DR Journal

Cloud Economics drive the IT Infrastructure of Tomorrow

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The cloud continues to dominate IT as businesses make their infrastructure decisions based on cost and agility. Public cloud, where shared infrastructure is paid for and utilized only when needed, is the most popular model today. However, more and more organizations are addressing security concerns by creating their own private clouds. As businesses deploy private cloud infrastructure, they are adopting techniques used in the public cloud to control costs. Gone are the traditional arrays and network switches of the past, replaced with software-defined data centers running on industry standard servers.

Efficiency features make the cloud model more effective by reducing costs and increasing data transfer speeds. One such feature, which is particularly effective in cloud environments is inline data reduction. This is a technology that can be used to lower the costs of data in flight and at rest. In fact, data reduction delivers unique benefits to each of the cloud deployment models.

Public Clouds

The public cloud’s raison d’etre is its ability to deliver IT business agility, deployment flexibility and elasticity. As a result, new workloads are increasingly deployed in public clouds.  Worldwide public IT cloud service revenue in 2018 is predicted to be $127B.  

Data reduction technology minimizes public cloud costs. For example, deduplication and compression typically cut capacity requirements of block storage in enterprise public cloud deployments by up to 6:1.  These savings are realized in reduced storage consumption and operating costs in public cloud deployments.   

Consider AWS costs employing data reduction;

If you provision a 300 TB of EBS General Purpose SSD (gp2) storage for 12 hours per day over a 30 day month in a region that charges $0.10 per GB-month, you would be charged $15,000 for the storage.

With data reduction, that monthly cost of $15,000 would be reduced to $2,500.  Over a 12 month period you will save $150,000.   Capacity planning is a simpler problem when it is 1/6th its former size.  Bottom line, data reduction increases agility and reduces costs of public clouds.

One data reduction application that can readily be applied in public cloud is Permabit’s Virtual Disk Optimizer (VDO) which is a pre-packaged software solution that installs and deploys in minutes on Red Hat Enterprise Linux and Ubuntu LTS Linux distributions. To deploy VDO in Amazon AWS, the administrator provisions Elastic Block Storage (EBS) volumes, installs the VDO package into their VMs and applies VDO to the block devices represented for their EBS volumes.  Since VDO is implemented in the Linux device mapper, it is transparent to the applications installed above it.

As data is written out to block storage volumes, VDO applies three reduction techniques:

  1. Zero-block elimination uses pattern matching techniques to eliminate 4 KB zero blocks

  2. Inline Deduplication eliminates 4 KB duplicate blocks

  3. HIOPS Compression™ compresses remaining blocks 

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This approach results in remarkable 6:1 data reduction rates across a wide range of data sets. 

Private Cloud

Organizations see similar benefits when they deploy data reduction in their private cloud environments. Private cloud deployments are selected over public because they offer the increased flexibility of the public cloud model but keep privacy and security under their own control. IDCpredicts in 2017 $17.2B in infrastructure spending for private cloud, including on-premises and hosted private clouds.

One problem that data reduction addresses for the private cloud is that, when implementing private cloud, organizations can get hit with the double whammy of hardware infrastructure costs plus annual software licensing costs. For example, Software Defined Storage (SDS) solutions are typically licensed by capacity and their costs are directly proportional to hardware infrastructure storage expenses. Data reduction decreases storage costs because it reduces storage capacity consumption. For example, deduplication and compression typically cut capacity requirements of block storage in enterprise deployments by up to 6:1 or approximately 85%.

Consider a private cloud configuration with a 1 PB deployment of storage infrastructure and SDS. Assuming a current hardware cost of $500 per TB for commodity server-based storage infrastructure with datacenter-class SSDs and a cost of $56,000 per 512 TB for the SDS component, users would pay $612,000 in the first year. In addition, software subscriptions are annual, over three years you will spend $836,000 for 1 PB of storage and over five years, $1,060,000.

The same configuration with 6:1 data reduction in comparison over five years will cost $176,667 for hardware and software resulting in $883,333 in savings. And that’s not including the additional substantial savings in power cooling and space. As businesses develop private cloud deployments, they must be sure it has data reduction capabilities because the cost savings are compelling.

When implementing private cloud on Linux, the easiest way to include data reduction is with Permabit Virtual Data Optimizer (VDO). VDO operates in the Linux kernel as one of many core data management services and is a device mapper target driver transparent to persistent and ephemeral storage services whether the storage layers above are providing object, block, compute, or file based access.

VDO – Seamless and Transparent Data Reduction

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The same transparency applies to the applications running above the storage service level. Customers using VDO today realize savings up to 6:1 across a wide range of use cases.

Some workflows that benefit heavily from data reduction are;

  • Logging: messaging, events, system and application logs

  • Monitoring: alerting, and tracing systems

  • Database: databases with textual content, NOSQL approaches such as MongoDB and Hadoop

  • User Data: home directories, development build environments

  • Virtualization and containers: virtual server, VDI, and container system image storage

  • Live system backups: used for rapid disaster recovery

With data reduction, cumulative cost savings can be achieved across a wide range of use cases which makes data reduction so attractive for private cloud deployments.

Reducing Hybrid Cloud’s Highly Redundant Data

Storage is at the foundation of cloud services and almost universally data in the cloud must be replicated for data safety. Hybrid cloud architectures that combine on-premise resources (private cloud) with colocation, private and multiple public clouds result in highly redundant data environments. IDC’s FutureScape report finds “Over 80% of enterprise IT organizations will commit to hybrid cloud architectures, encompassing multiple public cloud services, as well as private clouds by the end of 2017.” (IDC 259840)

Depending on a single cloud storage provider for storage services can risk SLA targets. Consider the widespread AWS S3 storage errors that occurred on February 28th 2017, where data was not available to clients for several hours. Because of loss of data access businesses may have lost millions of dollars of revenue. As a result today more enterprises are pursuing a “Cloud of Clouds” approach where data is redundantly distributed across multiple clouds for data safety and accessibility. But unfortunately, because of the data redundancy, this approach increases storage capacity consumption and cost.

That’s where data reduction comes in. In hybrid cloud deployments where data is replicated to the participating clouds, data reduction multiplies capacity and cost savings. If 3 copies of the data are kept in 3 different clouds, 3 times as much is saved. Take the private cloud example above where data reduction drove down the costs of a 1 PB deployment to $176,667, resulting in $883,333 in savings over five years. If that PB is replicated in 3 different clouds, the savings would be multiplied by 3 for a total savings of $2,649,999.

Permabit’s Virtual Data Optimizer (VDO) provides the perfect solution to address the multi-site storage capacity and bandwidth challenges faced in hybrid cloud environments. Its advanced data reduction capabilities have the same impact on bandwidth consumption as they do on storage and translates to a 6X reduction in network bandwidth consumption and associated cost.  Because VDO operates at the device level, it can sit above block-level replication products to optimize data before data is written out and replicated.

Summary

IT professionals are finding that the future of IT infrastructure lies in the cloud. Data reduction technologies enable clouds – public, private and hybrid to deliver on their promise of safety, agility and elasticity at the lowest possible cost making cloud the deployment model of choice for IT infrastructure going forward.”

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Cloud Economics drive the IT Infrastructure of Tomorrow

| ITBusinessNet.com
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Cloud Economics drive the IT Infrastructure of Tomorrow

The cloud continues to dominate IT as businesses make their infrastructure decisions based on cost and agility. Public cloud, where shared infrastructure is paid for and utilized only when needed, is the most popular model today. However, more and more organizations are addressing security concerns by creating their own private clouds. As businesses deploy private cloud infrastructure they are adopting techniques used in the public cloud to control costs. Gone are the traditional arrays and network switches of the past, replaced with software-defined data centers running on industry standard servers.

Efficiency features make the cloud model more effective by reducing costs and increasing data transfer speeds. One such feature, which is particularly effective in cloud environments, is inline data reduction. This is a technology that can be used to lower the costs of data in flight and at rest. In fact, data reduction delivers unique benefits to each of the cloud deployment models.

Public Clouds

The public cloud’s raison d’etre is its ability to deliver IT business agility, deployment flexibility and elasticity. As a result new workloads are increasingly deployed in public clouds.  Worldwide public IT cloud service revenue in 2018 is predicted to be $127B.

Data reduction technology minimizes public cloud costs. For example, deduplication and compression typically cut capacity requirements of block storage in enterprise public cloud deployments by up to 6:1.  These savings are realized in reduced storage consumption and operating costs in public cloud deployments.

Consider AWS costs employing data reduction;

If you provision a 300TB of EBS General Purpose SSD (gp2) storage for 12 hours per day over a 30 day month in a region that charges $0.10 per GB-month, you would be charged $15,000 for the storage.

With data reduction, that monthly cost of $15,000 would be reduced to $2,500.  Over a 12 month period you will save $150,000.   Capacity planning is a simpler problem when it is 1/6th its former size.  Bottom line, data reduction increases agility and reduces costs of public clouds.

One data reduction application that can readily be applied in public cloud is Permabit’s Virtual Disk Optimizer (VDO) which is a pre-packaged software solution that installs and deploys in minutes on Red Hat Enterprise Linux and Ubuntu LTS Linux distributions.  To deploy VDO in Amazon AWS, the administrator provisions Elastic Block Storage (EBS) volumes, installs the VDO package into their VMs and applies VDO to the block devices represented for their EBS volumes.  Since VDO is implemented in the Linux device mapper, it is transparent to the applications installed above it.

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CLICK ON THE LINK BELOW

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Using Data Reduction at the OS layer in Enterprise Linux Environments

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Enterprises and cloud service providers that have built their infrastructure around Linux should deploy data reduction in the operating system to drive costs down, say experts at Permabit Technology Corporation, the company behind Permabit Virtual Data Optimizer (VDO).  Permabit VDO is the only complete data reduction software for Linux, the world’s most popular server Operating System (OS). Permabit’s VDO software fills a gap in the Linux feature set by providing a cost effective, alternative to the data reduction services delivered as part of the two other major OS platforms – Microsoft Windows and VMware. IT architects are driven to cut costs as they build out their next generation infrastructure with one or more of these OS platforms in  public and/or private cloud deployments and one obvious way to do so is with data reduction.

When employed as a component of the OS, data reduction can be applied universally without lock-in of proprietary solutions. Adding compression, deduplication, and thin provisioning to the core OS, data reduction benefits can be leveraged by any application or infrastructure services running on that OS. This ensures that savings accrue across the entire IT infrastructure, delivering TCO advantages no matter where the data resides. This is the future of data reduction – as a ubiquitous service of the OS.

“We’re seeing movement away from proprietary storage solutions, where data reduction was a key differentiated feature, toward OS-based capabilities that are applied across an entire infrastructure,” said Tom Cook, Permabit CEO.  “Early adopters are reaping financial rewards through reduced cost of equipment, space, power and cooling. Today we are also seeing adoption of data reduction in the OS by more conservative IT organizations who are driven to take on more initiatives with tightly constrained IT budgets.”

VDO, with inline data deduplication, HIOPS Compression®, and fine-grained thin provisioning, is deployed as a device-mapper driver for Linux. This approach ensures compatibility with a full complement of direct-attached/ephemeral, block, file and object interfaces. VDO data reduction is available for Red Hat Enterprise Linux and Canonical Ubuntu Linux LTS distributions.

Advantages of in-OS data reduction technology include:

  • Improved density for public/private /hybrid cloud storage, resulting in lower storage and service costs
  • Vendor independent to function across hardware running the target OS
  • Seamless data mobility between on-premise and cloud resources
  • Up to six times lower IT infrastructure OpEx
  • Transparent to end users accessing data
  • Requires no modifications to existing applications, file systems, virtualization features, or data protection capabilities

With VDO, these advantages are being realized on Linux today. VDO deployments have been completed (or are currently in progress) with large telecommunications companies, government agencies, financial services firms and IaaS providers who have standardized on Linux for their data centers. With data reduction in Linux, enterprises achieve vendor independence across all Linux based storage, increased mobility of reduced data and hyper scale economics. What an unbeatable combination!

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Addressing Bandwidth Challenges in the Hybrid Cloud

| By: (53)

Any application infrastructure that relies on a single data center is only as safe as that data center’s physical resources and the competence of its staff.  Witness the recent S3 outage at Amazon. When you choose to deploy in a single public cloud, you are delegating infrastructure management to your provider. When you’re exclusively running in-house, private cloud infrastructure, you’re entrusting that management to your own organization.  Either way mistakes…

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Reduce Cloud’s Highly Redundant Data

| By: (60)

Storage is the foundation of cloud services. All cloud services – delineated as scalable, elastic, on-demand, and self-service – begin with storage. Almost universally, cloud storage services are virtualized and hybrid cloud architectures that combine on-premise resources with colocation, private and public clouds result in highly redundant data environments.  IDC’s FutureScape report finds “Over 80% of enterprise IT organizations will commit to hybrid cloud architectures, encompassing multiple public cloud services,…

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Hybrid Cloud

Hybrid Cloud Gains in Popularity, Survey Finds

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Hybrid Cloud

The hybrid model of cloud computing is gaining more popularity in the enterprise, as businesses move more workloads and applications to public cloud infrastructures and away from private deployments.

Those are some of the findings from RightScale’s annual “State of the Cloud” report, which the company released Wednesday. It’s based on interviews with 1,000 IT professionals, with 48% of them working in companies with more than 1,000 employees.

The biggest takeaway from the report is that enterprises and their IT departments are splitting their cloud dollars between public and private deployments, and creating demands for a hybrid approach.

“The 2017 State of the Cloud Survey shows that while hybrid cloud remains the preferred enterprise strategy, public cloud adoption is growing while private cloud adoption flattened and fewer companies are prioritizing building a private cloud,” according to a blog post accompanying the report. “This was a change from last year’s survey, where we saw strong gains in private cloud use.”

Specifically, 85% of respondents reported having a multi-cloud, hybrid strategy, and that’s up from the 82% who reported a similar approach in 2016. At the same time, private cloud adoption dropped from 77% in 2016 to 72% in 2017.

In the survey, 41% of respondents reported running workloads in public clouds, while 38% said they run workloads in private clouds. In large enterprises, those numbers reverse, with 32% of respondents running workloads in public clouds, and 43% running workloads within private infrastructures.

“It’s important to note that the workloads running in private cloud may include workloads running in existing virtualized environments or bare-metal environments that have been ‘cloudified,’ ” according to the report.

When it comes to adopting cloud technologies and services, there are less barriers and concerns this year compared to 2016. The lack of resources and expertise to implement a cloud strategy was still the top concern.

In addition the report notes that in every cloud expertise level the Top 5 Challenges” indicate there is a substantial concern with “managing costs”.  One vehicle that can help manage costs is to apply data reduction technologies to your cloud deployment. Permabit VDO can be applied to public and/or private clouds quickly and easily enabling cost reduction of 50% or more in on-premise, in-transit and public cloud deployments.

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Why Deduplication Matters for Cloud Storage

| dzone.com
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Most people assume cloud storage is cheaper than on-premise storage. After all, why wouldn’t they? You can rent object storage for $276 per TB per year or less, depending on your performance and access requirements. Enterprise storage costs between $2,500 to $4,000 per TB per year, according to analysts at Gartner and ESG.

This comparison makes sense for primary data, but what happens when you make backups or copies of data for other reasons in the cloud? Imagine that an enterprise needs to retain 3 years of monthly backups of a 100TB data set. In the cloud, this can be easily equated to 3.6 PB of raw backup data, or a monthly bill of over $83,000. That’s about $1 million a year before you even factor in and data access or retrieval charges.

That is precisely why efficient deduplication is hugely important for both on-premise and cloud storage, especially when enterprises want to retain their secondary data (backup, archival, long-term retention) for weeks, months, and years. Cloud storage costs can add up quickly, surprising even astute IT professionals, especially as data sizes get bigger with web-scale architectures, data gets replicated and they discover it can’t be deduplicated in the cloud.

The Promise of Cloud Storage: Cheap, Scalable, Forever Available

Cloud storage is viewed as cheap, reliable and infinitely scalable – which is generally true. Object storage like AWS S3 is available at just $23/TB per month for the standard tier, or $12.50/TB for the Infrequent Access tier. Many modern applications can take advantage of object storage. Cloud providers offer their own file or block options, such as AWS EBS (Elastic Block Storage) that starts at $100/TB per month, prorated hourly. Third-party solutions also exist that connect traditional file or block storage to object storage as a back-end.

Even AWS EBS, at $1,200/TB per year, compares favorably to on-premise solutions that cost 2-3 times as much, and require high upfront capital expenditures. To recap, enterprises are gravitating to the cloud because the OPEX costs are significantly lower, there’s minimal up-front cost, and you pay as you go (vs. traditional storage where you have to buy far ahead of actual need)

How Cloud Storage Costs Can Get Out of Hand: Copies, Copies Everywhere

The direct cost comparison between cloud storage and traditional on-premise storage can distract from managing storage costs in the cloud, particularly as more and more data and applications move there. There are three components to cloud storage costs to consider:

  • Cost for storing the primary data, either on object or block storage
  • Cost for any copies, snapshots, backups, or archive copies of data
  • Transfer charges for data

We’ve covered the first one. Let’s look at the other two.

Copies of data. It’s not how much data you put into the cloud — uploading data is free, and storing a single copy is cheap. It’s when you start making multiple copies of data — for backups, archives, or any other reason — that costs spiral if you’re not careful. Even if you don’t make actual copies of the data, applications or databases often have built-in data redundancy and replicate data (or in database parlance, a Replication Factor).

In the cloud, each copy you make of an object incurs the same cost as the original. Cloud providers may do some dedupe or compression behind the scenes, but this isn’t generally credited back to the customer. For example, in a consumer cloud storage service like DropBox, if you make a copy or ten copies of a file, each copy counts against your storage quota.

For enterprises, this means data snapshots, backups, and archived data all incur additional costs. As an example, AWS EBS charges $0.05/GB per month for storing snapshots. While the snapshots are compressed and only store incremental data, they’re not deduplicated. Storing a snapshot of that 100 TB dataset could cost $60,000 per year, and that’s assuming it doesn’t grow at all.

Data access. Public cloud providers generally charge for data transfer either between cloud regions or out of the cloud. For example, moving or copying a TB of AWS S3 data between Amazon regions costs $20, and transferring a TB of data out to the internet costs $90. Combined with GET, PUT, POST, LIST and DELETE request charges, data access costs can really add up.

Why Deduplication in the Cloud Matters

Cloud applications are distributed by design and are deployed on non-relational massively scalable databases as a standard. In non-relational databases, most data is redundant before you even make a copy. There are common blocks, objects, and databases like MongoDB or Cassandra have replication factor (RF) of 3 to ensure data integrity in a distributed cluster, so you start out with three copies.

Backups or secondary copies are usually created and maintained via snapshots (for example, using EBS snapshots as noted earlier). The database architecture means that when you take a snapshot, you’re really making three copies of the data. Without any deduplication, this gets really expensive.

Today there are solutions to solve the public cloud deduplication or data reduction conundrum. Permabit VDO can be easily deployed in public and/or private cloud solutions  Take a look at the following blog from Tom Cook http://permabit.com/data-efficiency-in-public-clouds/ or for the technical details look at one from Louis Imershein http://permabit.com/effective-use-of-data-reduction-in-the-public-cloud/. Both provide examples and details on why and how to drive deduplication and compression solutions in a public cloud.

 

 

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Effective use of data reduction in the Public Cloud

| By: (53)

  Permabit CEO, Tom Cook recently wrote about how data reduction technology can simplify the problems associated with provisioning adequate storage resources in the public cloud, while balancing performance and efficiency.  The good news is, taking advantage of data reduction software in the public cloud is easier than ever. For example,Permabit’s Virtual Disk Optimizer (VDO) is a pre-packaged software solution that installs and deploys in minutes on Red Hat Enterprise…

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Data Efficiency in Public Clouds

| By: (60)

Public cloud deployments deliver agility, flexibility and elasticity. This is why new workloads are increasingly deployed in public clouds.  Worldwide public IT cloud service revenue in 2018 is predicted to be $127B.  It’s powerful to spin up a data instance instantaneously, however managing workloads and storage still requires analysis, planning and monthly provisioning.  It would be extremely advantageous if public cloud storage capacity could automatically grow and condense to optimize…

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