Microsoft Hyper-V Is Alive Enhanced With Windows Server 2025

Yes, you read that correctly, Microsoft Hyper-V is alive and enhanced with Windows Server 2025, formerly Windows Server v.Next server. Note that  Windows Server 2025 preview build is just a preview available for download testing as of this time.

What about Myth Hyper-V is discontinued?

Despite recent FUD (fear, uncertainty, doubt), misinformation, and fake news, Microsoft Hyper-V is not dead. Nor has Hyper-V been discontinued, as some claim. Some Hyper-V FUD is tied to customers and partners of VMware following Broadcom’s acquisition of VMware looking for alternatives. More on Broadcom and VMware here, here, here, here, and here.

As a result of Broadcom’s VMware acquisition and challenges for partners and customers (see links above), organizations are doing due diligence, looking for replacement or alternatives. In addition, some vendors are leveraging the current VMware challenges to try and position themselves as the best hypervisor virtualization safe harbor for customers. Thus some vendors, their partners, influencers and amplifiers are using FUD to keep prospects from looking at or considering Hyper-V.

Virtual FUD (vFUD)

First, let’s shut down some Virtual FUD (vFUD). As mentioned above, some are claiming that Microsoft has discontinued Hyper-V. Specifically, the vFUD centers on Microsoft terminating a specific license SKU (e.g., the free Hyper-V Server 2019 SKU). For those unfamiliar with the discontinued SKU (Hyper-V Server 2019), it’s a headless (no desktop GUI) version of Windows Server  running Hyper-V VMs, nothing more, nothing less.

Does that mean the Hyper-V technology is discontinued? No.

Does that mean Windows Server and Hyper-V are discontinued? No.

Microsoft is terminating a particular stripped-down Windows Server version SKU (e.g. Hyper-V Server 2019) and not the underlying technology, including Windows Server and Hyper-V.

To repeat, a specific SKU or distribution (Hyper-V Server 2019) has been discontinued not Hyper-V. Meanwhile, other distributions of Windows Server with Hyper-V continue to be supported and enhanced, including the upcoming Windows Server 2025 and Server 2022, among others.

On the other hand, there is also some old vFUD going back many years, or a decade, when some last experienced using, trying, or looking at Hyper-V. For example, the last look at Hyper-V might been in the Server 2016 or before era.

If you are a vendor or influencer throwing vFUD around, at least get some new vFUD and use it in new ways. Better yet, up your game and marketing so you don’t rely on old vFUD. Likewise, if you are a vendor partner and have not extended your software or service support for Hyper-V, now is a good time to do so.

Watch out for falling into the vFUD trap thinking Hyper-V is dead and thus miss out on new revenue streams. At a minimum, take a look at current and upcoming enhancements for Hyper-V doing your due diligence instead of working off of old vFUD.

Where is Hyper-V being used?

From on-site (aka on-premises, on-premises, on-prem) and edge on Windows Servers standalone and clustered, to Azure Stack HCI. From Azure, and other Microsoft platforms or services to Windows Desktops, as well as home labs, among many other scenarios.

Do I use Hyper-V? Yes, when I  retired from the vExpert program after ten years. I moved all of my workloads from VMware environment to Hyper-V including *nix, containers and Windows VMs, on-site and on Azure Cloud.

How Hyper-V Is Alive Enhanced With Windows Server 2025

Is Hyper-V Alive Enhanced With Windows Server 2025?  Yup.

Formerly known as Windows Server v.Next, Microsoft announced the Windows Server 2025 preview build on January 26, 2024 (you can get the bits here). Note that Microsoft uses Windows Server v.Next as a generic placeholder for next-generation Windows Server technology.

A reminder that the cadence of Windows Server Long Term Serving Channels (LTSC) versions has been about three years (2012R2, 2016, 2019, 2022, now 2025), along with interim updates.

What’s enhanced with Hyper-V and Windows Server 2025

    • Hot patching of running server (requires Azure Arc management) with almost instant implementations and no reboot for physical, virtual, and cloud-based Windows Servers.
    • Scaling of even more compute processors and RAM for VMs.
    • Server Storage I/O performance updates, including NVMe optimizations.
    • Active Directory (AD) improvements for scaling, security, and performance.
    • There are enhancements to storage replica and clustering capabilities.
    • Hyper-V GPU partition and pools, including migration of VMs using GPUs.

More Enhancements for Hyper-V and Windows Server 2025

Active Directory (AD)

Enhanced performance using all CPUs in a process group up to 64 cores to support scaling and faster processing. LDAP for TLS 1.3, Kerberos support for AES SHA 256 / 384, new AD functional levels, local KDC, improved replication priority, NTLM retirement, local Kerberos, and other security hardening. In addition, 64-bit Long value IDs (LIDs) are supported along with a new database schema using 32K pages vs the previous 8K pages. You will need to upgrade forest-wide across domain controllers to leverage the new larger page sizes (at least Server 2016 or later). Note that there is also backward compatibility using 8K pages until all ADs are upgraded.

Storage, HA, and Clustering

Windows Server continues to offer flexible options for storage how you want or need to use it, from traditional direct attached storage (DAS) to Storage Area Networks (SAN), to Storage Spaces Direct (S2D) software-defined, including NVMe, NVMe over Fabrics (NVMeoF), SAS, Fibre Channel, iSCSI along with file attached storage. Some other storage and HA enhancements include Storage Replica performance for logging and compression and stretch S2D multi-site optimization.

Failover Cluster enhancements include AD-less clusters, cert-based VM live migration for the edge, cluster-aware updating reliability, and performance improvements. ReFS enhancements include dedupe and compression optimizations.

Other NVMe enhancements include optimization to boost performance while reducing CPU overhead, for example, going from 1.1M IOPS to 1.86M IOPS, and then with a new native NVMe driver (to be added), from 1.1M IOPs to 2.1M IOPs. These performance optimizations will be interesting to look at closer, including baseline configuration, number and type of devices used, and other considerations.

Compute, Hyper-V, and Containers

Microsoft has added and enhanced various Compute, Hyper-V, and Container functionality with Server 2025, including supporting larger configurations and more flexibility with GPUs. There are app compatibility improvements for containers that will be interesting to see and hear more details about besides just Nano (the ultra slimmed-down Windows container).

Hyper-V

Microsoft extensively uses Hyper-V technology across different platforms, including Azure, Windows Servers, and Desktops. In addition, Hyper-V is commonly found across various customer and partner deployments on Windows Servers, Desktops, Azure Stack HCI, running on other clouds, and virtualization (nested). While Microsoft effectively leverages Hyper-V and continues to enhance it, its marketing has not effectively told and amplified the business benefit and value, including where and how Hyper-V is deployed.

Hyper-V with Server 2025 includes discrete device assignment to VM (e.g., resources dedicated to VMs). However, dedicating a device like a GPU to a VM prevents resource sharing, failover cluster, or live migration. On the other hand, Server 2025 Hyper-V supports GPU-P (GPU Partitioning), enabling GPU(s) to be shared across multiple VMs. GPUs can be partitioned and assigned to VMs, with GPUs and GPU partitioning enabled across various hosts.

In addition to partitioning, GPUs can be placed into GPU pools for HA. Live migration and cluster failover (requires PCIe SR-IOV), AMD Lilan or later, Intel Sapphire Rapids, among other requirements, can be done. Another enhancement is Dynamic Processor Compatibility, which allows mixed processor generations to be used across VMs and then masks out functionalities that are not common across processors. Other enhancements include optimized UEFI, secure boot, TPM , and hot add and removal of NICs.

Networking

Network ATC provides intent-based deployments where you specify desired outcomes or states, and the configuration is optimized for what you want to do. Network HUD enables always-on monitoring and network remediation. Software Defined Network (SDN) optimization for transparent multi-site L2 and L3 connectivity and improved SDN gateway performance enhancements.

SMB over QUIC leverages TLS 1.3 security to streamline local, mobile, and remote networking while enhancing security with configuration from the server or client. In addition, there is an option to turn off SMB NTLM at the SMB level, along with controls on which versions of SMB to allow or refuse. Also being added is a brute force attack limiter that slows down SMB authentication attacks.

Management, Upgrades, General user Experience

The upgrade process moving forward with Windows Server 2025 is intended to be seamless and less disruptive. These enhancements include hot patching and flighting (e.g., LTSC Windows server upgrades similar to how you get regular updates). For hybrid management, an easier-to-use wizard to enable Azure Arc is planned. For flexibility, if present, WiFi networking and Bluetooth devices are automatically enabled with Windows Server 2025 focused on edge and remote deployment scenarios.

Also new is an optional subscription-based licensing model for Windows Server 2025 while retaining the existing perpetual use. Let me repeat that so as not to create new vFUD, you can still license Windows Server (and thus Hyper-V) using traditional perpetual models and SKUs.

Additional Resources Where to learn more

The following links are additional resources to learn about Windows Server, Server 2025, Hyper-V, and related data infrastructures and tradecraft topics.

What’s New in Windows Server v.Next video from Microsoft Ignite (11/17/23)
Microsoft Windows Server 2025 Whats New
Microsoft Windows Server 2025 Preview Build Download
Microsoft Windows Server 2025 Preview Build Download (site)
Microsoft Evaluation Center (various downloads for trial)
Microsoft Eval Center Windows Server 2022 download
Microsoft Hyper-V on Windows Information
Microsoft Hyper-V on Windows Server Information
Microsoft Hyper-V on Windows Desktop (e.g., Win10)
Microsoft Windows Server Release Information
Microsoft Hyper-V Server 2019
Microsoft Azure Virtual Machines Trial
Microsoft Azure Elastic SAN
If NVMe is the answer, what are the questions?
NVMe Primer (or refresh), The NVMe Place.

Additional learning experiences along with common questions (and answers), are found in my Software Defined Data Infrastructure Essentials book.

Software Defined Data Infrastructure Essentials Book SDDC

What this all means

Hyper-V is very much alive, and being enhanced. Hyper-V is being used from Microsoft Azure to Windows Server and other platforms at scale, and in smaller environments.

If you are looking for alternatives to VMware or simply exploring virtualization options, do your due diligence and check out Hyper-V. Hyper-V may or may not be what you want; however, is it what you need? Looking at Hyper-V now and upcoming enhancements also positions you when asked by management if you have done your due  diligence vs relying on vFUD.

Do a quick Proof of Concept, spin up a lab, and check out currently available Hyper-V. For example, on Server 2022 or 2025 preview, to get a feel for what is there to meet your needs and wants. Download the bits and get some hands on time with Hyper-V and Windows Server 2025.

Wrap up

Hyper-V is alive and enhanced with Windows Server 2025 and other releases.

Ok, nuff said, for now.

Cheers Gs

Greg Schulz – Nine time 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 UnlimitedIO LLC.

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.

Announcing My New Book Data Infrastructure Management Insight Strategies

Announcing My New Book Data Infrastructure Management Insight Strategies

Announcing My New Book Data Infrastructure Management Insight Strategies

Announcing my new book Data Infrastructure Management Insight Strategies published via Auerbach/CRC Press is now available via CRC Press and Amazon.com among other global venues.

My Fifth Solo Book Project – Data Infrastructure Management

Data Infrastructure Management Insight Strategies (e.g. the white book) is my fifth solo published book in addition to several other collaborative works. Given its title, the focus of this new book is around Data Infrastructures, the tools, technologies, techniques, trends including hardware, software, services, people, policies inside data centers that get defined to support business and application services delivery. The book (ISBN 9781138486423) is soft covered (also electronic kindle versions available) with 250 pages, over a 100 figures, tables, tips and examples. You can explore the contents via Google Books here.

Data Infrastructure Books by Greg Schulz
Stack of my solo books with common theme around Data Infrastructure topics

Data Infrastructure Management Book
Data Infrastructure Management – Insight and Strategies e.g. the White book (CRC Press 2019)

Some of My Other Books Include

Click on the following book images to learn more about, as well as order your copy.

Software Defined Data Infrastructure Essentials BookSNIA Recommended Reading List
Software Defined Data Infrastructure Essentials (SDDI) – Cloud, Converged, and Virtual Fundamental Server Storage I/O Tradecraft e.g. the Blue book covers software defined, sddc, sddi, hybrid, among other topics including serverless containers, NVMe, SSD, flash, pmem, scm as well as others. (CRC Press 2017) available at Amazon.com among other global venues.

Cloud and Virtual Data Storage Networking Intel recommended reading listIntel recommended reading list
Cloud and Virtual Data Storage Networking (CVDSN) – Your Journey to efficient and effective Information Services e.g. the Yellow or Gold Book (CRC Press 2011) available at Amazon.com among other global venues.

 

The Green and Virtual Data Center BookIntel Recommended Reading List
The Green and Virtual Data Center (TGVDC) – Enabling Efficient, Effective and Productive Data Infrastructures e.g. the Green Book (CRC Press 2009) available at Amazon.com among other venues.

Resilient Storage Networks Book
Resilient Storage Networks (RSN) – Designing Flexible scalable Data Infrastructures (Elsevier 2004) e.g. the Red Book is SNIA Education Endorsed Reading available at Amazon.com among other venues. I have some free copies of RSN for anybody who is willing to pay shipping and handling, send me a note and we will go from there.

Where to learn more

Learn more 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

Today more than ever there tends to be a focus on the date something was created or published as there is a lot of temporal content with short shelf life. This means that there is a lot of content including books being created that are short temporal usually focused on a particular technology, tool, trend that has a life span or attention focus of a couple of years at best.

On the other hand, there is also content that is still being created today that combines new and emerging technology, tools, trends with time-tested strategies, techniques as well as processes, some of whose names or buzzwords will evolve. My books fit into the latter category of combing current as well as emerging technologies, tools, trends, techniques that support longer shelf life, just insert your new favorite buzzword, buzz trend or buzz topic as needed.

Data Infrastructure Books by Greg Schulz

You will also notice looking at the stack of books, Data Infrastructure Management Insight and Strategies is a smaller soft covered book compared to others in my collection. The reason is that this new book can be a quick read to address what you need, as well as be a companion to others in the stack depending on what your focus or requirements are.

Common questions I get having written several books, not to mention the thousands of articles, tips, reports, blogs, columns, white papers, videos, webinars among other content is what’s is next? Good question, see what’s next, as well as check out some other things I’m doing over at www.picturesoverstillwater.com where I’m generating big data that gets stored and processed in various data infrastructures including cloud ;) .

Will there be another book and if so on or about what? As I mentioned, there are some projects I’m exploring, will they get finished or take different directions, wait and see what’s next.

How do I find the time to create these books and how long does it take? The time required varies as does the amount of work, what else I’m doing. I try to leverage the book (and other content creation projects) with other things I’m doing to maximize time. Some book projects have been very fast, a year or less. Some take longer such as Software Defined Data Infrastructure Essentials as it is a big book with lots of material that will have a long shelf life.

Do I write and illustrate the books or do I have somebody do them for me? For my books I do the writing and illustrating (drawings, figures, images) myself along with some of the layouts relying on external copy editors and production folks.

What do I recommend or give advice to those wanting to write a book? Understand that publishing a book is a project, there’s the actual writing, editing, reviews, art work, research, labs or other support items as book companions. Also understand why are you writing a book, for fame, fortune, acclaim, to share with others or some other reason. I also recommend before you write your entire book to talk with others who have been published to test the waters, get feedback. You might find it easier to shop an extended outline than a completed manuscript, that is unless you are writing a novel or similar.

Want to learn more about writing a book (or other content), get feedback, have other questions, drop me a note and will do what I can to help out.

Data Infrastructure Management Book

There is an old saying, publish or perish, well, I just published my fifth solo book Data Infrastructure Management Insight Strategies that you can buy at Amazon.com among other venues.

Ok, nuff said, for now.

Cheers Gs

Greg Schulz – Microsoft MVP Cloud and Data Center Management, VMware vExpert 2010-2019. 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 2006-2019 Server StorageIO and UnlimitedIO. All Rights Reserved. StorageIO is a registered Trade Mark (TM) of Server StorageIO.

Data Protection Recovery Life Post World Backup Day Pre GDPR

Data Protection Recovery Life Post World Backup Day Pre GDPR

Data Protection Recovery Life Post World Backup Day Pre GDPR trends

It’s time for Data Protection Recovery Life Post World Backup Day Pre GDPR Start Date.

The annual March 31 world backup day focus has come and gone once again.

However, that does not mean data protection including backup as well as recovery along with security gets a 364-day vacation until March 31, 2019 (or the days leading up to it).

Granted, for some environments, public relations, editors, influencers and other industry folks backup day will take some time off while others jump on the ramp up to GDPR which goes into effect May 25, 2018.

Expanding Focus Data Protection and GDPR

As I mentioned in this post here, world backup day should be expanded to include increased focus not just on backup, also recovery as well as other forms of data protection. Likewise, May 25 2018 is not the deadline or finish line or the destination for GDPR (e.g. Global Data Protection Regulations), rather, it is the starting point for an evolving journey, one that has global impact as well as applicability. Recently I participated in a fireside chat discussion with Danny Allan of Veeam who shared his GDPR expertise as well as experiences, lessons learned, tips of Veeam as they started their journey, check it out here.

Expanding Focus Data Protection Recovery and other Things that start with R

As part of expanding the focus on Data Protection Recovery Life Post World Backup Day Pre GDPR, that also means looking at, discussing things that start with R (like Recovery). Some examples besides recovery include restoration, reassess, review, rethink protection, recovery point, RPO, RTO, reconstruction, resiliency, ransomware, RAID, repair, remediation, restart, resume, rollback, and regulations among others.

Data Protection Tips, Reminders and Recommendations

  • There are no blue participation ribbons for failed recovery. However, there can be pink slips.
  • Only you can prevent on-premises or cloud data loss. However, it is also a shared responsibility with vendors and service providers
  • You can’t go forward in the future when there is a disaster or loss of data if you can’t go back in time for recovery
  • GDPR appliances to organizations around the world of all size and across all sectors including nonprofit
  • Keep new school 4 3 2 1 data protection in mind while evolving from old school 3 2 1 backup rules
  • 4 3 2 1 backup data protection rule

  • A Fundamental premise of data infrastructures is to enable applications and their data, protect, preserve, secure and serve
  • Remember to protect your applications, as well as data including metadata, settings configurations
  • Test your restores including can you use the data along with security settings
  • Don’t cause a disaster in the course of testing your data protection, backups or recovery
  • Expand (or refresh) your data protection and data infrastructure education tradecraft skills experiences

Where to learn more

Learn more about data protection, world backup day, recovery, restoration, GDPR along with related data infrastructure topics for cloud, legacy and other software defined environments 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 and wrap-up

Data protection including business continuance (BC), business resiliency (BR), disaster recovery (DR), availability, accessibility, backup, snapshots, encryption, security, privacy among others is a 7 x 24 x 365 day a year focus. The focus of data protection also needs to evolve from an after the fact cost overhead to proactive, business enabler Meanwhile, welcome to Data Protection Recovery Post World Backup Day Pre GDPR Start Date.

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.

Microsoft Windows Server 2019 Insiders Preview

Microsoft Windows Server 2019 Insiders Preview

Application Data Value Characteristics Everything Is Not The Same

Microsoft Windows Server 2019 Insiders Preview has been announced. Windows Server 2019 in the past might have been named 2016 R2 also known as a Long-Term Servicing Channel (LTSC) release. Microsoft recommends LTSC Windows Server for workloads such as Microsoft SQL Server, Share Point and SDDC. The focus of Microsoft Windows Server 2019 Insiders Preview is around hybrid cloud, security, application development as well as deployment including containers, software defined data center (SDDC) and software defined data infrastructure, as well as converged along with hyper-converged infrasture (HCI) management.

Windows Server 2019 Preview Features

Features and enhancements in the Microsoft Windows Server 2019 Insiders Preview span HCI management, security, hybrid cloud among others.

  • Hybrid cloud – Extending active directory, file server synchronize, cloud backup, applications spanning on-premises and cloud, management).
  • Security – Protect, detect and respond including shielded VMs, attested guarded fabric of host guarded machines, Windows and Linux VM (shielded), VMConnect for Windows and Linux troubleshooting of Shielded VM and encrypted networks, Windows Defender Advanced Threat Protection (ATP) among other enhancements.
  • Application platform – Developer and deployment tools for Windows Server containers and Windows Subsystem on Linux (WSL). Note that Microsoft has also been reducing the size of the Server image while extending feature functionality. The smaller images take up less storage space, plus load faster. As part of continued serverless and container support (Windows and Linux along with Docker), there are options for deployment orchestration including Kubernetes (in beta). Other enhancements include extending previous support for Windows Subsystem for Linux (WSL).

Other enhancements part of Microsoft Windows Server 2019 Insiders Preview include cluster sets in support of software defined data center (SDDC). Cluster sets expand SDDC clusters of loosely coupled grouping of multiple failover clusters including compute, storage as well as hyper-converged configurations. Virtual machines have fluidity across member clusters within a cluster set and unified storage namespace. Existing failover cluster management experiences is preserved for member clusters, along with a new cluster set instance of the aggregate resources.

Management enhancements include S2D software defined storage performance history, project Honolulu support for storage updates, along with powershell cmdlet updates, as well as system center 2019. Learn more about project Honolulu hybrid management here and here.

Microsoft and Windows LTSC and SAC

As a refresher, Microsoft Windows (along with other software) is now being released on two paths including more frequent semi-annual channel (SAC), and less frequent LTSC releases. Some other things to keep in mind that SAC are focused around server core and nano server as container image while LTSC includes server with desktop experience as well as server core. For example, Windows Server 2016 released fall of 2016 is an LTSC, while the 1709 release was a SAC which had specific enhancements for container related environments.

There was some confusion fall of 2017 when 1709 was released as it was optimized for container and serverless environments and thus lacked storage spaces direct (S2D) leading some to speculate S2D was dead. S2D among other items that were not in the 1709 SAC are very much alive and enhanced in the LTSC preview for Windows Server 2019. Learn more about Microsoft LTSC and SAC here.

Test Driving Installing The Bits

One of the enhancements with LTSC preview candidate server 2019 is improved upgrades of existing environments. Granted not everybody will choose the upgrade in place keeping existing files however some may find the capability useful. I chose to give the upgrade keeping current files in place as an option to see how it worked. To do the upgrade I used a clean and up to date Windows Server 2016 data center edition with desktop. This test system is a VMware ESXi 6.5 guest running on flash SSD storage. Before the upgrade to Windows Server 2019, I made a VMware vSphere snapshot so I could quickly and easily restore the system to a good state should something not work.

To get the bits, go to Windows Insiders Preview Downloads (you will need to register)

Windows Server 2019 LTSC build 17623 is available in 18 languages in an ISO format and require a key.

The keys for the pre-release unlimited activations are:
Datacenter Edition         6XBNX-4JQGW-QX6QG-74P76-72V67
Standard Edition             MFY9F-XBN2F-TYFMP-CCV49-RMYVH

First step is downloading the bits from the Windows insiders preview page including select language for the image to use.

Getting the windows server 2019 preview bits
Select the language for the image to download

windows server 2019 select language

Starting the download

Once you have the image download, apply it to your bare metal server or hypervisors guest. In this example, I copied the windows server 2019 image to a VMware ESXi server for a Windows Server 2016 guest machine to access via its virtual CD/DVD.

pre upgrade check windows server version
Verify the Windows Server version before upgrade

After download, access the image, in this case, I attached the image to the virtual machine CD, then accessed it and ran the setup application.

Microsoft Windows Server 2019 Insiders Preview download

Download updates now or later

license key

Entering license key for pre-release windows server 2019

Microsoft Windows Server 2019 Insiders Preview datacenter desktop version

Selecting Windows Server Datacenter with Desktop

Microsoft Windows Server 2019 Insiders Preview license

Accepting Software License for pre-release version.

Next up is determining to do a new install (keep nothing), or an in-place upgrade. I wanted to see how smooth the in-place upgrade was so selected that option.

Microsoft Windows Server 2019 Insiders Preview inplace upgrade

What to keep, nothing, or existing files and data


Confirming your selections

Microsoft Windows Server 2019 Insiders Preview install start

Ready to start the installation process

Microsoft Windows Server 2019 Insiders Preview upgrade in progress
Installation underway of Windows Server 2019 preview

Once the installation is complete, verify that Windows Server 2019 is now installed.

Microsoft Windows Server 2019 Insiders Preview upgrade completed
Completed upgrade from Windows Server 2016 to Microsoft Windows Server 2019 Insiders Preview

The above shows verifying the system build using Powershell, as well as the message in the lower right corner of the display. Granted the above does not show the new functionality, however you should get an idea of how quickly a Windows Server 2019 preview can be deployed to explore and try out the new features.

Where to learn more

Learn more Microsoft Windows Server 2019 Insiders Preview, Windows Server Storage Spaces Direct (S2D), Azure and related software defined data center (SDDC), software defined data infrastructures (SDDI) 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 and wrap-up

Microsoft Windows Server 2019 Insiders Preview gives a glimpse of some of the new features that are part of the next evolution of Windows Server as part of supporting hybrid IT environments. In addition to the new features and functionality that convey not only support for hybrid cloud, also hybrid applications development, deployment, devops and workloads, Microsoft is showing flexibility in management, ease of use, scalability, along with security as well as scale out stability. If you have not looked at Windows Server for a while, or involved with serverless, containers, Kubernetes among other initiatives, now is a good time to check out Microsoft Windows Server 2019 Insiders Preview.

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 Value Characteristics Everything Is Not The Same (Part I)

Application Data Value Characteristics Everything Is Not The Same

Application Data Value Characteristics Everything Is Not The Same

Application Data Value Characteristics Everything Is Not The Same

This is part one 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 start things off by looking at general application server storage I/O characteristics that have an impact on data value as well as access.

Application Data Value Software Defined Data Infrastructure Essentials Book SDDC

Everything is not the same across different organizations including Information Technology (IT) data centers, data infrastructures along with the applications as well as data they support. For example, there is so-called big data that can be many small files, objects, blobs or data and bit streams representing telemetry, click stream analytics, logs among other information.

Keep in mind that applications impact how data is accessed, used, processed, moved and stored. What this means is that a focus on data value, access patterns, along with other related topics need to also consider application performance, availability, capacity, economic (PACE) attributes.

If everything is not the same, why is so much data along with many applications treated the same from a PACE perspective?

Data Infrastructure resources including servers, storage, networks might be cheap or inexpensive, however, there is a cost to managing them along with data.

Managing includes data protection (backup, restore, BC, DR, HA, security) along with other activities. Likewise, there is a cost to the software along with cloud services among others. By understanding how applications use and interact with data, smarter, more informed data management decisions can be made.

IT Applications and Data Infrastructure Layers
IT Applications and Data Infrastructure Layers

Keep in mind that everything is not the same across various organizations, data centers, data infrastructures, data and the applications that use them. Also keep in mind that programs (e.g. applications) = algorithms (code) + data structures (how data defined and organized, structured or unstructured).

There are traditional applications, along with those tied to Internet of Things (IoT), Artificial Intelligence (AI) and Machine Learning (ML), Big Data and other analytics including real-time click stream, media and entertainment, security and surveillance, log and telemetry processing among many others.

What this means is that there are many different application with various character attributes along with resource (server compute, I/O network and memory, storage requirements) along with service requirements.

Common Applications Characteristics

Different applications will have various attributes, in general, as well as how they are used, for example, database transaction activity vs. reporting or analytics, logs and journals vs. redo logs, indices, tables, indices, import/export, scratch and temp space. Performance, availability, capacity, and economics (PACE) describes the applications and data characters and needs shown in the following figure.

Application and data PACE attributes
Application PACE attributes (via Software Defined Data Infrastructure Essentials)

All applications have PACE attributes, however:

  • PACE attributes vary by application and usage
  • Some applications and their data are more active than others
  • PACE characteristics may vary within different parts of an application

Think of applications along with associated data PACE as its personality or how it behaves, what it does, how it does it, and when, along with value, benefit, or cost as well as quality-of-service (QoS) attributes.

Understanding applications in different environments, including data values and associated PACE attributes, is essential for making informed server, storage, I/O decisions and data infrastructure decisions. Data infrastructures decisions range from configuration to acquisitions or upgrades, when, where, why, and how to protect, and how to optimize performance including capacity planning, reporting, and troubleshooting, not to mention addressing budget concerns.

Primary PACE attributes for active and inactive applications and data are:

P – Performance and activity (how things get used)
A – Availability and durability (resiliency and data protection)
C – Capacity and space (what things use or occupy)
E – Economics and Energy (people, budgets, and other barriers)

Some applications need more performance (server computer, or storage and network I/O), while others need space capacity (storage, memory, network, or I/O connectivity). Likewise, some applications have different availability needs (data protection, durability, security, resiliency, backup, business continuity, disaster recovery) that determine the tools, technologies, and techniques to use.

Budgets are also nearly always a concern, which for some applications means enabling more performance per cost while others are focused on maximizing space capacity and protection level per cost. PACE attributes also define or influence policies for QoS (performance, availability, capacity), as well as thresholds, limits, quotas, retention, and disposition, among others.

Performance and Activity (How Resources Get Used)

Some applications or components that comprise a larger solution will have more performance demands than others. Likewise, the performance characteristics of applications along with their associated data will also vary. Performance applies to the server, storage, and I/O networking hardware along with associated software and applications.

For servers, performance is focused on how much CPU or processor time is used, along with memory and I/O operations. I/O operations to create, read, update, or delete (CRUD) data include activity rate (frequency or data velocity) of I/O operations (IOPS). Other considerations include the volume or amount of data being moved (bandwidth, throughput, transfer), response time or latency, along with queue depths.

Activity is the amount of work to do or being done in a given amount of time (seconds, minutes, hours, days, weeks), which can be transactions, rates, IOPs. Additional performance considerations include latency, bandwidth, throughput, response time, queues, reads or writes, gets or puts, updates, lists, directories, searches, pages views, files opened, videos viewed, or downloads.
 
Server, storage, and I/O network performance include:

  • Processor CPU usage time and queues (user and system overhead)
  • Memory usage effectiveness including page and swap
  • I/O activity including between servers and storage
  • Errors, retransmission, retries, and rebuilds

the following figure shows a generic performance example of data being accessed (mixed reads, writes, random, sequential, big, small, low and high-latency) on a local and a remote basis. The example shows how for a given time interval (see lower right), applications are accessing and working with data via different data streams in the larger image left center. Also shown are queues and I/O handling along with end-to-end (E2E) response time.

fundamental server storage I/O
Server I/O performance fundamentals (via Software Defined Data Infrastructure Essentials)

Click here to view a larger version of the above figure.

Also shown on the left in the above figure is an example of E2E response time from the application through the various data infrastructure layers, as well as, lower center, the response time from the server to the memory or storage devices.

Various queues are shown in the middle of the above figure which are indicators of how much work is occurring, if the processing is keeping up with the work or causing backlogs. Context is needed for queues, as they exist in the server, I/O networking devices, and software drivers, as well as in storage among other locations.

Some basic server, storage, I/O metrics that matter include:

  • Queue depth of I/Os waiting to be processed and concurrency
  • CPU and memory usage to process I/Os
  • I/O size, or how much data can be moved in a given operation
  • I/O activity rate or IOPs = amount of data moved/I/O size per unit of time
  • Bandwidth = data moved per unit of time = I/O size × I/O rate
  • Latency usually increases with larger I/O sizes, decreases with smaller requests
  • I/O rates usually increase with smaller I/O sizes and vice versa
  • Bandwidth increases with larger I/O sizes and vice versa
  • Sequential stream access data may have better performance than some random access data
  • Not all data is conducive to being sequential stream, or random
  • Lower response time is better, higher activity rates and bandwidth are better

Queues with high latency and small I/O size or small I/O rates could indicate a performance bottleneck. Queues with low latency and high I/O rates with good bandwidth or data being moved could be a good thing. An important note is to look at several metrics, not just IOPs or activity, or bandwidth, queues, or response time. Also, keep in mind that metrics that matter for your environment may be different from those for somebody else.

Something to keep in perspective is that there can be a large amount of data with low performance, or a small amount of data with high-performance, not to mention many other variations. The important concept is that as space capacity scales, that does not mean performance also improves or vice versa, after all, everything is not the same.

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 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. However all applications have some element (high or low) of performance, availability, capacity, economic (PACE) along with various similarities. Likewise data has different value at various times. Continue reading the next post (Part II Application Data Availability Everything Is Not The Same) in this five-part mini-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 Availability 4 3 2 1 Data Protection

Application Data Availability 4 3 2 1 Data Protection

4 3 2 1 data protection Application Data Availability Everything Is Not The Same

Application Data Availability 4 3 2 1 Data Protection

This is part two 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 performance, availability, capacity, economic (PACE) attributes that have an impact on data value as well as availability.

4 3 2 1 data protection  Book SDDC

Availability (Accessibility, Durability, Consistency)

Just as there are many different aspects and focus areas for performance, there are also several facets to availability. Note that applications performance requires availability and availability relies on some level of performance.

Availability is a broad and encompassing area that includes data protection to protect, preserve, and serve (backup/restore, archive, BC, BR, DR, HA) data and applications. There are logical and physical aspects of availability including data protection as well as security including key management (manage your keys or authentication and certificates) and permissions, among other things.

Availability = accessibility (can you get to your application and data) + durability (is the data intact and consistent). This includes basic Reliability, Availability, Serviceability (RAS), as well as high availability, accessibility, and durability. “Durable” has multiple meanings, so context is important. Durable means how data infrastructure resources hold up to, survive, and tolerate wear and tear from use (i.e., endurance), for example, Flash SSD or mechanical devices such as Hard Disk Drives (HDDs). Another context for durable refers to data, meaning how many copies in various places.

Server, storage, and I/O network availability topics include:

  • Resiliency and self-healing to tolerate failure or disruption
  • Hardware, software, and services configured for resiliency
  • Accessibility to reach or be reached for handling work
  • Durability and consistency of data to be available for access
  • Protection of data, applications, and assets including security

Additional server I/O and data infrastructure along with storage topics include:

  • Backup/restore, replication, snapshots, sync, and copies
  • Basic Reliability, Availability, Serviceability, HA, fail over, BC, BR, and DR
  • Alternative paths, redundant components, and associated software
  • Applications that are fault-tolerant, resilient, and self-healing
  • Non disruptive upgrades, code (application or software) loads, and activation
  • Immediate data consistency and integrity vs. eventual consistency
  • Virus, malware, and other data corruption or loss prevention

From a data protection standpoint, the fundamental rule or guideline is 4 3 2 1, which means having at least four copies consisting of at least three versions (different points in time), at least two of which are on different systems or storage devices and at least one of those is off-site (on-line, off-line, cloud, or other). There are many variations of the 4 3 2 1 rule shown in the following figure along with approaches on how to manage technology to use. We will go into deeper this subject in later chapters. For now, remember the following.

large version application server storage I/O
4 3 2 1 data protection (via Software Defined Data Infrastructure Essentials)

4    At least four copies of data (or more), Enables durability in case a copy goes bad, deleted, corrupted, failed device, or site.
3    The number (or more) versions of the data to retain, Enables various recovery points in time to restore, resume, restart from.
2    Data located on two or more systems (devices or media/mediums), Enables protection against device, system, server, file system, or other fault/failure.

1    With at least one of those copies being off-premise and not live (isolated from active primary copy), Enables resiliency across sites, as well as space, time, distance gap for protection.

Capacity and Space (What Gets Consumed and Occupied)

In addition to being available and accessible in a timely manner (performance), data (and applications) occupy space. That space is memory in servers, as well as using available consumable processor CPU time along with I/O (performance) including over networks.

Data and applications also consume storage space where they are stored. In addition to basic data space, there is also space consumed for metadata as well as protection copies (and overhead), application settings, logs, and other items. Another aspect of capacity includes network IP ports and addresses, software licenses, server, storage, and network bandwidth or service time.

Server, storage, and I/O network capacity topics include:

  • Consumable time-expiring resources (processor time, I/O, network bandwidth)
  • Network IP and other addresses
  • Physical resources of servers, storage, and I/O networking devices
  • Software licenses based on consumption or number of users
  • Primary and protection copies of data and applications
  • Active and standby data infrastructure resources and sites
  • Data footprint reduction (DFR) tools and techniques for space optimization
  • Policies, quotas, thresholds, limits, and capacity QoS
  • Application and database optimization

DFR includes various techniques, technologies, and tools to reduce the impact or overhead of protecting, preserving, and serving more data for longer periods of time. There are many different approaches to implementing a DFR strategy, since there are various applications and data.

Common DFR techniques and technologies include archiving, backup modernization, copy data management (CDM), clean up, compress, and consolidate, data management, deletion and dedupe, storage tiering, RAID (including parity-based, erasure codes , local reconstruction codes [LRC] , and Reed-Solomon , Ceph Shingled Erasure Code (SHEC ), among others), along with protection configurations along with thin-provisioning, among others.

DFR can be implemented in various complementary locations from row-level compression in database or email to normalized databases, to file systems, operating systems, appliances, and storage systems using various techniques.

Also, keep in mind that not all data is the same; some is sparse, some is dense, some can be compressed or deduped while others cannot. Likewise, some data may not be compressible or dedupable. However, identical copies can be identified with links created to a common copy.

Economics (People, Budgets, Energy and other Constraints)

If one thing in life and technology that is constant is change, then the other constant is concern about economics or costs. There is a cost to enable and maintain a data infrastructure on premise or in the cloud, which exists to protect, preserve, and serve data and information applications.

However, there should also be a benefit to having the data infrastructure to house data and support applications that provide information to users of the services. A common economic focus is what something costs, either as up-front capital expenditure (CapEx) or as an operating expenditure (OpEx) expense, along with recurring fees.

In general, economic considerations include:

  • Budgets (CapEx and OpEx), both up front and in recurring fees
  • Whether you buy, lease, rent, subscribe, or use free and open sources
  • People time needed to integrate and support even free open-source software
  • Costs including hardware, software, services, power, cooling, facilities, tools
  • People time includes base salary, benefits, training and education

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 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. All applications have some element of performance, availability, capacity, economic (PACE) needs as well as resource demands. There is often a focus around data storage about storage efficiency and utilization which is where data footprint reduction (DFR) techniques, tools, trends and as well as technologies address capacity requirements. However with data storage there is also an expanding focus around storage effectiveness also known as productivity tied to performance, along with availability including 4 3 2 1 data protection. Continue reading the next post (Part III Application Data Characteristics Types 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 Characteristics Types Everything Is Not The Same

Application Data Characteristics Types Everything Is Not The Same

Application Data Characteristics Types Everything Is Not The Same

Application Data Characteristics Types Everything Is Not The Same

This is part three 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 different types of data. There is more to data than simply being big data, fast data, big fast or unstructured, structured or semistructured, some of which has been touched on in this series, with more to follow. Note that there is also data in terms of the programs, applications, code, rules, policies as well as configuration settings, metadata along with other items stored.

Application Data Value Software Defined Data Infrastructure Essentials Book SDDC

Various Types of Data

Data types along with characteristics include big data, little data, fast data, and old as well as new data with a different value, life-cycle, volume and velocity. There are data in files and objects that are big representing images, figures, text, binary, structured or unstructured that are software defined by the applications that create, modify and use them.

There are many different types of data and applications to meet various business, organization, or functional needs. Keep in mind that applications are based on programs which consist of algorithms and data structures that define the data, how to use it, as well as how and when to store it. Those data structures define data that will get transformed into information by programs while also being stored in memory and on data stored in various formats.

Just as various applications have different algorithms, they also have different types of data. Even though everything is not the same in all environments, or even how the same applications get used across various organizations, there are some similarities. Even though there are different types of applications and data, there are also some similarities and general characteristics. Keep in mind that information is the result of programs (applications and their algorithms) that process data into something useful or of value.

Data typically has a basic life cycle of:

  • Creation and some activity, including being protected
  • Dormant, followed by either continued activity or going inactive
  • Disposition (delete or remove)

In general, data can be

  • Temporary, ephemeral or transient
  • Dynamic or changing (“hot data”)
  • Active static on-line, near-line, or off-line (“warm-data”)
  • In-active static on-line or off-line (“cold data”)

Data is organized

  • Structured
  • Semi-structured
  • Unstructured

General data characteristics include:

  • Value = From no value to unknown to some or high value
  • Volume = Amount of data, files, objects of a given size
  • Variety = Various types of data (small, big, fast, structured, unstructured)
  • Velocity = Data streams, flows, rates, load, process, access, active or static

The following figure shows how different data has various values over time. Data that has no value today or in the future can be deleted, while data with unknown value can be retained.

Different data with various values over time

Application Data Value across sddc
Data Value Known, Unknown and No Value

General characteristics include the value of the data which in turn determines its performance, availability, capacity, and economic considerations. Also, data can be ephemeral (temporary) or kept for longer periods of time on persistent, non-volatile storage (you do not lose the data when power is turned off). Examples of temporary scratch include work and scratch areas such as where data gets imported into, or exported out of, an application or database.

Data can also be little, big, or big and fast, terms which describe in part the size as well as volume along with the speed or velocity of being created, accessed, and processed. The importance of understanding characteristics of data and how their associated applications use them is to enable effective decision-making about performance, availability, capacity, and economics of data infrastructure resources.

Data Value

There is more to data storage than how much space capacity per cost.

All data has one of three basic values:

  • No value = ephemeral/temp/scratch = Why keep it?
  • Some value = current or emerging future value, which can be low or high = Keep
  • Unknown value = protect until value is unlocked, or no remaining value

In addition to the above basic three, data with some value can also be further subdivided into little value, some value, or high value. Of course, you can keep subdividing into as many more or different categories as needed, after all, everything is not always the same across environments.

Besides data having some value, that value can also change by increasing or decreasing in value over time or even going from unknown to a known value, known to unknown, or to no value. Data with no value can be discarded, if in doubt, make and keep a copy of that data somewhere safe until its value (or lack of value) is fully known and understood.

The importance of understanding the value of data is to enable effective decision-making on where and how to protect, preserve, and cost-effectively store the data. Note that cost-effective does not necessarily mean the cheapest or lowest-cost approach, rather it means the way that aligns with the value and importance of the data at a given point in time.

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

Data has different value at various times, and that value is also evolving. 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 IV Application Data Volume Velocity Variety Everything 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 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.

VMware continues cloud construction with March announcements

VMware continues cloud construction with March announcements

VMware continues cloud construction sddc

VMware continues cloud construction with March announcements of new features and other enhancements.

VMware continues cloud construction SDDC data infrastructure strategy big picture
VMware Cloud Provides Consistent Operations and Infrastructure Via: VMware.com

With its recent announcements, VMware continues cloud construction adding new features, enhancements, partnerships along with services.

VMware continues cloud construction, like other vendors and service providers who tried and test the waters of having their own public cloud, VMware has moved beyond its vCloud Air initiative selling that to OVH. VMware which while being a public traded company (VMW) is by way of majority ownership part of the Dell Technologies family of company via the 2016 acquisition of EMC by Dell. What this means is that like Dell Technologies, VMware is focused on providing solutions and services to its cloud provider partners instead of building, deploying and running its own cloud in competition with partners.

VMware continues cloud construction SDDC data infrastructure strategy layers
VMware Cloud Data Infrastructure and SDDC layers Via: VMware.com

The VMware Cloud message and strategy is focused around providing software solutions to cloud and other data infrastructure partners (and customers) instead of competing with them (e.g. divesting of vCloud Air, partnering with AWS, IBM Softlayer). Part of the VMware cloud message and strategy is to provide consistent operations and management across clouds, containers, virtual machines (VM) as well as other software defined data center (SDDC) and software defined data infrastructures.

In other words, what this means is VMware providing consistent management to leverage common experiences of data infrastructure staff along with resources in a hybrid, cross cloud and software defined environment in support of existing as well as cloud native applications.

VMware continues cloud construction on AWS SDDC

VMware Cloud on AWS Image via: AWS.com

Note that VMware Cloud services run on top of AWS EC2 bare metal (BM) server instances, as well as on BM instances at IBM softlayer as well as OVH. Learn more about AWS EC2 BM compute instances aka Metal as a Service (MaaS) here. In addition to AWS, IBM and OVH, VMware claims over 4,000 regional cloud and managed service providers who have built their data infrastructures out using VMware based technologies.

VMware continues cloud construction updates

Building off of previous announcements, VMware continues cloud construction with enhancements to their Amazon Web Services (AWS) partnership along with services for IBM Softlayer cloud as well as OVH. As a refresher, OVH is what formerly was known as VMware vCloud air before it was sold off.

Besides expanding on existing cloud partner solution offerings, VMware also announced additional cloud, software defined data center (SDDC) and other software defined data infrastructure environment management capabilities. SDDC and Data infrastructure management tools include leveraging VMwares acquisition of Wavefront among others.

VMware Cloud Updates and New Features

  • VMware Cloud on AWS European regions (now in London, adding Frankfurt German)
  • Stretch Clusters with synchronous replication for cross geography location resiliency
  • Support for data intensive workloads including data footprint reduction (DFR) with vSAN based compression and data de duplication
  • Fujitsu services offering relationships
  • Expanded VMware Cloud Services enhancements

VMware Cloud Services enhancements include:

  • Hybrid Cloud Extension
  • Log intelligence
  • Cost insight
  • Wavefront

VMware Cloud in additional AWS Regions

As part of service expansion, VMware Cloud on AWS has been extended into European region (London) with plans to expand into Frankfurt and an Asian Pacific location. Previously VMware Cloud on AWS has been available in US West Oregon and US East Northern Virginia regions. Learn more about AWS Regions and availability zones (AZ) here.

VMware Cloud Stretch Cluster

VMware Cloud on AWS Stretch Clusters Source: VMware.com

VMware Cloud on AWS Stretch Clusters

In addition to expanding into additional regions, VMware Cloud on AWS is also being extended with stretch clusters for geography dispersed protection. Stretched clusters provide protection against an AZ failure (e.g. data center site) for mission critical applications. Build on vSphere HA and DRS  automated host failure technology, stretched clusters provide recovery point objective zero (RPO 0) for continuous protection, high availability across AZs at the data infrastructure layer.

The benefit of data infrastructure layer based HA and resiliency is not having to re architect or modify upper level, higher up layered applications or software. Synchronous replication between AZs enables RPO 0, if one AZ goes down, it is treated as a vSphere HA event with VMs restarted in another AZ.

vSAN based Data Footprint Reduction (DFR) aka Compression and De duplication

To support applications that leverage large amounts of data, aka data intensive applications in marketing speak, VMware is leveraging vSAN based data footprint reduction (DFR) techniques including compression as well as de duplication (dedupe). Leveraging DFR technologies like compression and dedupe integrated into vSAN, VMware Clouds have the ability to store more data in a given cubic density. Storing more data in a given cubic density storage efficiency (e.g. space saving utilization) as well as with performance acceleration, also facilitate storage effectiveness along with productivity.

With VMware vSAN technology as one of the core underlying technologies for enabling VMware Cloud on AWS (among other deployments), applications with large data needs can store more data at a lower cost point. Note that VMware Cloud can support 10 clusters per SDDC deployment, with each cluster having 32 nodes, with cluster wide and aware dedupe. Also note that for performance, VMware Cloud on AWS leverages NVMe attached Solid State Devices (SSD) to boost effectiveness and productivity.

VMware Hybrid Cloud Extension

Extending VMware vSphere any to any migration across clouds Source: VMware.com

VMware Hybrid Cloud Extension

VMware Hybrid Cloud Extension enables common management of common underlying data infrastructure as well as software defined environments including across public, private as well as hybrid clouds. Some of the capabilities include enabling warm VM migration across various software defined environments from local on-premises and private cloud to public clouds.

New enhancements leverages previously available technology now as a service for enterprises besides service providers to support data center to data center, or cloud centric AZ to AZ, as well as region to region migrations. Some of the use cases include small to large bulk migrations of hundreds to thousands of VM move and migrations, both scheduling as well as the actual move. Move and migrations can span hybrid deployments with mix of on-premises as well as various cloud services.

VMware Cloud Cost Insight

VMware Cost Insight enables analysis, compare cloud costs across public AWS, Azure and private VMware clouds) to avoid flying blind in and among clouds. VMware Cloud cost insight enables awareness of how resources are used, their cost and benefit to applications as well as IT budget impacts. Integrates vSAN sizer tool along with AWS metrics for improved situational awareness, cost modeling, analysis and what if comparisons.

With integration to Network insight, VMware Cloud Cost Insight also provides awareness into networking costs in support of migrations. What this means is that using VMware Cloud Cost insight you can take the guess-work out of what your expenses will be for public, private on-premisess or hybrid cloud will be having deeper insight awareness into your SDDC environment. Learn more about VVMware Cost Insight here.

VMware Log Intelligence

Log Intelligence is a new VMware cloud service that provides real-time data infrastructure insight along with application visibility from private, on-premises, to public along with hybrid clouds. As its name implies, Log Intelligence provides syslog and other log insight, analysis and intelligence with real-time visibility into VMware as well as AWS among other resources for faster troubleshooting, diagnostics, event correlation and other data infrastructure management tasks.

Log and telemetry input sources for VMware Log Intelligence include data infrastructure resources such as operating systems, servers, system statistics, security, applications among other syslog events. For those familiar with VMware Log Insight, this capability is an extension of that known experience expanding it to be a cloud based service.

VMware Wavefront SaaS analytics
Wavefront by VMware Source: VMware.com

VMware Wavefront

VMware Wavefront enables monitoring of cloud native high scale environments with custom metrics and analytics. As a reminder Wavefront was acquired by VMware to enable deep metrics and analytics for developers, DevOps, data infrastructure operations as well as SaaS application developers among others. Wavefront integrates with VMware vRealize along with enabling monitoring of AWS data infrastructure resources and services. With the ability to ingest, process, analyze various data feeds, the Wavefront engine enables the predictive understanding of mixed application, cloud native data and data infrastructure platforms including big data based.

Where to learn more

Learn more about VMware, vSphere, vRealize, VMware Cloud, AWS (and other clouds), 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

VMware continues cloud construction. For now, it appears that VMware like Dell Technologies is content on being a technology provider partner to large as well as small public, private and hybrid cloud environments instead of building their own and competing. With these series of announcements, VMware continues cloud construction enabling its partners and customers on their various software defined data center (SDDC) and related data infrastructure journeys. Overall, this is a good set of enhancements, updates, new and evolving features for their partners as well as customers who leverage VMware based technologies. Meanwhile VMware continues cloud construction.

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.

Use Intel Optane NVMe U.2 SFF 8639 SSD drive in PCIe slot

Use NVMe U.2 SFF 8639 disk drive form factor SSD in PCIe slot

server storage I/O data infrastructure trends

Need to install or use an Intel Optane NVMe 900P or other Nonvolatile Memory (NVM) Express NVMe based U.2 SFF 8639 disk drive form factor Solid State Device (SSD) into PCIe a slot?

For example, I needed to connect an Intel Optane NVMe 900P U.2 SFF 8639 drive form factor SSD into one of my servers using an available PCIe slot.

The solution I used was an carrier adapter card such as those from Ableconn (PEXU2-132 NVMe 2.5-inch U.2 [SFF-8639] via Amazon.com among other global venues.

xxxx
Top Intel 750 NVMe PCIe AiC SSD, bottom Intel Optane NVMe 900P U.2 SSD with Ableconn carrier

The above image shows top an Intel 750 NVMe PCIe Add in Card (AiC) SSD and on the bottom an Intel Optane NVMe 900P 280GB U.2 (SFF 8639) drive form factor SSD mounted on an Ableconn carrier adapter.

NVMe server storage I/O sddc

NVMe Tradecraft Refresher

NVMe is the protocol that is implemented with different topologies including local via PCIe using U.2 aka SFF-8639 (aka disk drive form factor), M.2 aka Next Generation Form Factor (NGFF) also known as "gum stick", along with PCIe Add in Card (AiC). NVMe accessed devices can be installed in laptops, ultra books, workstations, servers and storage systems using the various form factors. U.2 drives are also refereed to by some as PCIe drives in that the NVMe command set protocol is implemented using PCIe x4 physical connection to the devices. Jump ahead if you want to skip over the NVMe primer refresh material to learn more about U.2 8639 devices.

data infrastructure nvme u.2 8639 ssd
Various SSD device form factors and interfaces

In addition to form factor, NVMe devices can be direct attached and dedicated, rack and shared, as well as accessed via networks also known as fabrics such as NVMe over Fabrics.

NVMeoF FC-NVMe NVMe fabric SDDC
The many facets of NVMe as a front-end, back-end, direct attach and fabric

Context is important with NVMe in that fabric can mean NVMe over Fibre Channel (FC-NVMe) where the NVMe command set protocol is used in place of SCSI Fibre Channel Protocol (e.g. SCSI_FCP) aka FCP or what many simply know and refer to as Fibre Channel. NVMe over Fabric can also mean NVMe command set implemented over an RDMA over Converged Ethernet (RoCE) based network.

NVM and NVMe accessed flash SCM SSD storage

Another point of context is not to confuse Nonvolatile Memory (NVM) which are the storage or memory media and NVMe which is the interface for accessing storage (e.g. similar to SAS, SATA and others). As a refresher, NVM or the media are the various persistent memories (PM) including NVRAM, NAND Flash, 3D XPoint along with other storage class memories (SCM) used in SSD (in various packaging).

Learn more about 3D XPoint with the following resources:

Learn more (or refresh) your NVMe server storage I/O knowledge, experience tradecraft skill set with this post here. View this piece here looking at NVM vs. NVMe and how one is the media where data is stored, while the other is an access protocol (e.g. NVMe). Also visit www.thenvmeplace.com to view additional NVMe tips, tools, technologies, and related resources.

NVMe U.2 SFF-8639 aka 8639 SSD

On quick glance, an NVMe U.2 SFF-8639 SSD may look like a SAS small form factor (SFF) 2.5" HDD or SSD. Also, keep in mind that HDD and SSD with SAS interface have a small tab to prevent inserting them into a SATA port. As a reminder, SATA devices can plug into SAS ports, however not the other way around which is what the key tab function does (prevents accidental insertion of SAS into SATA). Looking at the left-hand side of the following image you will see an NVMe SFF 8639 aka U.2 backplane connector which looks similar to a SAS port.

Note that depending on how implemented including its internal controller, flash translation layer (FTL), firmware and other considerations, an NVMe U.2 or 8639 x4 SSD should have similar performance to a comparable NVMe x4 PCIe AiC (e.g. card) device. By comparable device, I mean the same type of NVM media (e.g. flash or 3D XPoint), FTL and controller. Likewise generally an PCIe x8 should be faster than an x4, however more PCIe lanes does not mean more performance, its what’s inside and how those lanes are actually used that matter.

NVMe U.2 8639 2.5" 1.8" SSD driveNVMe U.2 8639 2.5 1.8 SSD drive slot pin
NVMe U.2 SFF 8639 Drive (Software Defined Data Infrastructure Essentials CRC Press)

With U.2 devices the key tab that prevents SAS drives from inserting into a SATA port is where four pins that support PCIe x4 are located. What this all means is that a U.2 8639 port or socket can accept an NVMe, SAS or SATA device depending on how the port is configured. Note that the U.2 8639 port is either connected to a SAS controller for SAS and SATA devices or a PCIe port, riser or adapter.

On the left of the above figure is a view towards the backplane of a storage enclosure in a server that supports SAS, SATA, and NVMe (e.g. 8639). On the right of the above figure is the connector end of an 8639 NVM SSD showing addition pin connectors compared to a SAS or SATA device. Those extra pins give PCIe x4 connectivity to the NVMe devices. The 8639 drive connectors enable a device such as an NVM, or NAND flash SSD to share a common physical storage enclosure with SAS and SATA devices, including optional dual-pathing.

More PCIe lanes may not mean faster performance, verify if those lanes (e.g. x4 x8 x16 etc) are present just for mechanical (e.g. physical) as well as electrical (they are also usable) and actually being used. Also, note that some PCIe storage devices or adapters might be for example an x8 for supporting two channels or devices each at x4. Likewise, some devices might be x16 yet only support four x4 devices.

NVMe U.2 SFF 8639 PCIe Drive SSD FAQ

Some common questions pertaining NVMe U.2 aka SFF 8639 interface and form factor based SSD include:

Why use U.2 type devices?

Compatibility with what’s available for server storage I/O slots in a server, appliance, storage enclosure. Ability to mix and match SAS, SATA and NVMe with some caveats in the same enclosure. Support higher density storage configurations maximizing available PCIe slots and enclosure density.

Is PCIe x4 with NVMe U.2 devices fast enough?

While not as fast as a PCIe AiC that fully supports x8 or x16 or higher, an x4 U.2 NVMe accessed SSD should be plenty fast for many applications. If you need more performance, then go with a faster AiC card.

Why not go with all PCIe AiC?

If you need the speed, simplicity, have available PCIe card slots, then put as many of those in your systems or appliances as possible. Otoh, some servers or appliances are PCIe slot constrained so U.2 devices can be used to increase the number of devices attached to a PCIe backplane while also supporting SAS, SATA based SSD or HDDs.

Why not use M.2 devices?

If your system or appliances supports NVMe M.2 those are good options. Some systems even support a combination of M.2 for local boot, staging, logs, work and other storage space while PCIe AiC are for performance along with U.2 devices.

Why not use NVMeoF?

Good question, why not, that is, if your shared storage system supports NVMeoF or FC-NVMe go ahead and use that, however, you might also need some local NVMe devices. Likewise, if yours is a software-defined storage platform that needs local storage, then NVMe U.2, M.2 and AiC or custom cards are an option. On the other hand, a shared fabric NVMe based solution may support a mixed pool of SAS, SATA along with NVMe U.2, M.2, AiC or custom cards as its back-end storage resources.

When not to use U.2?

If your system, appliance or enclosure does not support U.2 and you do not have a need for it. Or, if you need more performance such as from an x8 or x16 based AiC, or you need shared storage. Granted a shared storage system may have U.2 based SSD drives as back-end storage among other options.

How does the U.2 backplane connector attach to PCIe?

Via enclosures backplane, there is either a direct hardwire connection to the PCIe backplane, or, via a connector cable to a riser card or similar mechanism.

Does NVMe replace SAS, SATA or Fibre Channel as an interface?

The NVMe command set is an alternative to the traditional SCSI command set used in SAS and Fibre Channel. That means it can replace, or co-exist depending on your needs and preferences for access various storage devices.

Who supports U.2 devices?

Dell has supported U.2 aka PCIe drives in some of their servers for many years, as has Intel and many others. Likewise, U.2 8639 SSD drives including 3D Xpoint and NAND flash-based are available from Intel among others.

Can you have AiC, U.2 and M.2 devices in the same system?

If your server or appliance or storage system support them then yes. Likewise, there are M.2 to PCIe AiC, M.2 to SATA along with other adapters available for your servers, workstations or software-defined storage system platform.

NVMe U.2 carrier to PCIe adapter

The following images show examples of mounting an Intel Optane NVMe 900P accessed U.2 8639 SSD on an Ableconn PCIe AiC carrier. Once U.2 SSD is mounted, the Ableconn adapter inserts into an available PCIe slot similar to other AiC devices. From a server or storage appliances software perspective, the Ableconn is a pass-through device so your normal device drivers are used, for example VMware vSphere ESXi 6.5 recognizes the Intel Optane device, similar with Windows and other operating systems.

intel optane 900p u.2 8639 nvme drive bottom view
Intel Optane NVMe 900P U.2 SSD and Ableconn PCIe AiC carrier

The above image shows the Ableconn adapter carrier card along with NVMe U.2 8639 pins on the Intel Optane NVMe 900P.

intel optane 900p u.2 8639 nvme drive end view
Views of Intel Optane NVMe 900P U.2 8639 and Ableconn carrier connectors

The above image shows an edge view of the NVMe U.2 SFF 8639 Intel Optane NVMe 900P SSD along with those on the Ableconn adapter carrier. The following images show an Intel Optane NVMe 900P SSD installed in a PCIe AiC slot using an Ableconn carrier, along with how VMware vSphere ESXi 6.5 sees the device using plug and play NVMe device drivers.

NVMe U.2 8639 installed in PCIe AiC Slot
Intel Optane NVMe 900P U.2 SSD installed in PCIe AiC Slot

NVMe U.2 8639 and VMware vSphere ESXi
How VMware vSphere ESXi 6.5 sees NVMe U.2 device

Intel NVMe Optane NVMe 3D XPoint based and other SSDs

Here are some Amazon.com links to various Intel Optane NVMe 3D XPoint based SSDs in different packaging form factors:

Here are some Amazon.com links to various Intel and other vendor NAND flash based NVMe accessed SSDs including U.2, M.2 and AiC form factors:

Note in addition to carriers to adapt U.2 8639 devices to PCIe AiC form factor and interfaces, there are also M.2 NGFF to PCIe AiC among others. An example is the Ableconn M.2 NGFF PCIe SSD to PCI Express 3.0 x4 Host Adapter Card.

In addition to Amazon.com, Newegg.com, Ebay and many other venues carry NVMe related technologies.
The Intel Optane NVMe 900P are newer, however the Intel 750 Series along with other Intel NAND Flash based SSDs are still good price performers and as well as provide value. I have accumulated several Intel 750 NVMe devices over past few years as they are great price performers. Check out this related post Get in the NVMe SSD game (if you are not already).

Where To Learn More

View additional NVMe, SSD, NVM, SCM, Data Infrastructure and 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

NVMe accessed storage is in your future, however there are various questions to address including exploring your options for type of devices, form factors, configurations among other topics. Some NVMe accessed storage is direct attached and dedicated in laptops, ultrabooks, workstations and servers including PCIe AiC, M.2 and U.2 SSDs, while others are shared networked aka fabric based. NVMe over fabric (e.g. NVMeoF) includes RDMA over converged Ethernet (RoCE) as well as NVMe over Fibre Channel (e.g. FC-NVMe). Networked fabric accessed NVMe access of pooled shared storage systems and appliances can also include internal NVMe attached devices (e.g. as part of back-end storage) as well as other SSDs (e.g. SAS, SATA).

General wrap-up (for now) NVMe U.2 8639 and related tips include:

  • Verify the performance of the device vs. how many PCIe lanes exist
  • Update any applicable BIOS/UEFI, device drivers and other software
  • Check the form factor and interface needed (e.g. U.2, M.2 / NGFF, AiC) for a given scenario
  • Look carefully at the NVMe devices being ordered for proper form factor and interface
  • With M.2 verify that it is an NVMe enabled device vs. SATA

Learn more about NVMe at www.thenvmeplace.com including how to use Intel Optane NVMe 900P U.2 SFF 8639 disk drive form factor SSDs in PCIe slots as well as for fabric among other scenarios.

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 Fundamental Topics Tools Techniques Technologies Tips

Data Protection Fundamental Topics Tools Techniques Technologies Tips

Update 1/16/2018

Data protection fundamental 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 I 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 Protection Fundamental Infrastructure Essentials Book SDDC

The focus of this series is around data protection fundamental topics including Data Infrastructure Services: Availability, RAS, RAID and Erasure Codes (including LRC) ( Chapter 9), Data Infrastructure Services: Availability, Recovery Point ( Chapter 10). Additional Data Protection related chapters include Storage Mediums and Component Devices ( Chapter 7), Management, Access, Tenancy, and Performance ( Chapter 8), as well as Capacity, Data Footprint Reduction ( Chapter 11), Storage Systems and Solutions Products and Cloud ( Chapter 12), Data Infrastructure and Software-Defined Management ( Chapter 13) among others.

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.

Posts in this data protection fundamental series include:

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

Data Infrastructures

Data Infrastructures exists to support business, cloud and information technology (IT) among other applications that transform data into information or services. The fundamental role of data infrastructures is to provide a platform environment for applications and data that is resilient, flexible, scalable, agile, efficient as well as cost-effective.

Put another way, data infrastructures exist to protect, preserve, process, move, secure and serve data as well as their applications for information services delivery. Technologies that make up data infrastructures include hardware, software, or managed services, servers, storage, I/O and networking along with people, processes, policies along with various tools spanning legacy, software-defined virtual, containers and cloud. Read more about data infrastructures (its what’s inside data centers) here.

Why SDDC SDDI Need Data Protection
Various Needs Demand Drivers For Data Protection Fundamentals

Why The Need For Data Protection

Data Protection encompasses many different things, from accessibility, durability, resiliency, reliability, and serviceability ( RAS) to security and data protection along with consistency. Availability includes basic, high availability ( HA), business continuance ( BC), business resiliency ( BR), disaster recovery ( DR), archiving, backup, logical and physical security, fault tolerance, isolation and containment spanning systems, applications, data, metadata, settings, and configurations.

From a data infrastructure perspective, availability of data services spans from local to remote, physical to logical and software-defined, virtual, container, and cloud, as well as mobile devices. Figure 9.2 shows various data infrastructure availability, accessibility, protection, and security points of interest. On the left side of Figure 9.2 are various data protection and security threat risks and scenarios that can impact availability, or result in a data loss event ( DLE), data loss access ( DLA), or disaster. The right side of Figure 9.2 shows various techniques, tools, technologies, and best practices to protect data infrastructures, applications, and data from threat risks.

SDDI SDDC Data Protection Fundamental Big Picture
Figure 9.2 Various threat vectors, issues, problems, and challenges that drive the need for data protection

A fundamental role of data infrastructures (and data centers) is to protect, preserve, secure and serve information when needed with consistency. This also means that the data infrastructure resources (servers, storage, I/O networks, hardware, software, external services) and the applications (and data) they combine and are defined to protect are also accessible, durable and secure.

Data Protection topics include:

  • Maintaining availability, accessibility to information services, applications and data
  • Data include software, actual data, metadata, settings, certificates and telemetry
  • Ensuring data is durable, consistent, secure and recoverable to past points in time
  • Everything is not the same across different environments, applications and data
  • Aligning techniques and technologies to meet various service level objectives ( SLO)

Data Protection Fundamental Tradecraft Skills Experience Knowledge

Tools, technologies, trends are part of Data Protection, so to are the techniques of knowing (e.g. tradecraft) what to use when, where, why and how to protect against various threats risks (challenges, issues, problems).

Part of what is covered in this series of posts as well as in the Software Defined Data Infrastructure (SDDI) Essentials book is tradecraft skills, tips, experiences, insight into what to use, as well as how to use old and new things in new ways.

This means looking outside the technology box towards what is that you need to protect and why, then knowing how to use different skills, experiences, techniques part of your tradecraft combined with data protection toolbox tools. Read more about tradecraft here.

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 environments, data centers, data infrastructures and applications.

Likewise everything is and does not have to be the same when it comes to Data Protection. Data protection fundamentals encompasses many different hardware, software, services including cloud technologies, tools, techniques, best practices, policies and tradecraft experience skills (e.g. knowing what to use when, where, why and how).

Since everything is not the same, various data protection approaches are needed to address various application performance availability capacity economic ( PACE) needs, as well as SLO and SLAs.

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 2 Reliability, Availability, Serviceability ( RAS) Data Protection Fundamentals.

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 Reliability, Availability, Serviceability RAS Fundamentals

Reliability, Availability, Serviceability RAS Fundamentals

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 2 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 1 Data Infrastructure Data Protection Fundamentals, and click here to view the next post Part 3 Data Protection Access Availability RAID Erasure Codes (EC) including LRC.

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 availability from Chapter 9 which includes access, durability, RAS, RAID and Erasure Codes (including LRC), mirroring and replication along with related topics.

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

Reliability, Availability, Serviceability (RAS) Data Protection Fundamentals

Reliability, Availability Serviceability (RAS) and other access availability along with Data Protection topics are covered in chapter 9. A resilient data infrastructure (software-defined, SDDC and legacy) protects, preserves, secures and serves information involving various layers of technology. These technologies enable various layers ( altitudes) of functionality, from devices up to and through the various applications themselves.

SDDI SDDC Data Protection Big Picture
Figure 9.2 Various threat issues and challenges that drive the need for data protection

Some applications need a faster rebuild, while others need sustained performance (bandwidth, latency, IOPs, or transactions) with the slower rebuild; some need lower cost at the expense of performance; others are ok with more space if other objectives are meet. The result is that since everything is different yet there are similarities, there is also the need to tune how data Infrastructure protects, preserves, secures, and serves applications and data.

General reliability, availability, serviceability, and data protection functionality includes:

  • Manually or automatically via policies, start, stop, pause, resume protection
  • Adjust priorities of protection tasks, including speed, for faster or slower protection
  • Fast-reacting to changes, disruptions or failures, or slower cautious approaches
  • Workload and application load balancing (performance, availability, and capacity)

RAS can be optimized for:

  • Reduced redundancy for lower overall costs vs. resiliency
  • Basic or standard availability (leverage component plus)
  • High availability (use better components, multiple systems, multiple sites)
  • Fault-tolerant with no single points of failure (SPOF)
  • Faster restart, restore, rebuild, or repair with higher overhead costs
  • Lower overhead costs (space and performance) with lower resiliency
  • Lower impact to applications during rebuild vs. faster repair
  • Maintenance and planned outages or for continues operations

Common availability 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.

Data Protection Gaps and Air Gap

There are Good Data Protection Gaps that provide recovery points to a past time enabling recoverability in the future to move forward. Another good data protection gap is an Air Gap that isolates protection copies off-site or off-line so that they can not be tampered with enabling recovery from ransomware and other software defined threats. There are Bad data protection gaps including gaps in coverage where data is not protected or items are missing. Then there are Ugly data protecting gaps which include Bad gaps that result in what you think is protected are not and finding that your copies are bad when it is too late.

Data Protection Gaps Good Bad Ugly
Data Protection Gaps Good Bad and Ugly

The following figure shows good data protection gaps including recovery points (point in time protection) along with air gaps.

Good Data Protection Gaps
Figure 9.9 Air Gaps and Data Protection

Fault / Failures To Tolerate (FTT)

FTT is how many faults or failures to tolerate for a given solution or service which in turn determines what mode of protection, or fault tolerant mode ( FTM) to use.

Fault Tolerant Mode (FTM)

FTM is the mode or technique used to enable resiliency and protect against some number of faults.

Fault / Failure Domains

Fault or Failure domains are places and things that can fail from regions, data centers or availability zones, clusters, stamps, pods, servers, networks, storage, hardware (systems, components including SSD and HDDs, power supplies, adapters). Other fault domain topics and focus areas include facility power, cooling, software including applications, databases, operating systems and hypervisors among others.

SDDI SDDC Fault Domains Zones Regions
Figure 9.5 Various Fault and Failure Domains, Regions, Locations

Clustering

Clustering is a technique and technology for enabling resiliency, as well as scaling performance, availability, and capacity. Clusters can be local, remote, or wide-area to support different data infrastructure objectives, combined with replication and other techniques.

SDDI SDDC Clustering
Figure 9.12 Clustering and Replication Examples

Another characteristic of clustering and resiliency techniques is the ability to detect and react quickly to failures to isolate and contain faults, as well as invoking automatic repair if needed. Different clustering technologies enable various approaches, from proprietary hardware and software tightly coupled to loosely coupled general-purpose hardware or software.

Clustering characteristics include:

  • Application, database, file system, operating system (Windows Storage Replica)
  • Storage systems, appliances, adapters and network devices
  • Hypervisors ( Hyper-V, VMware vSphere ESXi and vSAN among others)
  • Share everything, share some things, share nothing
  • Tightly or loosely coupled with common or individual system metadata
  • Local in a data center, campus, metro, or stretch cluster
  • Wide-area in different regions and availability zones
  • Active/active for fast fail over or restart, active/passive (standby) mode

Additional clustering considerations include:

  • How does performance scale as nodes are added, or what overhead exists?
  • How is cluster resource locking in shared environments handled?
  • How many (or few) nodes are needed for quorum to exist?
  • Network and I/O interface (and management) requirements
  • Cluster partition or split-brain (i.e., cluster splits into two)?
  • Fast-reacting fail over and resiliency vs. overhead of failing back
  • Locality of where applications are located vs. storage access and clustering

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 and applications. There are various performance, availability, capacity economic (PACE) considerations along with service level objectives (SLO). Availability means being able to access information resources (applications, data and underlying data infrastructure resources), as well as data being consistent along with durable. Being durable means enabling data to be accessible in the event of a device, component or other fault domain item failures (hardware, software, data center).

Just as everything is not the same across different environments, there are various techniques, technologies and tools that can be used in different ways to enable availability and accessibility. These include high availability (HA), RAS, mirroring, replication, parity along with derivative erasure code (EC), LRC, RS and other RAID implementations, along with clustering. Also keep in mind that pertaining to data protection, there are good gaps (e.g. time intervals for recovery points, air gaps), bad gaps (missed coverage or lack of protection), and ugly gaps (not being able to recover from a gap in time).

Note that mirroring, replication, EC, LRC, RS or other Parity and RAID approaches are not replacements for backup, rather they are companions to time interval based recovery point protection such as snapshots, backup, checkpoints, consistency points and versioning among others (discussed in follow-up posts in this series).

Which data protection tool, technology to trend is the best depends on what you are trying to accomplish and your application workload PACE requirements along with SLOs. 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 3 Data Protection Access Availability RAID Erasure Codes (EC) including LRC.

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.