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Simplifying Data Management for Virtualized Workloads Across Private, Public and Hybrid Clouds

A Crash Course in How to Leverage and Protect All Data, in All Environments

When it comes to protecting your virtual machines (VMs), here’s a surprise: it’s not about your VMs at all. It’s really more about the data that your virtual servers contain – whether on premises or in the cloud. To ensure reliable VM data protection, you need to build a model that will not only capture, monitor and protect your data, but also help you leverage it – regardless of where it may reside.

As VMs proliferate, and data continues to grow dramatically in both volume and complexity, your best defense really is a good offense. Take this crash course in virtualization and data management, to learn how to better leverage and protect your data. It presents five essential data management and recovery lessons for your virtualized workloads.

Put these lessons to use and you’ll reap the benefits of more consistent policy management, better VM forecasting, freedom from vendor lock-in, and greater ability to meet your SLAs, consistently and uniformly.

Simplifying Data Management for Virtualized Workloads Across Private, Public, and Hybrid Clouds

Simply stated, virtualized workloads rule the data world. Trend forecasts estimate that, by 2021, a full 94 percent of all workloads will be running in a virtualized environment.1 The move to the cloud – public or private – is a key driver in this shift to how enterprises run workloads.

As Enterprise Strategy Group notes, enterprises are “accelerating virtualization adoption to deliver a cloud-like experience on premises.”2

Organizations need a solution that can manage and recover data across these mixed virtual environments – whether in the cloud or on premises. IT and VM administrators need to be proactive, examining whether their current toolset will enable them to seamlessly extend to an all-virtualized environment that can be further extended to cloud, while still supporting new workloads.

Where do you start when evaluating your current support of virtualized workloads? A first step is to take this crash course and learn these five essential data management and recovery lessons for your virtualized workloads. These lessons will help you identify areas of concern, raise questions about forecasting needs, prompt you to think again about scalability, and overall, provide you with a takeaway list of areas in which you can make improvements to execute more powerful and consistent VM data management.

Lesson 1 – Define Policy-Based Rules Once.

How can you meet your basic RPOs, RTOs, and recovery SLAs in this complex hybrid environment? Siloed data, in this regard, is not your friend. Your data management solution should allow you to define your policy-based rules once, then automatically detect new workloads and assign them to the correct protection policy based on rules that you set; rules that follow your data regardless of location. This would include policies on the front end that follow the data around, regardless of where it moves; along with policies on the back end that make the necessary copies of data for recovery, operational, or archive purposes; as well as policies related to governance and compliance.

Lesson 2 – Accurately Manage and Forecast VM Requirements.

To control your expenditures, it’s imperative that you carefully forecast your VM resource needs and identify exactly where new virtualized workloads can best be optimized. VMs that contribute critical business value are, of course, a valid budget line item. On the other hand, new VMs may – or may not – be valid budget items. Before a department puts in a requisition order for any new VMs, be sure to determine whether any VMs no longer in department use have actually been decommissioned. In a perfect world, your data management software solution should be able to “see” these virtual machines that have been sitting idle, and can automatically kick-off a customizable, policy-driven process that can help you eliminate VM sprawl.

Lesson 3 – Enable Scalability and Vendor Choice.

IT managers want to be able to scale virtualized workloads as needed. They don’t want to be locked in to a particular vendor agreement or be limited to a specific type of hypervisor or cloud that can be used for a specific workload or application. Being agile, watching your budget, and having the freedom to make the most effective performance choices is an effective roadmap for bringing greater business value to your organization.

Look at your current data management solution and ask yourself these three questions:

  • Can you easily scale-up VMs to meet your future needs with minimal disruption?
  • Does your solution integrate with a wide range of hypervisors and clouds, and allow you to seamlessly move workloads around as needed?
  • Are you able - without changing your data management tools - to select the best vendor solutions, for storage, servers, and virtual/cloud infrastructure, both now and in the future?

If you answer ‘no’ to any of these, your virtualization support will be less agile and will most likely be more costly than necessary, chipping away at the full value of your virtualization initiatives.

"A multi-cloud strategy is becoming more commonplace across a variety of organizations, regardless of the industry. Complications around vendor lock-in, data sovereignty, innovation and the need for workload-specific services are driving organizations to leverage multiple clouds to achieve business success."

VMware Research
After Deployment Storms, Skies Turn Sunny for Multi-Cloud Environments, 2017

Lesson 4 – Meet SLAs with Consistency.

Achieving your SLAs across on premises, cloud, and hybrid virtual environments can be a daunting task, especially given the fact that you may have multiple, siloed VM environments, and may be using standalone “point” tools – for backup, for DR, for compliance, for archiving, or for self-service. Attempting to manage your environment with multiple tools is, at best, inefficient, and can make it extremely difficult for you to consistently achieve your recovery SLAs.

A centrally managed solution that can support these heterogeneous environments will enable your IT staff to execute consistently on SLAs. Another important attribute is increased productivity: with a centrally managed solution you can quickly search and retrieve data across all of your protected data tiers and environments.

Lesson 5 – Operationalize Disaster Recovery (DR).

Similarly, you need a unified, centrally managed approach to DR that will enable you to consistently meet your recovery SLAs. This solution should support virtual, cloud, on premises, and hybrid environments, and be able to replicate and recover VM workloads and data to/from and across the cloud for secure, fast disaster recovery.

In any disaster recovery scenario, downtime and loss of productivity are always major concerns. To minimize downtime, having access to self-service recovery options allows your users to manage DR for their own data and workloads. But providing your users with self-serve flexibility doesn’t have to mean that you give up control over your replicated files. With customizable, role-based access controls that integrate with your directory security polices, you establish who has access to which data, combining convenience and efficiency with secure management oversight. With enormous workloads now the norm in most any enterprise, having access to self-service functionality is key to maintaining productivity, reducing stress on your IT resources, and effectively managing costs.

Look at your current DR approach and ask yourself:

  • Are your VMs protected with the appropriate SLAs (RPO and RTO), or are you simply replicating the top 10% and just backing-up the rest?
  • In the case of a DR situation, what is your level of confidence for recoverability of the required VMs and their applications?
  • Is your current DR approach costing you too much… in money, time, or aggravation?

Odds are, if you’re using multiple point solutions, and self-service recovery is not implemented and secure, your costs will increase, and recovery times will fall short of your SLAs.

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Lessons Learned

As you can see, these five essential lessons for your virtualized workloads will give you a head start in evaluating whether you still have work to do in optimizing the management and recovery of your data. To help simplify managing all that data and related workloads, you need a unified, purpose-built approach that can help you manage and protect your data across all your environments. Once that’s in place, you can provide your employees with the speed and flexibility of self-service recovery, to improve their productivity. And from a business value standpoint, you’ll be better able to manage your costs by setting consistent policies that can be easily executed through automation, while at the same time avoiding vendor lock-in.

  1. Cisco Global Cloud Index (2016-2021), February 2018
  2. Data Center Knowledge, This Wave of Data Center Consolidation is Different from the First One, February 2018
  3. Based on Commvault data analysis of Customers reporting their data storage usage type.
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