costs and storage space capacity overhead, then a wider (i.e., more devices) with fewer protect devices might make sense. On the other hand, if performance, availability, and minimal to no impact during rebuild or reconstruction are important, then a narrower drive set, or a smaller ratio of data to protect drives, might make sense.

Also note that the higher or larger the RAID number, or parity scheme, or number of "m" devices in a parity and erasure code group may not be better, likewise smaller may not be better. What is better is which approach meets your specific application performance, availability, capacity, economic (PACE) needs, along with SLO, RTO, RPO requirements. What can also be good is to use hybrid approaches combining different technologies and tools to facilitate both access, availability, durability along with point in time recovery across different layers of granularity (e.g. device, drive, adapter, controller, cabinet, file system, data center, etc).

Some focus on the lower level RAID as the single or primary point of protection, however watch out for that being your single point of failure as well. For example, instead of building a resilient RAID 10 and then neglecting to have adequate higher level access, as well as recovery point protection, combine different techniques including file system protection, snapshots, and backups among others.

Figure 9.14 shows various options and considerations for balancing between too many or too few data (k) and protect (m) devices. The balance is about enabling particular FTT along with PACE attributes and SLO. This means, for some environments or applications, using different failure-tolerant modes ( FTM) in various combinations as well as configurations.

SDDC SDDI Data Protection
Figure 9.14 Comparing various data drive to protection devices

Figure 9.14 top shows no protection overhead (with no protection); the bottom shows 13 data drives and three protection drives in an EC (RS or LRC among others) configuration that could tolerate three devices failing before loss of data or access occurs. In between are various options that can also be scaled up or down across a different number of devices ( HDDs, SSD, or systems).

Some solutions allow the user or administrator to configure the I/O chunk, slabs, shard, or stripe size, for example, from 8 KB to 256 KB to 1 MB (or larger), aligning with application workload and I/O profiles. Other options include the ability to set or disable read-ahead, write-through vs. write-back cache (with battery-protected cache), among other options.

The width or number of devices in a RAID parity or erasure group is based on a combination of factor, including how much data is to be stored and what your FTT objective is, along with spreading out protection overhead. Another consideration is whether you have large or small files and objects.

For example, if you have many small files and a wide stripe, parity, or erasure code set with a large chunk or shard size, you may not have an optimal configuration from a performance perspective.

The following figure shows combing various data protection availability and accessibility technologies including local as well as remote mirroring and replication, along with parity or erasure code (including LRC, RS, SHEC among others) approaches. Instead of just using one technology, a hybrid approach is used leveraging mirror (local on SSD) and replication across sites including asynchronous and synchronous. Replication modes include Asynchronous (time-delayed, eventual consistency) for longer distance, higher latency networks, and synchronous (strong consistency, real-time) for short distance or low-latency networks.

Note that the mirror and replication can be done in software deployed as part of a storage system, appliance or as tin-wrapped software, virtual machine, virtual storage appliance, container or some other deployment mode. Likewise RAID, parity and erasure code software can be deployed and packaged in different ways.

In addition to mirror and replication, solutions are also using parity based including erasure code variations for lower cost, less active data. In other words, the mirror on SSD handles active hot data, as well as any buffering or cache, while lower performance, higher capacity, lower cost data gets de-staged or migrated to a parity erasure code tier. Some vendors, service provider and solutions leveraging variations of the approach in figure 9.15 include Microsoft ( Azure and Windows) and VMware among others.

SDDC SDDI Data Protection
Figure 9.15 Combining various availability data protection techniques

A tradecraft skill is finding the balance, knowing your applications, the data, and how the data is allocated as well as used, then leveraging that insight and your experience to configure to meet your application PACE requirements.

Consider:

  • Number of drives (width) in a group, along with protection copies or parity
  • Balance rebuild performance impact and time vs. storage space overhead savings
  • Ability to mix and match various devices in different drive groups in a system
  • Management interface, tools, wizards, GUIs, CLIs, APIs, and plug-ins
  • Different approaches for various applications and environments
  • Context of a physical RAID array, system, appliance, or solution vs. logical

Erasure Codes (EC)

Erasure Codes ( EC) combines advanced protection with variable space capacity overhead over many drives, devices, or systems using large parity chunks, shards compared to traditional parity RAID approaches. There are many variations of EC as well as parity based approaches, some are tied to Reed Solomon (RS) codes while others use different approaches.

Note that some EC are optimized for reducing the overhead and cost of storing data (e.g. less space capacity) for inactive, or primarily read data. Likewise, some EC or variations are optimized for performance of reads/writes as well as reducing overhead of rebuild, reconstructions, repairs with least impact. Which EC or parity derivative approach is best depends on what you are trying to do or impact to avoid.

Reed Solomon (RS) codes

Reed Solomon (RS) codes are advanced parity protection mathematical algorithm technique that works well on large amounts of data providing protection with lower space capacity overhead depending on how configured. Many Erasure Codes (EC) are based on derivatives of RS. Btw, did you know (or remember) that RAID 2 (rarely used with few legacy implementations) has ties to RS codes? Here are some additional links to RS including via Backblaze, CMU, and Dr Dobbs.

Local Reconstruction Codes (LRC)

Microsoft leverages LRC in Azure as well as in Windows Servers. LRC are optimized for a balance of protection, space capacity savings, normal performance as well as reducing impact on running workloads during a repair, rebuild or reconstruction. One of the tradeoffs that LRC uses is to add some amount of additional space capacity in exchange for normal and abnormal (e.g. during repair) performance improvements. Where RS, EC and other parity based derivatives typically use a (k,m) nomenclature (e.g. data, protection), LRC adds an extra variable to help with constructions (k,m,n).

Some might argue that LRC are not as space efficient as other EC, RS or parity derivative variations of which the counter argument can be that some of those approaches are not as performance effective. In other words, everything is not the same, one approach does not or should not have to be applied to all, unless of course your preferred solution approach can only do one thing.

Additional LRC related material includes:

  • (PDF by Microsoft) LRC Erasure Coding in Windows Storage Spaces
  • (Microsoft Usenix Paper) Best Paper Award Erasure Coding in Azure
  • (Via MSDN Shared) Azure Storage Erasure Coding with LRC
  • (Via Microsoft) Azure Storage with Strong Consistency
  • (Paper via Microsoft) 23rd ACM Symposium on Operating Systems Principles (SOSP)
  • (Microsoft) Erasure Coding in Azure with LRC
  • (Via Microsoft) Good collection of EC, RS, LRC and related material
  • (Via Microsoft) Storage Spaces Fault Tolerance
  • (Via Microsoft) Better Way To Store Data with EC/LRC
  • (Via Microsoft) Volume resiliency and efficiency in Storage Spaces

Shingled Erasure Code (SHEC)

Shingled Erasure Codes (SHEC) are a variation of Erasure Codes leveraging shingled overlay approach similar to what is being used in Shingled Magnetic Recording (SMR) on some HDDs. Ceph has been an early promoter of SHEC, read more here, and here.

Replication and Mirroring

Replication and Mirroring create a mirror or replica copy of data across different devices, systems, servers, clusters, sites or regions. In addition to keeping a copy, mirror and replication can occur on different time intervals such as real-time ( synchronous) and time deferred (Asynchronous). Besides time intervals, mirror and replication are implemented in different locations at various altitudes or stack layers from lower level hardware adapter or storage systems and appliances, to operating systems, hypervisors, software defined storage, volume managers, databases and applications themselves.

Covered in more detail in chapters 5 and 6, synchronous provides real-time, strong consistency, although high-latency local or remote interfaces can impact primary application performance. Note there is a common myth that high-latency networks are only long distance when in fact some local networks can also be high-latency. Asynchronous (also discussed in more depth in chapters 5 and 6) enables local and remote high-latency communications to be spanned, facilitating protection over a distance without impacting primary application performance, albeit with lower consistency, time deferred, also known as eventual consistency.

Mirroring (also known as RAID 1) and replication creates a copy (a mirror or replica) across two or more storage targets (devices, systems, file systems, cloud storage service, applications such as a database). The reason for using mirrors is to provide a faster (for normal running and during recovery) failure-tolerant mode for enabling availability, resiliency, and data protection, particularly for active data.

Figure 9.10 shows general replication scenarios. Illustrated are two basic mirror scenarios: At the top, a device, volume, file system, or object bucket is replicated to two other targets (i.e., three-way or three replicas); At the bottom, is a primary storage device using a hybrid replica and dispersal technique where multiple data chunks, shards, fragments, or extents are spread across devices in different locations.

SDDC SDDI Mirror and Replication
Figure 9.10 Various Mirror and Replication Approaches

Mirroring and replication can be done locally inside a system (server, storage system, or appliance), within a cabinet, rack, or data center, or remotely, including at cloud services. Mirroring can also be implemented inside a server in software or using RAID and HBA cards to off-load the processing.

SDDC SDDI Mirror Replication Techniques
Figure 9.11 Mirror or Replication combined with Snapshots or other PiT protection

Keep in mind that mirroring and replication by themselves are not a replacement for backups, versions, snapshots, or another recovery point, time-interval (time-gap) protection. The reason is that replication and mirroring maintain a copy of the source at one or more destination targets. What this means is that anything that changes on the primary source also gets applied to the target destination (mirror or replica). However, it also means that anything changed, deleted, corrupted, or damaged on the source is also impacted on the mirror replica (assuming the mirror or replicas were or are mounted and accessible on-line).

implementations in various locations (hardware, software, cloud) include:

  • Applications and databases such as SQL Server, Oracle among others
  • File systems, volume manager, Software-defined storage managers
  • Third-party storage software utilities and drivers
  • Operating systems and hypervisors
  • Hardware adapter and off-load devices
  • Storage systems and appliances
  • Cloud and managed services

Where To Learn More

Continue reading additional posts in this series of Data Infrastructure Data Protection fundamentals and companion to Software Defined Data Infrastructure Essentials (CRC Press 2017) book, as well as the following links covering technology, trends, tools, techniques, tradecraft and tips.

Additional learning experiences along with common questions (and answers), as well as tips can be found in Software Defined Data Infrastructure Essentials book.

Software Defined Data Infrastructure Essentials Book SDDC

What This All Means

There are various data protection technologies, tools and techniques for enabling availability of information resources including applications, data and data Infrastructure resources. Likewise there are many different aspects of RAID as well as context from legacy hardware based to cloud, virtual, container and software defined. In other words, not all RAID is in legacy storage systems, and there is a lot of FUD about RAID in general that is probably actually targeted more at specific implementations or products.

There are different approaches to meet various needs from stripe for performance with no protection by itself, to mirror and replication, as well as many parity approaches from legacy to erasure codes including Reed Solomon based as well as LRC among others. Which approach is best depends on your objects including balancing performance, availability, capacity economic (PACE) for normal running behavior as well as during faults and failure modes.

Get your copy of Software Defined Data Infrastructure Essentials here at Amazon.com, at CRC Press among other locations and learn more here. Meanwhile, continue reading with the next post in this series, Part 4 Data Protection Recovery Points (Archive, Backup, Snapshots, Versions).

Ok, nuff said, for now.

Gs

Greg Schulz – Microsoft MVP Cloud and Data Center Management, VMware vExpert 2010-2017 (vSAN and vCloud). Author of Software Defined Data Infrastructure Essentials (CRC Press), as well as Cloud and Virtual Data Storage Networking (CRC Press), The Green and Virtual Data Center (CRC Press), Resilient Storage Networks (Elsevier) and twitter @storageio. Courteous comments are welcome for consideration. First published on https://storageioblog.com any reproduction in whole, in part, with changes to content, without source attribution under title or without permission is forbidden.

All Comments, (C) and (TM) belong to their owners/posters, Other content (C) Copyright 2006-2024 Server StorageIO and UnlimitedIO. All Rights Reserved. StorageIO is a registered Trade Mark (TM) of Server StorageIO.

Data Protection Fundamentals Recovery Points (Backup, Snapshots, Versions)

Enabling Recovery Points (Backup, Snapshots, Versions)

Updated 1/7/18

Companion to Software Defined Data Infrastructure Essentials – Cloud, Converged, Virtual Fundamental Server Storage I/O Tradecraft ( CRC Press 2017)

server storage I/O data infrastructure trends

By Greg Schulzwww.storageioblog.com November 26, 2017

This is Part 4 of a multi-part series on Data Protection fundamental tools topics techniques terms technologies trends tradecraft tips as a follow-up to my Data Protection Diaries series, as well as a companion to my new book Software Defined Data Infrastructure Essentials – Cloud, Converged, Virtual Server Storage I/O Fundamental tradecraft (CRC Press 2017).

Software Defined Data Infrastructure Essentials Book SDDC

Click here to view the previous post Part 3 Data Protection Access Availability RAID Erasure Codes (EC) including LRC, and click here to view the next post Part 5 Point In Time Data Protection Granularity Points of Interest.

Post in the series includes excerpts from Software Defined Data Infrastructure (SDDI) pertaining to data protection for legacy along with software defined data centers ( SDDC), data infrastructures in general along with related topics. In addition to excerpts, the posts also contain links to articles, tips, posts, videos, webinars, events and other companion material. Note that figure numbers in this series are those from the SDDI book and not in the order that they appear in the posts.

In this post the focus is around Data Protection Recovery Points (Archive, Backup, Snapshots, Versions) from Chapter 10 .

SDDC, SDI, SDDI data infrastructure
Figure 1.5 Data Infrastructures and other IT Infrastructure Layers

Enabling RPO (Archive, Backup, CDP, PIT Copy, Snapshots, Versions)

SDDC SDDI Data Protection Points of Interests
Figure 9.5 Data Protection and Availability Points of Interest

RAID, including parity and erasure code (EC) along with mirroring and replication, provide availability and accessibility. These by themselves, however, are not a replacement for backup (or other point in time data protection) to support recovery points. For complete data protection the solution is to combine resiliency technology with point-in-time tools enabling availability and facilitate going back to a previous consistency time.

Recovery point protection is implemented within applications using checkpoint and consistency points as well as log and journal switches or flush. Other places where recovery-point protection occurs include in middleware, database, key-value stores and repositories, file systems, volume managers, and software-defined storage, in addition to hypervisors, operating systems, containers, utilities, storage systems, appliances, and service providers.

In addition to where, there are also different approaches, technologies, techniques, and tools, including archive, backup, continuous data protection, point-in-time copies, or clones such as snapshots, along with versioning.

Common recovery point Data Protection related terms, technologies, techniques, trends and topics pertaining to data protection from availability and access to durability and consistency to point in time protection and security are shown below.

Time interval protection for example with Snapshot, backup/restore, point in time copies, checkpoints, consistency point among other approaches can be scheduled or dynamic. They can also vary by how they copy data for example full copy or clone, or incremental and differential (e.g. what has changed) among other techniques to support 4 3 2 1 data protection. Other variations include how many concurrent copies, snapshots or versions can take place, along with how many stored and for how long (retention).

Additional Data Protection Terms

Copy Data Management ( CDM) as its name implies is associated managing various data copies for data protection, analytics among other activities. This includes being able to identify what copies exist (along with versions), where they are located among other insight.

Data Protection Management ( DPM) as its name implies is the management of data protection from backup/restore, to snapshots and other recovery point in time protection, to replication. This includes configuration, monitoring, reporting, analytics, insight into what is protected, how well it is protected, versions, retention, expiration, disposition, access control among other items.

Number of 9s Availability – Availability (access or durability or access and availability) can be expressed in number of nines. For example, 99.99 (four nines), indicates the level of availability (downtime does not exceed) objective. For example, 99.99% availability means that in a 24-hour day there could be about 9 seconds of downtime, or about 52 minutes and 34 seconds per year. Note that numbers can vary depending on whether you are using 30 days for a month vs. 365/12 days, or 52 weeks vs. 365/7 for weeks, along with rounding and number decimal places as shown in Table 9.1.

Uptime

24-hour Day

Week

Month

Year

99

0 h 14 m 24 s

1 h 40 m 48 s

7 h 18 m 17 s

3 d 15 h 36 m 15 s

99.9

0 h 01 m 27 s

0 h 10 m 05 s

0 h 43 m 26 s

0 d 08 h 45 m 36 s

99.99

0 h 00 m 09 s

0 h 01 m 01 s

0 h 04 m 12 s

0 d 00 h 52 m 34 s

99.999

0 h 00 m 01s

0 h 00 m 07 s

0 h 00 m 36 s

0 d 00 h 05 m 15 s

Table 9.1 Number of 9’s Availability Shown as Downtime per Time Interval

Service Level Objectives SLOs are metrics and key performance indicators (KPI) that guide meeting performance, availability, capacity, and economic targets. For example, some number of 9’s availability or durability, a specific number of transactions per second, or recovery and restart of applications. Service-level agreement (SLA) – SLA specifies various service level objectives such as PACE requirements including RTO and RPO, among others that define the expected level of service and any remediation for loss of service. SLA can also specify availability objectives as well as penalties or remuneration should SLO be missed.

Recovery Time Objective RTO is how much time is allowed before applications, data, or data infrastructure components need to be accessible, consistent, and usable. An RTO = 0 (zero) means no loss of access or service disruption, i.e., continuous availability. One example is an application end-to-end RTO of 4 hours, meaning that all components (application server, databases, file systems, settings, associated storage, networks) must be restored, rolled back, and restarted for use in 4 hours or less.

Another RTO example is component level for different data infrastructure layers as well as cumulative or end to end. In this scenario, the 4 hours includes time to recover, restart, and rebuild a server, application software, storage devices, databases, networks, and other items. In this scenario, there are not 4 hours available to restore the database, or 4 hours to restore the storage, as some time is needed for all pieces to be verified along with their dependencies.

Data Loss Access DLA occurs when data still exists, is consistent, durable, and safe, but it cannot be accessed due to network, application, or other problem. Note that the inverse is data that can be accessed, but it is damaged. Data Loss Event DLE is an incident that results in loss or damage to data. Note that some context is needed in a scenario in which data is stolen via a copy but the data still exists, vs. the actual data is taken and is now missing (no copies exist). Also note that there can be different granularity as well as scope of DLE for example all data or just some data lost (or damaged). Data Loss Prevention DLP encompasses the activities, techniques, technologies, tools, best practices, and tradecraft skills used to protect data from DLE or DLA.

Point in Time (PiT) such as PiT copy or data protection refers to a recovery or consistency point where data can be restored from or to (i.e., RPO), such as from a copy, snapshot, backup, sync, or clone. Essentially, as its name implies, it is the state of the data at that particular point in time.

Recovery Point Objective RPO is the point in time to which data needs to be recoverable (i.e., when it was last protected). Another way of looking at RPO is how much data you can afford to lose, with RPO = 0 (zero) meaning no data loss, or, for example, RPO = 5 minutes being up to 5 minutes of lost data.

SDDC SDDI RTO RPO
Figure 9.8 Recovery Points (point in time to recover from), and Recovery Time (how long recovery takes)

Frequency refers to how often and on what time interval protection is performed.

4 3 2 1 and 3 2 1 data protection rule
Figure 9.4 Data Protection 4 3 2 1 and 3 2 1 rule

In the context of the 4 3 2 1 rule, enabling RPO is associated with durability, meaning number of copies and versions. Simply having more copies is not sufficient because if they are all corrupted, damaged, infected, or contain deleted data, or data with latent nefarious bugs or root kits, then they could all be bad. The solution is to have multiple versions and copies of the versions in different locations to provided data protection to a given point in time.

Timeline and delta or recovery points are when data can be recovered from to move forward. They are consistent points in the context of what is/was protected. Figure 10.1 shows on the left vertical axis different granularity, along with protection and consistency points that occur over time (horizontal axis). For example, data “Hello” is written to storage (A) and then (B), an update is made “Oh Hello,” followed by (C) full backup, clone, and master snapshot or a gold copy is made.

SDDC SDDI Data Protection Recovery consistency points
Figure 10.1 Recovery and consistency points

Next, data is changed (D) to “Oh, Hello,” followed by, at time-1 (E), an incremental backup, copy, snapshot. At (F) a full copy, the master snapshot, is made, which now includes (H) “Hello” and “Oh, Hello.” Note that the previous full contained “Hello” and “Oh Hello,” while the new full (H) contains “Hello” and “Oh, Hello.” Next (G) data is changed to “Oh, Hello there,” then changed (I) to “Oh, Hello there I’m here.” Next (J) another incremental snapshot or copy is made, date is changed (K) to “Oh, Hello there I’m over here,” followed by another incremental (L), and other incremental (M) made a short time later.

At (N) there is a problem with the file, object, or stored item requiring a restore, rollback, or recovery from a previous point in time. Since the incremental (M) was too close to the recovery point (RP) or consistency point (CP), and perhaps damaged or its consistency questionable, it is decided to go to (O), the previous snapshot, copy, or backup. Alternatively, if needed, one can go back to (P) or (Q).

Note that simply having multiple copies and different versions is not enough for resiliency; some of those copies and versions need to be dispersed or placed in different systems or locations away from the source. How many copies, versions, systems, and locations are needed for your applications will depend on the applicable threat risks along with associated business impact.

The solution is to combine techniques for enabling copies with versions and point-in-time protection intervals. PIT intervals enable recovering or access to data back in time, which is a RPO. That RPO can be an application, transactional, system, or other consistency point, or some other time interval. Some context here is that there are gaps in protection coverage, meaning something was not protected.

A good data protection gap is a time interval enabling RPO, or simply a physical and logical break and the distance between the active or protection copy, and alternate versions and copies. For example, a gap in coverage (e.g. bad data protection gap) means something was not protected.

A protection air or distance gap is having one of those versions and copies on another system, in a different location and not directly accessible. In other words, if you delete, or data gets damaged locally, the protection copies are safe. Furthermore, if the local protection copies are also damaged, an air or distance gap means that the remote or alternate copies, which may be on-line or off-line, are also safe.

Good Data Protection Gaps
Figure 9.9 Air Gaps and Data Protection

Figure 10.2 shows on the left various data infrastructure layers moving from low altitude (lower in the stack) host servers or bare metal (BM) physical machine (PM) and up to higher levels with applications. At each layer or altitude, there are different hardware and software components to protect, with various policy attributes. These attributes, besides PACE, FTT, RTO, RPO, and SLOs, include granularity (full or incremental), consistency points, coverage, frequency (when protected), and retention.

SDDC SDDI Data Protection Granularity
Figure 10.2 Protecting data infrastructure granularity and enabling resiliency at various stack layers (or altitude)

Also shown in the top left of Figure 10.2 are protections for various data infrastructure management tools and resources, including active directory (AD), Azure AD (AAD), domain controllers (DC), group policy objects (GPO) and organizational units (OU), network DNS, routing and firewall, among others. Also included are protecting management systems such as VMware vCenter and related servers, Microsoft System Center, OpenStack, as well as data protection tools along with their associated configurations, metadata, and catalogs.

The center of Figure 10.2 lists various items that get protected along with associated technologies, techniques, and tools. On the right-hand side of Figure 10.2 is an example of how different layers get protected at various times, granularity, and what is protected.

For example, the PM or host server BIOS and UEFI as well as other related settings seldom change, so they do not have to be protected as often. Also shown on the right of Figure 10.2 are what can be a series of full and incremental backups, as well as differential or synthetic ones.

Figure 10.3 is a variation of Figure 10.2 showing on the left different frequencies and intervals, with a granularity of focus or scope of coverage on the right. The middle shows how different layers or applications and data focus have various protection intervals, type of protection (full, incremental, snap, differentials), along with retention, as well as some copies to keep.

SDDC SDDI Data Protection Granularity
Figure 10.3 Protecting different focus areas with various granularities

Protection in Figures 10.2 and 10.3 for the PM could be as simple as documentation of what settings to configure, versions, and other related information. A hypervisors may have changes, such as patches, upgrades, or new drivers, more frequently than a PM. How you go about protecting may involve reinstalling from your standard or custom distribution software, then applying patches, drivers, and settings.

You might also have a master copy of a hypervisors on a USB thumb drive or another storage device that can be cloned, customized with the server name, IP address, log location, and other information. Some backup and data protection tools also provide protection of hypervisors (or containers and cloud machine instances) in addition to the virtual machine (VM), guest operating systems, applications, and data.

The point is that as you go up the stack, higher in altitude (layers), the granularity and frequency of protection increases. What this means is that you may have more frequent smaller protection copies and consistency points higher up at the application layer, while lower down, less frequent, yet larger full image, volume, or VM protection, combining different tools, technology, and techniques.

Where To Learn More

Continue reading additional posts in this series of Data Infrastructure Data Protection fundamentals and companion to Software Defined Data Infrastructure Essentials (CRC Press 2017) book, as well as the following links covering technology, trends, tools, techniques, tradecraft and tips.

Additional learning experiences along with common questions (and answers), as well as tips can be found in Software Defined Data Infrastructure Essentials book.

Software Defined Data Infrastructure Essentials Book SDDC

What This All Means

Everything is not the same across different environments, data centers, data infrastructures, applications and their workloads (along with data, and its value). Likewise there are different approaches for enabling data protection to meet various SLO needs including RTO, RPO, RAS, FTT and PACE attributes among others. What this means is that complete data protection requires using different new (and old) tools, technologies, trends, services (e.g. cloud) in new ways. This also means leveraging existing and new techniques, learning from lessons of the past to prevent making the same errors.

RAID (mirror, replicate, parity including erasure codes) regardless of where and how implemented (hardware, software, legacy, virtual, cloud) by itself is not a replacement for backup, they need to be combined with recovery point protection of some type (backup, checkpoint, consistency point, snapshots). Also protection should occur at multiple levels of granularity (device, system, application, database, table) to meet various SLO requirements as well as different time intervals enabling 4 3 2 1 data protection.

Keep in mind what is it that you are protecting, why are you protecting it and against what, what is likely to happen, also if something happens what will its impact be, what are your SLO requirements, as well as minimize impact to normal operating, as well as during failure scenarios. For example do you need to have a full system backup to support recovery of an individual database table, or can that table be protected and recovered via checkpoints, snapshots or other fine-grained routine protection? Everything is not the same, why treat and protect everything the same way?

Get your copy of Software Defined Data Infrastructure Essentials here at Amazon.com, at CRC Press among other locations and learn more here. Meanwhile, continue reading with the next post in this series, Part 5 Point In Time Data Protection Granularity Points of Interest.

Ok, nuff said, for now.

Gs

Greg Schulz – Microsoft MVP Cloud and Data Center Management, VMware vExpert 2010-2017 (vSAN and vCloud). Author of Software Defined Data Infrastructure Essentials (CRC Press), as well as Cloud and Virtual Data Storage Networking (CRC Press), The Green and Virtual Data Center (CRC Press), Resilient Storage Networks (Elsevier) and twitter @storageio. Courteous comments are welcome for consideration. First published on https://storageioblog.com any reproduction in whole, in part, with changes to content, without source attribution under title or without permission is forbidden.

All Comments, (C) and (TM) belong to their owners/posters, Other content (C) Copyright 2006-2024 Server StorageIO and UnlimitedIO. All Rights Reserved. StorageIO is a registered Trade Mark (TM) of Server StorageIO.