How to Add to Your IT Environment without Adding Costs

Part 2 of our 2-part series on Driving Efficiency through Infrastructure Optimization. Read Part 1 “Where to Find Cost Savings in Your Cloud or Data Center Environment

In the response to the current global crisis, short-term cost reductions have been prioritized by many  organizations looking to keep their businesses viable during the economic downturn.  Quite often they are looking to drive greater efficiency in their IT environments.

However, as organizations move from efficiency into recovery and beyond, the need to add new applications and workloads won’t disappear. It’s important for organizations to consider ways to optimize infrastructure to add new workloads while incurring minimal or no additional costs.

Why is this so important?  In the data center, 67% of organizations over-invest in data center storage while 33% have run out of capacity or experienced high utilization that impacted up-time (Source: Futurum Research). In the cloud, 60% of organizations have overspent their planned budgets at some point (Source: Rightscale).

Organizations that sustain efficiencies found in the short term will equip themselves to compete and thrive in recovery and beyond. This is where looking into the data center to find excess capacity and resources, tiering storage appropriately and choosing cloud over new servers all come into play.

Here are the steps you can take to optimize your infrastructure to add new workloads cost effectively by optimizing the on-premise data center and moving the right workloads into the cloud.

Optimizing Your On-Premise Data Center

As application workloads change, the optimal infrastructure setup to support them changes, too. When the time comes to add new applications to the IT environment, adding new hardware or spinning up new workloads in the cloud without a plan in place often results in unnecessary waste.

Instead, look for opportunities to optimize existing data center infrastructure to support new workloads without additional costs.

The following actions will help you understand your applications and ensure you have each running on the ideal compute and storage resources:

  • Take a comprehensive inventory: Use data collection tools to gather a holistic view of your existing on-premise environment, including devices and workloads. Capturing and analyzing current usage and performance data will uncover opportunities for greater efficiency. In turn, this data can inform your decisions about where to make changes based on accurate estimates of cost and business impact.
  • Consolidate the data center: Now is the time to assess the business value of owning multiple data center sites and whether there is an opportunity to consolidate these. Shutting down unnecessary sites and leveraging lower-cost cloud backup and disaster recovery could provide considerable infrastructure efficiency benefits.
  • Defer data center refresh costs: If you have hardware devices that have or are about to reach end-of-support (EOS) or end-of-life (EOL) and migrating to the cloud isn’t an option, a refresh may be unavoidable. Fortunately, many hardware providers have deferred some or all upfront costs until 2021 to help organizations through cash flow issues. It may also be worth considering other alternatives to an upfront capital expenditure, such as leasing or pay-per-usage options.

Migrating the Right Workloads to the Cloud

For many organizations, COVID-19 has put plans to migrate applications and workloads to the cloud on fast-forward. This has the potential to increase agility and cost efficiency by reducing technical debt and physical footprint associated with the traditional data center.

In fact, the Flexera State of the Cloud Report 2020 finds that more than half surveyed have seen increased cloud usage due to reliance on cloud-based applications since stay-at-home orders came into effect worldwide (Source: Flexera).

Reduced IT operations personnel, difficulties in accessing data center facilities and delays in hardware supply chains have all contributed to this shift.

Nonetheless, not every application or workload makes sense in the cloud. Furthermore, challenges in understanding application dependencies, assessing the feasibility of migration and predicting the costs to run a given workload on-premise versus in the cloud all get in the way.

The following steps will help you identify the best candidate workloads for cloud migration:

  • Assess suitability and identify migration risks: Analyze application, data and dependencies to determine the most suitable workloads for cloud migration and address potential performance and downtime risks.
  • Conduct total cost of ownership (TCO) and return on investment (ROI) analysis: Equipped with insights into applications, you’ll be able to define the infrastructure requirements to run applications in the cloud at optimal performance and cost.
  • Compare the cost-benefit of running each workload in the cloud vs. on-premise: The next step is to estimate the cost and business impact of running a given workload on-prem or in the cloud.
  • Plan and migrate: From here, you can determine the appropriate migration strategy to move workloads into the cloud with minimal risk. With complete and accurate documentation, you can establish the best migration sequence and apply dependency controls to avoid downtime.

Taking steps to optimize infrastructure and minimize the cost of adding new application workloads to your environment is a big milestone on the road to recovery.

We offer the following solutions to assist organizations like yours to move ahead with infrastructure optimization in the data center and migrate the right workloads to the cloud.

  • Workload Assessment: Evaluate the technical feasibility and cost of migrating and running application workloads in the public cloud based on usage, performance and technical characteristics of existing workloads to identify application dependencies, total cost of ownership and cost management considerations.
  • Public Cloud Accelerator: Leverage an operating expense (OPEX) model to meet new workload needs by reducing the risk of deploying workloads to the cloud and mitigating cost overruns based on proven experience earned through hundreds of cloud engagements.

Our team of licensing and technology vendor experts are ready to help you find efficiencies wherever you are in your journey from response to recovery.

Looking for further insights to help  drive efficiency and optimize the infrastructure in your IT environment? 

Watch our webinar, “Cloud Cost Optimization: How to Avoid Overspend and Control Costs,” on-demand or connect with an expert.

Getting Workload Placement Right – [Infographic]

Placing application workloads in the public cloud comes with a few key benefitsincluding ease of deployment, pay-per-use billing and scalability 

But as we discussed in our previous article, a “cloud-first for all new workloads” approach may be premature.  

Varying performance characteristicssecurity and compliance requirements mean some workloads are better suited to legacy or private cloud infrastructureFurthermore, the cost of modifying workloads for cloud-readiness and the expense involved in repatriating workloads from the public cloud both mean the workload placement decision deserves careful consideration.

In fact, without due consideration, “lifting and shifting” workloads into the public cloud can result in cost, complexity and performance issues that are difficult to predict.  We created this infographic to outline the key steps to getting the workload placement decision right the first time.  

Need help with your workload placement decisions?

The calculations that go into any workload placement decision must weigh technical and business needs. Assessing the performance demands, security and compliance restrictions and long-term business impact are all imperative before determining workload placement. At the same time, a hybrid or multicloud approach mixing public, private and on-premise infrastructure and services makes sense for many organizations. Learn more about the key considerations for multicloud strategy in our guide, Roadmap to Multicloud Success: Why Architecture Matters.  

Just beginning your cloud transition or looking to get more out of your existing cloud deployments? Check out this Forrester report, Top 10 Facts Tech Leaders Should Know About Cloud Migration or explore Softchoice cloud services 

 

 

 

Legacy vs. Cloud Environments: How to Determine Workload Placement

Imagine buying a home. Soon after you purchase, you discover that it has a hidden structural flaw – termite damage, black mold or crumbling clay-tile plumbing. This requires a very expensive fix. In that case, it may have been better to have not purchased the home at all, and instead found a place with fewer issues. 

 Similar situations can occur with cloud workload placement. In 2019, IDC noted the continued trend of reverse cloud migrations, which involve organizations moving workloads that had previously been placed in the cloud back into on-premises environments, often at great expense.  

IDC also estimated that by 2020, 75% of enterprises will also use a private cloud. The reasons include security and compliance, anticipated cost savings that failed to materialize and growing interest in hyper-converged infrastructure. Performing due diligence before a workload goes into the cloud is the best way to avoid the technical complications and potentially high costs of making such adjustments after the fact.  

 In this article, we’ll look at what steps to consider when deciding where to place a workload, so that you can make an informed choice that will provide the right combination of cloud performance and cost-effectiveness. Let’s go through them one by one, starting with what you need to discover during an initial hybrid IT assessment. 

What are the performance characteristics of the workloads in question?

By measuring each workload’s usage of CPU, memory, and networks, it’s possible to get a general sense of whether it would be a good candidate for the cloud. 

 For example, a highly variable workload such as an intermittently busy e-commerce site or student enrollment system would be ideal for public cloud placement. Because it doesn’t require a steady stream of IT resources, there’s no real reason to purchase and provide them in-house. You would only invest in copious amounts of memory and numerous CPUs that would occasionally be needed at full capacity. Apps with unpredictable demand area are also good cloud candidates for these same reasons. 

 In contrast, an application that sees constant demand will usually be better suited to legacy/on-prem deployment. Moving it to the cloud could result in major sticker shock, as its level of activity will accrue significant charges for all of the necessary public cloud services, including snapshots and bandwidth. 

Does the workload need any modifications before it’s placed in the cloud?

Most of the time, the answer to this question is “yes.” We estimate that at least 80% of workloads require some adjustments before they’re cloud-ready. Sending a legacy workload as-is into a public cloud is typically a recipe for subpar performance and potentially a reverse migration. 

Porting an on-prem workload into a cloud-optimized version is a multi-step process, often requiring: 

  • Applying relevant patches and security upgrades. 
  • Assessing all of its security contingencies, e.g. with HIPAA, GDPR, etc. 
  • Identifying the workload’s dependencies on specific pieces of infrastructure. 
  • Updating or rewriting it for a different OS or framework. 
  • Placing it into a container for increased portability. 

It’s also possible that after performing deeper analysis using versioning tools, you’ll discover that a workload isn’t suitable for a public cloud environment. This could be because of its performance characteristics. Or, because there is a lack of support for its requirements. For example, the decision to port an application to the cloud may not ensure passage of a regulatory audit. The result would require you to know the exact locations of application data and prevent any unauthorized access. 

 If a workload isn’t cloud-ready or even cloud-suitable, it should be left in place and perhaps revisited later on to see if the situation has changed or if it could be replaced by SaaS.

Would a hybrid cloud that extends the current environment make sense for the workload?

 Using multiple clouds is fast becoming the norm. In 2019, RightScale found that most enterprises had a multicloud strategy in place and that the share of businesses combining public and private cloud deployments rose from 51% in 2018 to 58% 

 A hybrid cloud can sometimes provide the right balance of control and performance for workloads that are being migrated from a legacy environment. Solutions such as VMware on AWS allow current data center processes and tools to be copied over into a cloud environment.  

 Moving to this type of hybrid platform requires no sweeping changes. At the same time, it opens the door to additional services for security and disaster recovery. A hybrid cloud ultimately allows for more streamlined data center operations in support of key workflows such as devtest. 

What is the business impact of migrating this workload to the cloud? 

Without getting into all of the technical details discussed above, a workload’s suitability for the cloud can be evaluated based on how its migration would affect the organization as a whole. For instance, how would it change the day-to-day experience of its end users? 

 Keeping a workload in a single main data center might actually degrade its performance, due to it being centralized in a location that’s physically quite far from some branch sites. Also, single-site deployments are at higher risk from disasters, since all the eggs are in the same technical basket.   

 Consider what it would be like to have the bulk of your employees or customers in Seattle while your data center was in New York City. That distance would materially affect workload performance, plus any failure would immediately put you in a bind. The rise of the Internet of Things and the corresponding need to backhaul more data with less latency shows how difficult it will be to maintain certain data center setups going forward. 

 Shifting more of these sorts of workloads into the cloud might provide some much-needed redundancy and greater geographical distribution. However, there are some different physical limitations that could come into play. A workload that runs on system memory and flash storage in a data center might theoretically be public cloud-able, but it wouldn’t perform exactly the same way once there. 

How to make the best decision about workload placement 

We’ve covered some of the biggest considerations for placing workloads, but there are others that will inevitably enter the picture. Looking to learn more about the challenges of cloud migration? Check out this Forrester report, 10 Facts Tech Leaders Should Know About Cloud Migration.

Softchoice can help you navigate them en route to making the best possible choices for your environment. Learn more by contacting our team or explore Softchoice cloud services.