GigaOm Key Criteria for Evaluating Cloud Resource Optimization Solutionsv3.0

An Evaluation Guide for Technology Decision-Makers

Table of Contents

  1. Executive Summary
  2. Cloud Resource Optimization Sector Brief
  3. Decision Criteria Analysis
  4. Analyst’s Outlook
  5. About Matt Jallo

1. Executive Summary

Cloud resource optimization solutions provide a holistic view across an organization’s public or private cloud infrastructure. They deliver and provision resource configuration recommendations that balance cost, performance, and other objectives.

Before the rapid adoption of public cloud infrastructures, it was common for application teams to overprovision their virtual machine (VM) resource requests, since provisioning could take a long time and they had little insight into future requirements. IT operations teams could manage the cost and resource overprovisioning issues by overallocating their infrastructure, and did so often by an order of magnitude.

Organizations today provision many more cloud resources across public clouds. These services effectively offer the opportunity to pay only for what is needed and dynamically scale up or down as the need changes. This often presents challenges with cost and resource usage. The question of precisely how much is needed becomes relevant in a new way. Application teams still overprovision their cloud requests, while public clouds charge for exactly what is provisioned, which leads to waste. Sometimes this lack of diligence is just an old habit, but even with effective processes and controls, it can be difficult to safely and precisely predict runtime requirements by hand. Any degree of overprovisioning translates into a wasted expense, but when managed by hand, it would be imprudent to not leave a comfortable margin for safety. After all, availability or performance issues would ultimately impact the bottom line more profoundly than overspending on a safety margin for resources.

Application teams deploy many more systems than they used to, as the provisioning time is instantaneous, and there might be very little oversight of their spending for cloud resources. Modern software architecture demands greater subdivision of monolithic applications into microservices, and this multiplies the potential overhead expenses incurred by safe resource provisioning. Automating resource configuration is a clear solution to this problem because it assures users that their software can effectively scale to any level without spending a dime on unneeded resources. This would be anywhere from impractical to impossible to do by hand.

Business Imperative
As organizations continue to deploy cloud resources across multiple public and private clouds, each with potentially different resource monitoring solutions, they need solutions that can provide a holistic view across all cloud resources, which will identify resource configuration optimizations that balance performance and cost. This includes the need to make specific recommendations and potentially act on those recommendations without burdening operations engineers.

Cloud resource optimization solutions have been around for years and provide reliable and mature management of traditional IaaS (such as the dynamic provisioning and configuration of VMs). For large organizations that have migrated legacy software from private data centers, this continues to be the most relevant capability. As cloud-native software development proceeds, it is important that these solutions keep pace with evolving paradigms, such as containerized deployments, and platform as a service (PaaS) architectures, such as serverless APIs, which inherently provide a more solid foundation for scale. This year’s report will take a closer look at that evolution.

Sector Adoption Score
To help executives and decision-makers assess the potential impact and value of a cloud resource optimization solution deployment to the business, this GigaOm Key Criteria report provides a structured assessment of the sector across five factors: benefit, maturity, urgency, impact, and effort. By scoring each factor based on how strongly it compels or deters adoption of a cloud resource optimization solution, we provide an overall Sector Adoption Score (Figure 1) of 4.4 out of 5, with 5 indicating the strongest possible recommendation to adopt. This indicates that a cloud resource optimization solution is a credible candidate for deployment and worthy of thoughtful consideration.

The factors contributing to the Sector Adoption Score for cloud resource optimization are explained in more detail in the Sector Brief section that follows.

Key Criteria for Evaluating Cloud Resource Optimization Solutions

Sector Adoption Score







Figure 1. Sector Adoption Score for Cloud Resource Optimization

This is the third year that GigaOm has reported on the cloud resource optimization space in the context of our Key Criteria and Radar reports. This report builds on our previous analysis and considers how the market has evolved over the last year.

This GigaOm Key Criteria report highlights the capabilities (table stakes, key features, and emerging features) and nonfunctional requirements (business criteria) for selecting an effective cloud resource optimization solution. The companion GigaOm Radar report identifies vendors and products that excel in those decision criteria. Together, these reports provide an overview of the category and its underlying technology, identify leading cloud resource optimization offerings, and help decision-makers evaluate these solutions so they can make a more informed investment decision.


The GigaOm Key Criteria report provides a detailed decision framework for IT and executive leadership assessing enterprise technologies. Each report defines relevant functional and nonfunctional aspects of solutions in a sector. The Key Criteria report informs the GigaOm Radar report, which provides a forward-looking assessment of vendor solutions in the sector.

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