Gartner Insight on What Dynamic Optimization Technology Is, And Why Should You Care?

Rachel Dines
Sr. Director of Product Marketing
Apr. 28, 2016
3 minute read

The content in this blog is outdated and we cannot reliably say it is still accurate with the speed in which the cloud industry moves. But don’t worry—below are more recent, up-to-date blogs.

What Does Cloud Efficiency Mean To You?

The CloudHealth Guide To AWS Cost And Usage Reports

How To Best Manage Cloud Financial Reports

Early adopters of the public cloud set out in search of cost savings, time savings, and overall efficiency gains. What they quickly learned, was that simply migrating infrastructure to the cloud and operating it as they did on-premises did not lead to the benefits they expected. Specifically, they ran into challenges around cloud sprawl, poor utilization, lack of governance, and complexity on a scale beyond human control. Gartner put it best when they wrote:

“Cloud computing adoption, in particular, is moving so fast that there is a requirement for greater automation such that decentralized teams can develop new software and services with policies enforced dynamically and transparently at provisioning time, during runtime and when reprovisioned.”

Gartner, Innovation Insight for Dynamic Optimization Technology for Infrastructure Resources and Cloud Services, Donna Scott and Milind Govekar, 29 February 2016

The most mature organizations started looking for ways to manage, automate, and govern their cloud environments, and thus, a new type of tools called dynamic optimization technologies were born. Gartner recently wrote an excellent Innovation Insight report that gives an overview of dynamic optimization technologies which they define as:

“Dynamic optimization technology for resources and cloud service is a technology capability that uses telemetry, algorithms, service and resource analytics, and policies to drive automated actions that reduce waste, cost and risk exposure, while simultaneously improving service levels. These technologies help reduce cloud service and virtual infrastructure sprawl and cost, while improving governance and compliance.”

Gartner, Innovation Insight for Dynamic Optimization Technology for Infrastructure Resources and Cloud Services, Donna Scott and Milind Govekar, 29 February 2016

In other words, dynamic optimization technologies turn big data analytics inwards to help contain costs, free up employee time, and maintain control over their cloud infrastructure. This can be a standalone technology, or purchased as part of cloud service management platforms like CloudHealth.

CloudHealth Technologies is listed as a representative provider in the report with a focus on the public cloud. Gartner outlines 3 common use-cases for dynamic optimization technologies in the report:

  • Dynamic placement and provisioning of cloud services. We feel this means that with so many different public and private cloud options available today, many companies struggle with decided where to place new services. Dynamic provisioning helps customers deploy the right workloads in the right public, private, or hybrid cloud solution. Typically this would be determined by requirements around performance, compliance, or latency.

How does CloudHealth help? Today, CloudHealth cannot provision new cloud services on your behalf, but the platform can make recommendations around rightsizing instances and model out cloud costs for on-premises infrastructure.

  • Event stream processing with dynamic policy enforcement. We believe battling shadow IT is one of the constant struggles in organizations large and small, and cloud services make this problem more acute with decentralized management and provisioning. Dynamic policy enforcement helps companies centralize and control governance, budget, or security policies, even after they have been deployed.

How does CloudHealth help? For example, many CloudHealth customers use this feature to ensure users deploy instances with proper tagging, or set a budget for an individual or a department.

  • Dynamic service and resource optimization. As the early adopters learned, in order to get the full benefit of the public cloud, we believe it’s critical to continuously optimize your environment in real time. Unlike in the data center where change is slow and many assets are static, assets in the cloud are dynamic. Dynamic service and resource optimization continuously evaluates your cloud assets and makes recommendations (or proactively makes changes) as to how to improve utilization and efficiency.

How does CloudHealth help? Many CloudHealth users rely on this feature to monitoring for unattached/unused storage volumes, purchasing or reallocating reserved instances, or scaling up or down CPU and memory allocations.

If you are heavily invested in using the public cloud, or are considering moving towards a cloud-first strategy, it’s critical that you get ahead of cloud optimization now before it spirals out of control. As Gartner says:

“I&O leaders, CSBs and IT finance must invest in dynamic optimization technology as they increase their adoption of cloud services to ensure policy enforcement on provisioning, but also post provisioning to best balance SLAs, costs and risks.”

Gartner, Innovation Insight for Dynamic Optimization Technology for Infrastructure Resources and Cloud Services, Donna Scott and Milind Govekar, 29 February 2016

Let leading dynamic optimization providers like CloudHealth help automate your cloud environment so you can innovate faster without sacrificing governance or control. Try CloudHealth risk free today.