Tag: data infrastructure

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March 2018 Server StorageIO Data Infrastructure Update Newsletter

March 2018 Server StorageIO Data Infrastructure Update Newsletter

Server and StorageIO Update Newsletter

Volume 18, Issue 3 (March 2018)

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

If you are wondering where the January and February 2018 update newsletters are, they are rolled into this combined edition. In addition to the short email version (free signup here), you can access full versions (html here and PDF here) along with previous editions here.

In this issue:

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

Cheers GS

Data Infrastructure and IT Industry Activity Trends

Data Infrastructure Data Protection and Backup BC BR DR HA Security

World Backup day is coming up on March 31 which is a good time to remember to verify and validate that your data protection is working as intended. On one hand I think it is a good idea to call out the importance of making sure your data is protected including backed up.

On the other hand data protection is not a once a year, rather a year around, 7 x 24 x 365 day focus. Also the focus needs to be on more than just backup, rather, all aspects of data protection from archiving to business continuance (BC), business resiliency (BR), disaster recovery (DR), always on, always accessible, along with security and recovery.

Data Infrastructure Data Protection Backup 4 3 2 1 rule
Data Infrastructure 4 3 2 1 Data Protection and Backup

Some data spring thoughts, perspectives and reminders. Data lakes may swell beyond their banks causing rivers of data to flood as they flow into larger reservoirs, great data lakes, gulfs of data, seas and oceans of data. Granted, some of that data will be inactive cold parked like glaciers while others semi-active floating around like icebergs. Hopefully your data is stored on durable storage solutions or services and does not melt.

Data Infrastructure Server Storage I/O flash SSD NVMe
Various NAND Flash SSD devices and SAS, SATA, NVMe, M.2 interfaces

Non-Volatile Memory (NVM) including various solid state device (SSD) mediums (e.g. nand flash, 3D XPoint, MRAM among others), packaging (drives, PCIe Add in cars [AiC] along with entire systems, appliances or arrays). Also part of the continue evolution of NVM, SSD and other persistent memories (PM) including storage class memories (SCM) are different access protocol interfaces.

Keep in mind that there is a difference between NVM (medium) and NVMe (access), NVM is the generic category of mediums or media and devices such as nand flash, nvram, 3D XPoint among others SCM (and PMs). In other words, NVM is what data devices use for storing data, NVMe is how devices and systems are accessed. NVMe and its variations is how NVM, SSD, PM, SCM media and devices get accessed locally, as well as over network fabrics (e.g. NVMe-oF an FC-NVMe).

NVMe continues to evolve including with networked fabric variations such as RDMA based NVMe over Fabric (NVMe-oF), along with Fibre Channel based (FC-NVMe). The Fibre Channel Industry Association trade group recently held its second multi-vendor plugfest in support of NVMe over Fibre Channel.

Read more about NVM, NVMe, SSD, SCM, flash and related technologies, tools, trends, tips via the following resources:

Has Object Storage failed to live up to its industry hype lacking traction? Or, is object storage (also known as blobs) progressing with customer adoption and deployment on normal realistic timelines? Recently I have seen some industry comments about object storage not catching on with customers or failing to live up to its hyped expectation. IMHO object storage is very much alive along with block, file, table (e.g. database SQL and NoSQL repositories), message/queue among others, as well as emerging blockchain aka data exchanges.

Various Industry and Customer Adoption Deployment timeline
Various Industry and Customer Adoption Deployment Timeline (Via: StorageIOblog.com)

An issue with object storage is that it is still new, still evolving, many IT environments applications do not yet speak or access objects and blobs natively. Likewise as is often the case, industry adoption and deployment is usually early and short term around the hype, vs. the longer cycle of customer adoption and deployment. The downside for those who only focus on object storage (or blobs) is that they may be under pressure to do things short term instead of adjusting to customer cycles which take longer, however real adoption and deployment also last longer.

While the hype and industry buzz around object storage (and blobs) may have faded, customer adoption continues and is here to stay, along with block, file among others, learn more at www.objectstoragecenter.com. Also keep in mind that there is a difference between industry and customer adoption along with deployment.

Some recent Industry Activities, Trends, News and Announcements include:

In case you missed it, Amazon Web Services (e.g. AWS) announced EKS (Elastic Kubernetes Service) which as its name implies, is an easy to use and manage Kubernetes (containers, serverless data infrastructure) running on AWS. AWS joins others including Microsoft Azure Kubernetes Services (AKS), Googles Kubernetes Engine, EasyStack (ESContainer for openstack and Kubernetes),VMware Pivotal Container Service (PKS) among others. What this means is that in the container serverless data infrastructure ecosystem Kubernetes container management (orchestration platform) is gaining in both industry as well as customer adoption along with deployment.

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

Data Infrastructure Server StorageIO Comments Content

Server StorageIO Commentary in the news, tips and articles

Recent Server StorageIO industry trends perspectives commentary in the news.

Via BizTech: Why Hybrid (SSD and HDD) Storage Might Be Fit for SMB environments
Via Excelero: Server StorageIO white paper enabling database DBaaS productivity
Via Cloudian: YouTube video interview file services on object storage with HyperFile
Via CDW Solutions: Comments on Software Defined Access
Via SearchStorage: Comments on Cloudian HyperStore on demand cloud like pricing
Via EnterpriseStorageForum: Comments and tips on Software Defined Storage Best Practices
Via PRNewsWire: Comments on Excelero NVMe NVMesh Database and DBaaS solutions
Via SearchStorage: Comments on NooBaa multi-cloud storage management
Via CDW: Comments on New IT Strategies Improve Your Bottom Line 
Via EnterpriseStorageForum: Comments on Software Defined Storage: Pros and Cons
Via DataCenterKnowledge: Comments on The Great Data Center Headache IoT
Via SearchStorage: Comments on Dell and VMware merger scenario options
Via PRNewswire: Comments on Chelsio Microsoft Validation of iWARP/RDMA
Via SearchStorage: Comments on Server Storage Industry trends and Dell EMC
Via ChannelProSMB: Comments on Hybrid HDD and SSD storage solutions
Via ChannelProNetwork: Comments on What the Future Holds for HDDs
Via HealthcareITnews: Comments on MOUNTAINS OF MOBILE DATA
Via SearchStorage: Comments on Cloudian HyperStore 7 targets multi-cloud complexities
Via GlobeNewsWire: Comments on Cloudian HyperStore 7
Via GizModo: Comments on Intel Optane 800P NVMe M.2 SSD
Via DataCenterKnowledge: Comments on getting data centers ready for IoT
Via DataCenterKnowledge: Comments on Beyond the Hype: AI in the Data Center
Via DataCenterKnowledge: Comments on Data Center and Cloud Disaster Recovery
Via SearchStoragae: Comments on Cloudian HyperFile marries NAS and object storage
Via SearchStoragae: Comments on Top 10 Tips on Solid State Storage Adoption Strategy
Via SearchStoragae: Comments on 8 Top Tips for Beating the Big Data Deluge

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

Data Infrastructure Server StorageIOblog posts

Server StorageIOblog Data Infrastructure Posts

Recent and popular Server StorageIOblog posts include:

Application Data Value Characteristics Everything Is Not The Same
Application Data Availability 4 3 2 1 Data Protection
AWS Cloud Application Data Protection Webinar
Microsoft Windows Server 2019 Insiders Preview
Application Data Characteristics Types Everything Is Not The Same
Application Data Volume Velocity Variety Everything Is Not The Same
Application Data Access Lifecycle Patterns Everything Is Not The Same
Veeam GDPR preparedness experiences Webinar walking the talk
VMware continues cloud construction with March announcements
Benefits of Moving Hyper-V Disaster Recovery to the Cloud Webinar
World Backup Day 2018 Data Protection Readiness Reminder
Use Intel Optane NVMe U.2 SFF 8639 SSD drive in PCIe slot
Data Infrastructure Resource Links cloud data protection tradecraft trends
How to Achieve Flexible Data Protection Availability with All Flash Storage Solutions
November 2017 Server StorageIO Data Infrastructure Update Newsletter
IT transformation Serverless Life Beyond DevOps Podcast
Data Protection Diaries Fundamental Topics Tools Techniques Technologies Tips
HPE Announces AMD Powered Gen 10 ProLiant DL385 For Software Defined Workloads
AWS Announces New S3 Cloud Storage Security Encryption Features
Introducing Windows Subsystem for Linux WSL Overview #blogtober
Hot Popular New Trending Data Infrastructure Vendors To Watch

View other recent as well as past StorageIOblog posts here

Server StorageIO Recommended Reading (Watching and Listening) List

Software-Defined Data Infrastructure Essentials SDDI SDDC

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

In case you may have missed it, here is a good presentation from AWS re:invent 2017 by Brendan Gregg (@brendangregg) about how Netflix does EC2 and other AWS tuning along with plenty of great resource links. Keith Tenzer (@keithtenzer) provides a good perspective piece about containers in a large IT enterprise environment here including various options.

Speaking of IT data centers and data infrastructure environments, checkout the list of some of the worlds most extreme habitats for technology here. Mark Betz (@markbetz) has a series of Docker and Kubernetes networking fundamentals posts on his site here, as well as over at Medium including mention of Google Cloud (@googlecloud). The posts in Marks series are good refresher or intros to how Docker and Kubernetes handles basic networking between containers, pods, nodes, hosts in clusters. Check out part I here and part II here.

Blockchain elements
Image via https://stevetodd.typepad.com

Steve Todd (@Stevetodd) has some good perspectives about Trusted Data Exchanges e.g. life beyond blockchain and bitcoin here along with core element considerations (beyond the product pitch) here, along with associated data infrastructure and storage evolution vs. revolution here.

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

Data Infrastructure Server StorageIO event activities

Events and Activities

Recent and upcoming event activities.

March 27, 2018 – Webinar – Veeams Road to GDPR Compliancy The 5 Lessons Learned

Feb 28, 2018 – Webinar – Benefits of Moving Hyper-V Disaster Recovery to the Cloud

Jan 30, 2018 – Webinar – Achieve Flexible Data Protection and Availability with All Flash Storage

Nov. 9, 2017 – Webinar – All You Need To Know about ROBO Data Protection Backup

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

Data Infrastructure Server StorageIO Industry Resources and Links

Various useful links and resources:

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

Connect and Converse With Us

Storage IO RSS storageio linkedin storageio facebook    Google+   storageio youtube  storageio instagram

Subscribe to Newsletter – Newsletter Archives – StorageIO.com – StorageIOblog.com

What this all means and wrap-up

Data Infrastructures are what exists inside physical data centers spanning cloud, converged, hyper-converged, virtual, serverless and other software defined as well as legacy environments. The fundamental role of data infrastructures comprising server (compute), storage, I/O networking hardware, software, services defined by management tools, best practices and policies is to provide a platform for applications along with their data to deliver information services. With March 31 being world backup day, also focus on making sure that on April 1st you are not a fool trying to recover from a bad data protection copy. With the continued movement to flash SSD along with other forms of storage class memory (SCM) and persistent memories (PM), data moves at a faster rate meaning data protection is even more important to get you out of trouble as fast as you get into issues.

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.

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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.

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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.

Posted on

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.

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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 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.

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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.

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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.

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World Backup Day 2018 Data Protection Readiness Reminder

World Backup Day 2018 Data Protection Readiness Reminder

server storage I/O trends

It’s that time of year again, World Backup Day 2018 Data Protection Readiness Reminder.

In case you have forgotten, or were not aware, this coming Saturday March 31 is World Backup (and recovery day). The annual day is a to remember to make sure you are protecting your applications, data, information, configuration settings as well as data infrastructures. While the emphasis is on Backup, that also means recovery as well as testing to make sure everything is working properly.

data infrastructure data protection

Its time that the focus of world backup day should expand from just a focus on backup to also broader data protection and things that start with R. Some data protection (and backup) related things, tools, tradecraft techniques, technologies and trends that start with R include readiness, recovery, reconstruct, restore, restart, resume, replication, rollback, roll forward, RAID and erasure codes, resiliency, recovery time objective (RTO), recovery point objective (RPO), replication among others.

data protection threats ransomware software defined

Keep in mind that Data Protection is a broader focus than just backup and recovery. Data protection includes disaster recovery DR, business continuance BC, business resiliency BR, security (logical and physical), standard and high availability HA, as well as durability, archiving, data footprint reduction, copy data management CDM along with various technologies, tradecraft techniques, tools.

data protection 4 3 2 1 rule and 3 2 1 rule

Quick Data Protection, Backup and Recovery Checklist

  • Keep the 4 3 2 1 or shorter older 3 2 1 data protection rules in mind
  • Do you know what data, applications, configuration settings, meta data, keys, certificates are being protected?
  • Do you know how many versions, copies, where stored and what is on or off-site, on or off-line?
  • Implement data protection at different intervals and coverage of various layers (application, transaction, database, file system, operating system, hypervisors, device or volume among others)

    • data infrastructure backup data protection

  • Have you protected your data protection environment including software, configuration, catalogs, indexes, databases along with management tools?
  • Verify that data protection point in time copies (backups, snapshots, consistency points, checkpoints, version, replicas) are working as intended
  • Make sure that not only are the point in time protection copies running when scheduled, also that they are protected what’s intended

    • data infrastructure backup data protection

  • Test to see if the protection copies can actually be used, this means restoring as well as accessing the data via applications
  • Watch out to prevent a disaster in the course of testing, plan, prepare, practice, learn, refine, improve
  • In addition to verifying your data protection (backup, bc, dr) for work, also take time to see how your home or personal data is protected
  • View additional tips, techniques, checklist items in this Data Protection fundamentals series of posts here.

storageio data protection toolbox

Where To Learn More

View additional Data Infrastructure Data Protection and related tools, trends, technology and tradecraft skills 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

You can not go forward if you can not go back to a particular point in time (e.g. recovery point objective or RPO). Likewise, if you can not go back to a given RPO, how can you go forward with your business as well as meet your recovery time objective (RTO)?

data protection restore rto rpo

Backup is as important as restore, without a good backup or data protection point in time copy, how can you restore? Some will say backup is more important than recovery, however its the enablement that matters, in other words being able to provide data protection and recover, restart, resume or other things that start with R. World backup day should be a reminder to think about broader data protection which also means recovery, restore and realizing if your copies and versions are good. Keep the above in mind and this is your World Backup Day 2018 Data Protection Readiness Reminder.

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.

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Data Infrastructure Resource Links Server Storage I/O Network

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

By Greg Schulz – www.storageioblog.com April 28, 2018

Various data infrastructure resource links.

SDDC Data Infrastructure

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

Where to learn more

Vmware Vsphere Vsan Vcenter Version 6 7 Summary

Vmware Vsphere Vsan Vcenter V6 7 Sddc Details

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New Cloud Act Data Regulation

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Cloud Conversations Aws Ebs Glacier And S3 Overview Part Ii S3

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Epa Energy Star Data Center Storage Draft Specification Review

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Nvme Overview And Primer Part I

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Part Ii Nvme Overview And Primer Different Configurations

Part Iii Nvme Overview And Primer Need For Performance Speed

Part Iv Nvme Overview And Primer Where And How To Use Nvme

Part V Nvme Overview And Primer Where To Learn More What This All Means

Server Storage Io Benchmark Workload Scripts Part

Part Ii Server Storage Io Benchmark Workload Scripts Results

Politics And Storage Or Storage In An Election Year V2008

Sherwood Becomes Atrato

Updated Look And Feel

Chargeback For Storage

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Im Leaving On A Jet Plane

Links To Upcoming And Recent Webcasts And Videocasts

Off To Snw In Dallas For The Day

Poll Whats Your Take On Windows 7

Update Energystar For Server Workshop

Emc And Cisco Acadia Vce What Does It Mean

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Snw Spring 2008 Audio And Podcasts

Presentation Downloads From Storage Decisions New York 2008

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Back From Fall 2008 Snw In Dallas

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Atrato Part Deux

Updated Look And Feel Part Deux

Summer Dog Days

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Director Dinner Discussions Of The San Kind

Hello From Emc World Bloggers Lounge

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Storage Magazine In A Virtual World

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It Optimization Efficiency Convergence And Cloud Conversations From Snw

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Out And About Update

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Declared Dead Fibre Channel Continues Evolve Fcbb6

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Introducing Josh Apter And The Padcaster From Nab 2013

Amazon Cloud Storage Options Enhanced With Glacier

Software Defined Virtual Hard Disk Vhd

Ibm Vs Oracle Nad Intervenes Again

Vmware Announces Vsphere V6 Virtualization Technologies

Server And Storage Io Benchmarking 101 For Smarties

Cloud Conversations Focused Cost Missing Cloud Opportunities

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Commentary On Clouds Storage Networking Green It And Other Topics

Future Ethernet 2016 Roadmap Released Ethernet Alliance

Brocade To Buy Foundry Networks Prelude To Upcoming Converged Ethernet Battle

Podcast Vbrownbags Vforums And Vmware Vtraining With Alastair Cooke

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Just When You Thought It Was Safe To Go In The Water Again

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Lenovo Thinkserver Td340 Storageio Lab Review

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My Server And Storage Io Holiday Break Projects

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Comptia Input Storage Certification

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Part Ii Revisting Aws S3 Storage Gateway Test Drive Deployment

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Researchers And Marketers Dont Agree On Future Of Nand Flash Ssd

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Server Storage Io Network Benchmark Winter Olympic Games

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Hitting The Road Again

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Trains Going Green Ah Well Maybe Blue

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

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

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Dell Updates Storage Center Operating System 7 Scos 7

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Cloud And Virtual Data Storage Networking Book Released

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Server Storageio November 2015 Update Newsletter

Dell Emc Azure Stack Hybrid Cloud Solution

Msp Business Journal Names Greg Schulz An Eco Tech Warrior

Continuing Education And Refresher Time Raid And Luns

Many Different Implementations Of Raid

Wide World Of Archiving Life Beyond Compliance

Comfort Zones Stating What Might Be Obvious To Some

The Differences Between Singapore And Houston In May

Do Disk Based Vtls Draw Less Power Than Tape

More On Fibre Channel Over Ethernet Fcoe

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Thank You Gartner For Generating Awareness For My New Book

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Das Sas Fcoe Green Efficient Storage And Io Podcast Faqs

Cmg Enabling The Green And Virtual Data Center

It Belt Tightening And Stratigies For It Economic Sustainment

Vendors Who Dont Want To Be Virtualized

Did Someone Forget To Tell Dell That Tape Is Dead

Ssd Activity Continues To Go Virtually Round And Round

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

Industry Trend And Perspective Seagate Changes Disk Drive Warranties

Just For Fun Of Flying

Raid Data Protection Remains Relevant

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Is There Still Innovation For It And Storage

Io Virtualization Iov Revisited

Shifting Industry Trend From Purchase To Leasing

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Us Epa Looking For Industry Input On Energy Star For Storage

Shifting From Energy Avoidance To Energy Efficiency

Ibm Out Oracle In As Buyer Of Sun

Us Epa Energy Star For Server Update

Data Center Io Bottlenecks Performance Issues And Impacts

Clarifying Clustered Storage Confusion

Green It Confusion Continues Opportunities Missed

Clouds Are Like Electricity Dont Be Scared

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

Should Everything Be Virtualized

Optimize Data Storage For Performance And Capacity Efficiency

Justifying Green It And Home Hardware Upgrades With Energystar

How To Win Approval For Upgrades Link Them To Business Benefits

What Is The Future Of Servers

Ssd And Storage System Performance

Green It And Virtual Data Centers

Emc Storage And Management Software Getting Fast

Its Us Census Time What About It Data Centers

Nas Nasa And Nascar Do They Have Anything In Common

Is Maid Dead I Dont Think So

Happy Earth Day 2010

Who Or What Is Your Sphere Of Influence

Apple Ipad Is It A Business Itool Or Itoy

Cloud Conversations Nirvanix Shutdown Caused Cloud Confidence Concerns

Industry Trends And Perspectives Raid Rebuild Rates

Industry Trends And Perspectives Storage Virtualization And Virtual Storage

Industry Trends And Perspectives Converged Networking And Io Virtualization Iov

Industry Trends And Perspectives Tiered Storage Systems And Mediums

Initial Virtumania Appearance Episode 14 With Fellow Vexperts

Industry Trends And Perspectives Tiered Hypervisors And Microsoft Hyperv

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

Industry Trends And Perspectives Blog Series

My Favorite Late Summer Reading Material

Supreme Court Rules Sarbox Intact Oversight Board Changes

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

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

Has Fcoe Entered The Trough Of Disillusionment

What Is Dfr Or Data Footprint Reduction

Santas It Elf Limited Time Discount

What Do You Do When Your Service Provider Drops The Ball

Green It Goes Mainstream What About Data Storage Environments

Storageio Momentus Hybrid Hard Disk Drive Hhdd Moments

Buzzword Bingo 1 0 Are You Ready For Fall Product Announcemnts

Happy Holidays 2010

What Have I Been Doing This Winter

What Do Vars And Clouds As Well As Msps Have In Common

What Do You Need When Its Time To Buy A New Server

Securing Data At Rest Self Encrypting Disks Seds

Buzzword Bingo And Acronym Update V2 011

Happy Earth Day 2011

The Data Storage Prayer

Cloud And Virtual Data Storage Networking

Cloud Storage Dont Be Scared However Look Before You Leap

Storageio Going Dutch Seminar For Storage And Io Professionals

Seagate Kinetic Cloud Object Storage Io Platform

Summer Greetings And Happy Holidays V2011

Industry Trend People Plus Data Are Aging And Living Longer

Dell Storage Forum 2011 Revisited

Storageio Going Dutch Again October 2011 Seminar For Storage Professionals

Time In And Around Clouds

Congratulations To Infosmack On Episode 100

Industry Trends And Perspectives Public And Private It Clouds

Dude Is Dell Going To Buy Brocade

Spring May 2012 Storageio News Letter

Data Migration Tips

Cloud Conversation Thanks Gartner For Saying What Has Been Said

December 2012 Storageio Update News Letter

January 2013 Server And Storageio Update Newsletter

Behind The Scenes Santa Claus Global Cloud Story

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

Many Faces Of Storage Hypervisor Virtual Storage Or Storage Virtualization

February 2013 Server And Storageio Update Newsletter

Xtremio Xtremsw And Xtremsf Emc Flash Ssd Portfolio Redefined

Some Things Keep Going Around Seagate Ships 2 Billion Hdds

Where Has The Fcoe Hype And Fud Gone With Poll

A Pivotal Or Cloudy Moment For Emc And Vmware

March Metrics And Measuring Social Media

Are Your Analyst Blogger Media Or Press Requests Being Read

March 2013 Server And Storageio Update Newsletter

Pressure Cooker Good

Hp Moonshot 1500 Software Defined Capable Compute Servers

Netapp And Akorri An E2e Cross Technology Domain Sra Play

Full Rss Archive Feeds Are Now Available For Storageioblog

2013 Server Storageio Update Newsletter

Morning Summer Storms Walking Midwest

Ibm Buys Softlayer Software Defined Infrastructures Clouds

Upgrading Lenovo X1 Windows 7 Samsung 840 Ssd

Geek Gadgets Kill A Watt Meter

Green Storage Practical Ways To Reduce Power Consumption

Data Proteciton For Virtual Environments At Vmware Vmworld

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

Industry Trends And Perspectives Tape Disk And Dedupe Coexistence

Ilm Has It Losts Its Meaning

Is Ibm Xiv Still Relevant

Data Proteciton For Virtual Environments

Spc And Storage Benchmarking Games

Server And Storage Virtualization Life Beyond Consolidation

Epa Draft 3 Of Energy Star For Computer Server Specification

Cloud Virtual Server Storage Io Technology Tiering

Disruptive Updates

Virtual Cloud Availability Shared Responsibility Common Sense

Storage Performance

Will 6gb Sas Kill Fibre Channel

Poll Whats Do You Think Of It Clouds

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

Catch Of The Day Or Post Of The Day

Availability Or Lack There Of Lessons From Our Frail Aging Infrastructure

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

Power Cooling Floor Space Environmental Pcfe And Green Metrics

Tape Talk Changing Role Of Tape

Sas Disk Drives Appearing In Larger Mid Range Arrays

Blog Post March Metric Madness Fun With Simple Math

Hard Product Vs Soft Product

Optical Storage Oppourtunities Or Obsolence

Storage Efficiency And Optimization The Other Green

Smb Capacity Planning Focusing On Energy Conservation

Whats Your Take On Ftc Guidelines For Bloggers

Technology And Traveling

Clouds And Data Loss Time For Cdp Commonsense Data Protection

Epa Energy Star For Data Center Storage Update 2

From Bits To Bytes Decoding Encoding

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

As The Hard Disk Drive Hdd Continues To Spin

Another Storageio Hybrid Momentus Moment

Cloud Conversations Aws Ebs Optimized Instances

Unified Storage Systems Showdown Netapp Fas Vs Emc Vnx

April 2013 Server Storageio Update Newsletter

Cloud Conversations Aws Ebs Glacier And S3 Overview Part Iii

Part Ii Ibm Server Side Storage Io Ssd Flash Cache Software

Are Hard Disk Drives Hdds Getting To Big

2011 Summer Momentus Hybrid Hard Disk Drive Hhdd Moment

Measuring Windows Performance Impact For Vdi Planning

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

Supporting It Growth Demand During Economic Uncertain Times

Inaugural Ssd Show

Care Coraid Content Conversation

Wd Buys Nand Flash Ssd Storage Io Cache Vendor Virident

Depends

Fall 2013 Dutch Cloud Virtual Storage Io Seminars

Data Footprint Reduction Part 2 Dell Ibm Ocarina And Storwize

Fall 2010 Storageio News Letter

Spring 2011 Server And Storageio News Letter

Winter 2011 Server And Storageio News Letter

Summer 2011 Storageio News Letter

A Storage Io Momentus Moment

Part Ii Emc Announces Xtremio General Availability

Fall December 2011 Storageio News Letter

Merry Christmas Seasons Happy Holidays 2013 Server Storageio

Fusionio Fio Ssd Vendor Ceo Flash Whats

Server Virtualization Nested Tiered Hypervisors

Book Review Rethinking Enterprise Storage Microsoftstorsimple Marc Farley

Kudos To Hp Ceo Mark Hurd For Dignity To Step Down From His Post

Dell Inspiron 660 Virtual Diamond Rough

August 2010 Storageio News Letter

Small Medium Business Smb Continues Gain Respect Soho

Using Removable Hard Disk Drives Rhdds

Storage Bridge Bay Sbb Industry Group Update

Emc Announces Xtremio General Availability Part

Emc Evolves Enterprise Data Protection Enhancements Part

Raid Extend Life Nand Flash Ssd

Fall 2013 Aws Cloud Storage Compute Enhancements

Emc Vplex Virtual Storage Redefined Or Respun

The Other Green Storage Efficiency And Optimization

Is Fcoe Struggling To Gain Traction Or On A Normal Adoption Course

Big Fish And Small Fish Fish Story Or The One That Did Not Get Away

Side Context Iops

Part Ii Revisiting Reinvent 2014 And Other Aws Updates

Summer 2013 Server And Storageio Update Newsletter

Dell Will Buy Someone However Not Brocade At Least For Now

Happy Thanks Giving 2010

June 2010 Storageio Newsletter

What Records Will Emc Break In Nyc January 18 2011

Smb Soho And Low End Nas Gaining Enterprise Features

Gregs Storageio Out And About Update June 2010

Vmware Vsphere V5 And Storage Drs

Storage Effiency And Optimizaiton Balancing Time And Space

Pue Are You Managing Power Energy Or Productivity

Emc Vnx Mcx Storage Io Work

The New Green Gaining Realistic Economic Efficiencys Now

Closing The Green Gap Wsradio Internet Radio Interview

Determining Computer Or Server Energy Use

Epa Energy Star For Data Center Storage Update

Saving Money With Green It Time To Invest In Information Factories

Webcast E2e Awareness And Insight For It Environments

Ibm Server Side Storage Io Ssd Flash Cache Software

Part Ii Emc Evolves Enterprise Data Protection Enhancements

Cisco Buys Whiptail Continuing Storage Storage Io Flash Cash Cache Dash

Fall 2013 Storageio Update Newsletter

Raid Relevance Revisited

Have You Heard Of 2drs Data Protection Technology

July 2010 Odds And Ends Perspectives Tips And Articles

Has Ssd Put Hard Disk Drives Hdds On Endangered Species List

Seagate Proof Life Enterprise Hdd Enhancements

Seagate To Say Goodbye To Cayman Islands Hello Ireland

Cloud Conversations Gaining Cloud Confidence From Insights Into Aws Outages

Have Vtls Or Vxls Become Zombies Declared Dead Yet Still Alive

Tiered Communication And Media Venues

Are You On The Storageio It Data Infrastructure Industry Links Page

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

Tape Talk Time

Back To School Dedupe School

Storageio V20 11 2011 Events Seminars And Web Casts Schedule

Getting Caught Up And Holiday Shopping

Performance Availability Storageioblog Featured Itke Guest Blog

The New Green It Efficient Effective Smart And Productive

Dude Is Dell Doing A Disk Deal Again With Compellent

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

2010 And 2011 Trends Perspectives And Predictions More Of The Same

Mainframe Cmg Virtualization Storage And Zombie Technologies

Vmworld 2010 Virtual Roads Clouds And Inxs Devil Inside

Green Power And Cooling Tools And Calculators

Green It Green Gap Tiered Energy And Green Myths

Vmworld 2013 Vmware Server Storage Io Networking Update Day 1

Part Ii Xtremio Xtremsw And Xtremsf Emc Flash Ssd Portfolio Redefined

Datadynamics Storagex 70 File Data Management Migration Software

Whats Your Take On Open Virtualization Alliance And Vmware

September October Server Storageio Update Newsletter

Server Storageio June July 2016 Update Newsletter

Open Data Center Alliance Odca Bmw Private Cloud Strategy

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

Server Storageio March 2016 Update Newsletter

Netapp Ef540 Something Familiar Something New

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

Emc Vipr Software Defined Object Storage Part Ii

Emc Vipr Software Defined Object Storage Part Iii

Emc Vipr Virtual Physical Object Software Defined Storage Sds

Breaking Vmware Esxi 55 Acpi Boot Loop Lenovo Td350

Storageio In The News

Summer Book Update And Back To School Reading

February 2014 Server Storageio Update Newsletter

November 2013 Server Storageio Update Newsletter

Matt Vogt Computex Talks Vmware Vcops Podcast

August 2014 Server Storageio Update Newsletter

July 2014 Server Storageio Update Newsletter

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

Snow Fun And Information Technology They Do Mix

Technology Tiering Servers Storage And Snow Removal

Netapp Buying Lsis Engenio Storage Business Unit

Summer Weddings Emcdatadomain And Hpibrix

Server Storage Io Intel Nuc Nick Knack Notes Second Impressions

Emc Vfcache Respinning Ssd And Intelligent Caching Part Ii

Hds Claus Mikkelsen Talking Storage Snw Fall 2012

How To Write Publish And Promote A Book Or Blog

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

Open Data Center Alliance Odca Publishes Two New Cloud Usage Models

Nand Flash Sata Ssd Ddr3 Dimm Slot

Server Storageio February 2016 Update Newsletter

Server Storageio January 2016 Update Newsletter

June 2017 Server Storageio Data Infrastructures Update Newsletter

Ibms Storwize Or Wise Storage The V7000 And Dfr

Re Visiting If Ibm Xiv Is Still Relevant With V7000

Part I Puresystems Something Old Something New Something From Big Blue

Part V Puresystems Something Old Something New Something From Big Blue

Part Iv Puresystems Something Old Something New Something From Big Blue

Part Ii Puresystems Something Old Something New Something From Big Blue

Microsoft Azure Cloud Software Defined Data Infrastructure Reference Architecture Resources

Happy 100th Birthday Or Anniversary Wishes

Azure Stack Tp3 Overview Preview Review Part Ii

Data Protection Diaries Data Protection

March2014 Storageio Newsletter Cisco Cloud Vmware Vsan

June 2014 Server Storageio Update Newsletter

Chat With Cash Coleman Talking Cleardb Cloud Database And Johnny Cash

April 2014 Server Storageio Update Newsletter

Acadia Vce Vmware Cisco Emc Virtual Computing Environment

Storageio Spring Keynote And Speaking Tour V2008

Server Storageio April 2016 Update Newsletter

Cloud Conversations Loss Of Data Access Vs Data Loss

Hpe Buying Server Storage Io Data Infrastructures

January 2017 Server Storageio Update Newsletter

Top Vblog 2017 Voting Open

Data Infrastructure Tradecraft Trends

Converged Ci Hyperconverged Hci Mean Storage Io

Popular Viewed Storageioblog Posts 2016

March 2017 Server Storageio Update Newsletter

Top Storage World Decade

Back To School Shopping Dude Dell Digests 3par Disk Storage

Does Ibm Power7 Processor Announcement Signal Storage Upgrades

Do You Know Hds Or What It Means

Is The New Hds Vsp Really The Mvsp

Hds Mid Summer Storage Converged Compute Enhancements

Object Storage News Trends Cloud Bulk Storage

Hds Buys Bluearc Any Surprises Here

June 2015 Server Storageio Update Newsletter

Server Storageio Holiday Seasons 2016

Do Software Vendors Eliminate Or Move Location Of Vendor Lock In

Vendor Lockin Responsibiity

Spam Of A Different Kind

Part Iii Puresystems Something Old Something New Something From Big Blue

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

Which Enterprise Hdd Content Application Testing

Which Enterprise Hdd Content Server Test Configuration

Hdd Ssd Flash Storage Iops

Which Enterprise Hdd Use For Database Workloads

Enterprise Hdd For Content Server Different File Size

Which Enterprise Hdd General Io Performance

Enterprise Hdds Evolve For Content Server Applications

Achieve Flexible Data Protection

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

Software Defined Data Infrastructure Essentials Book SDDC

What This All Means

SDDC Data Infrastructure

Check out the above links to data infrastructure resource links.

Ok, nuff said, for now.

Gs

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

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

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How to Achieve Flexible Data Protection Availability with All Flash Storage Solutions

Achieve Flexible Data Protection Availability with All Flash Solutions

server storage I/O data infrastructure trends

Updated 1/21/2018

How to Achieve Flexible flash data protection and Availability with All-Flash Storage Solutions

Interactive webinar discussion (not death by power point or Ui Gui product demo ;) pertaining flash data protection )
Tuesday January 30 2018 11AM PT / 2PM ET
Via Redmond Magazine (Free with registration)

Everything is not the same across different organizations, environments, application workloads and the data infrastructures that support them. Fast application and workloads need fast protection, restoration, and resumption as well as fast flash storage. This applies across legacy, software-defined, virtual, container, cloud, hybrid, converged and HCI among other environments.

SDDC Data Infrastructure Data Protection

Join me along with representatives from Pure Storage along with Veeam for this interactive discussion as we explore how to boost the performance, availability, capacity, and economics (PACE) of your applications along with the data infrastructures that support them.

  • How all-flash storage enables faster protection and restoration of fast applications
  • Why data protection and availability should not be an afterthought
  • Ways to leverage your data protection storage to drive business change
  • How to simplify and reduce complexity to boost productivity while lowering costs
  • Why workload aggregation consolidation should not cause aggravation

Register for the live event or catch the replay here.

Where to learn more

Learn more about data protection, SSD, flash, data infrastructure 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

Fast applications need fast and resilient data infrastructures that include server, storage, I/O networking along with data protection. Likewise performance depends on availability along with durability, likewise, availability and accessibility depend on performance, they go hand in hand. Join me and others from Pure Storage as well as Veeam for this conversational discussion about How to Achieve Flexible Data Protection and Availability with All-Flash Storage Solutions.

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.

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2017 Holiday Seasons Greetings From Server StorageIO

2017 Holiday Seasons Greetings

Greetings from Server StorageIO wishing you, your data infrastructures as well as friends and family’s all the best for a safe, merry happy 2017 holiday season.

In the Jingle Bell

Btw, if you have not done so lately, check out storageio.tv to view various videos, podcasts and images. Some of the storageio.tv content is data infrastructure technology, tools, technique, tradecraft and trends related. Also on storageio.tv are fun content including views from the drone as well as cooking (food and recipes) among other items.

Ok, nuff said, for now.

Cheers 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 2006-2023 Server StorageIO(R) and UnlimitedIO. All Rights Reserved.

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November 2017 Server StorageIO Data Infrastructure Update Newsletter

Volume 17, Issue 11 (November 2017)

Hello and welcome to the November 2017 issue of the Server StorageIO update newsletter.

Software-Defined Data Infrastructure Essentials SDDI SDDC

2017 has a few more weeks left which look to be busy with end of year, holidays and other activities. Like the rest of 2017 November saw a lot of activity in and around the industry, setting up 2018 as yet another sequel to the busiest and most exciting year ever.

This is also the time of year when predictions for the following year (e.g. 2018) start to roll out, some of which are variations from those of the past or perennial favorites (e.g. the year of flash, the year of cloud, the year of software defined, the year of <insert_your_favorite_item_here>. Look for predictions and perspectives in future posts and newsletters.

Having been a busy month, let’s get to the content…

In This Issue

Enjoy this edition of the Server StorageIO data infrastructure update newsletter.

Cheers GS

Data Infrastructure and IT Industry Activity Trends

Some recent Industry Activities, Trends, News and Announcements include:

On the heals of completing its acquisition of Brocade (note previously Avago (who bought LSI) also bought Broadcom and then changed its name to the more well-known entity. Broadcom also announced relocating it headquarters from Singapore to the US, along an over $100 Billion USD acquisition offer of Qualcomm (here is interesting perspective Apple might play). Broadcom has been focused more on server, storage, I/O and general networking technology, while Qualcomm on mobile including phones and related items. Note that Qualcomm has previously made a $38.5 Billion USD offer for NXP semiconductors waiting regularity approval. View recent Broadcom financial results here.

Also in November server storage I/O controller chip maker Marvell (not to be confused with entertainment provider Marvel) announced a merger with Cavium who had previously acquired Qlogic among others. The resulting combined entity to be called Marvell will have an estimated $16 Billion USD revenue stream focused on server, storage, I/O and networking technologies among others.

In other merger and acquisition activity, VMware announced acquisition of VeloCloud for software defined wide area networking (SD-WAN).

With Super Compute 2017 (SC17) in November there were several announcements including from ATTO, DDN, Enmotus and Micron, Everspin, along with many others. By the way, in case you missed it at end of October Microsoft and Cray announced a partnership to bring Super Compute capabilities to Azure clouds. Speaking of Microsoft, there was also an announcement of adding VMware running on top of Azure (granted without VMware support), similar in concept to VMware on AWS (read hare).

Also at the end of November was AWS Reinvent with many announcements (more on those in a follow-up newsletter and posts). Prior to Reinvent AWS announced several server, storage and other data infrastructure security enhancements including for S3. Highlights from AWS reinvent include Fargate (serverless aka containers at scale without managing infrastructure), Elastic Container Services for Kubernetes (EKS), Greengrass (machine learning [ML] data infrastructure), along with many others.

Fargate is for those who want to leverage serveless microservices containers without having to devote DevOps and related activity to the care and feeding of its data infrastructure. In other words, Fargate is for those who want to focus maximum effort on the business applications, vs. the business of setting up and maintaining the data infrastructure for serverless On the other hand, AWS also announced EKS for those who want or need to customize their serverless data infrastructure including around Kubernetes among others.

In other industry activity, Taiwanese based Foxconn who manufactures technology for the who’s who of the industry announced progress towards their future Wisconsin based factory complex.

Over at HPE, the big news announcement is that CEO Meg Whitman is stepping down. HPE also announced new AMD powered Gen 10 Proliant services, as well as multi-cloud management solutions. HPE also announced new partnerships with DDN for HPC and SC, with Rackspace for selling private cloud services, along with Cloudian EMEA partnership among others.

OwnBackup announced a new version of their data protection software, while low-cost budget bulk storage service backblaze (B2) announced their more recent quarterly drive failure (or success) reliability reports. Meanwhile over at Quantum they released former Ceo Jon Gacek and rotated in new management.

Red Hat announced Ceph Storage 3 including CephFS (POSIX compatible file system), iSCSI gateway including support for VMware and Windows that lack native Ceph drivers, daemon deployment in Linux containers for smaller hardware footprint. Also included are enhanced monitoring, troubleshooting and diagnostics to streamline deployment and ongoing management. Red Hat also announced OpenShift version 3.7 for containers.

SANblaze announced NVMf and dual port NVMe capabilities for NVMe fabrics, while Linbit won an European grant to build out a software defined storage cloud scale out solution.

I often get asked who are the hot, new, trendy or other vendors and services to keep an eye on some of which I have mentioned in previous newsletters, as well as posts such as here and here. Moving in to 2018 some to keep an eye on (not all are new or trendy, yet they can enable you to be productive, or differentiate) include the following.

AWS, Bluemedora, Chelsio, Cloudian, CloudPassage, Compuverde, Databricks, Datadog, Datos, Enmotus, Everspin, Excelero, Fluree (Blockchain database), Google, Mellonox, Microsemi, Microsoft, Marvel and Cavium, MyWorkDrive, Red Hat, Rook, Rozo, Rubrik, Strongbox, Storone, Turbonomic, Ubuntu, Veeam, Velostrata, Virtuozo, VMware, WekaIO and others.

What the above means, is that it has been a busy month as well as year, and, the year is not over yet. There are still plenty of shopping days left both for christmas and the holidays, as well as for IT year-end spending, vendors looking to do acquisitions, or other last-minute projects. Speaking of which, drop me a note if you have any end of year, or new year projects Server StorageIO can assist you with.

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

Server StorageIO Commentary in the news, tips and articles

Recent Server StorageIO industry trends perspectives commentary in the news.

Via HPE Insights: Comments on Public cloud versus on-prem storage
Via DataCenterKnowledge: Data Center Standards: Where’s the Value?
Via arsTechnica: Comments on cloud backup disaster recovery

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

Server StorageIOblog Data Infrastructure Posts

Recent and popular Server StorageIOblog posts include:

In Case You Missed It #ICYMI

View other recent as well as past StorageIOblog posts here

Server StorageIO Recommended Reading (Watching and Listening) List

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

Intel Recommended Reading List (IRRL) for developers is a good resource to check out.

For those who are into Linux, container and hypervisor performance along with internals including cloud based, check out Brendan Gregg site. He has a lot of great material including some recent interesting posts ranging from dealing with workplace jerks, to whats inside AWS EC2 new KVM (switch from Xen based) hypervisors among others.

Here is a post by New York Times CIO/CTO Nick Rockwell The (Futile) Resistance to Serverless, also check out my podcast discussion with Nick here.

Over at Next Platform they have some interesting perspectives on Intel’s next Exascale architecture worth spending a few minutes to read.

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

Events and Activities

Recent and upcoming event activities.

Nov. 9, 2017 – Webinar – All You Need To Know about ROBO Data Protection Backup
Nov. 2, 2017 – Webinar – Modern Data Protection for Hyper-Convergence

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

Server StorageIO Industry Resources and Links

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

Connect and Converse With Us


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 2006-2023 Server StorageIO(R) and UnlimitedIO. All Rights Reserved.

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Data Protection Diaries Fundamental Topics Tools Techniques Technologies Tips

Data Protection Fundamental Topics Tools Techniques Technologies Tips

Data Infrastructure and 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 Schulz – www.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.

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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 Schulz – www.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.