Gartner Research

Solution Comparison for Public Cloud Third-Party Cost Optimization Tools

Published: 10 December 2019


To increase efficiency of public cloud IaaS and PaaS, I&O technical professionals must employ tools to continuously and programmatically optimize cloud spend. This research assesses and compares the capabilities of five common third-party tools for public cloud cost optimization.


Key Findings
  • Solutions that focus only on cost management and resource optimization have deeper capabilities than those that aspire to cover multiple areas of management.

  • Vendors are inconsistent about what they consider essential capabilities for cost optimization. Some vendors chose to first implement more advanced functions at the expense of those that Gartner considers indispensable for enterprise organizations.

  • All vendors provide functionality to identify spending waste and pursue cost optimization opportunities. However, few vendors have moved beyond recommendations to providing execution and automation capabilities.

  • The only public cloud platforms supported by the assessed vendors are AWS, Microsoft Azure and GCP. Some vendors extend their capabilities to on-premises environments. However, feature parity among supported platforms is often limited and difficult to assess.


Technical professionals in charge of selecting cost optimization solutions for infrastructure, operations and cloud management should:

  • Implement public cloud cost optimization with cloud provider’s native tools first. Identify functionality gaps and address them with third-party tools.

  • Prioritize your requirements and adopt solutions that focus on cost optimization if you need to maximize savings while ensuring performance. Conversely, choose solutions that provide broader functionality if you need to minimize the number of cloud management tools in use.

  • Prioritize vendors that provide sophisticated analytics that ensure high-quality insights. The ability to consume large amount of data to find the right opportunities to pursue is the core value of cost optimization tools.

  • Scrutinize the solution’s capabilities for the cloud platforms you use. Plan for multicloud, and prioritize solutions with higher feature parity between platforms.

Solution Comparison

Many organizations approach procurement of cloud infrastructure as a service (IaaS) and platform as a service (PaaS) with the same buying habits they use within data centers. They buy servers and storage resources that are bigger than needed based on growth expectations that may or may not materialize. Services are often left running all the time, irrespective of actual utilization. This behavior generates spending waste — which can reach up to 70% in the first 18 months, according to Gartner’s estimate— that organizations must learn how to manage on an ongoing basis.

In addition, the ease of procuring public cloud services via web interfaces and APIs in the absence of capacity constraints can compound this spending waste. At the same time, cloud providers continue to innovate, providing new configuration options and pricing models that, if properly leveraged, can drive significant cost reductions.

To contain spending waste and pursue opportunities to lower costs, organizations must implement continuous cost optimization processes. Cost optimization requires visibility of metrics on the utilization, performance and cost of cloud services. The large number of these metrics makes it difficult for organizations to gain insights into the actions that can minimize spend while keeping sufficient performance. For example, the price list of just one service (Amazon Elastic Compute Cloud [EC2]) in just one region (us-east-1) provides more than 1,350,000 entries that organizations must learn and manage. Therefore, to drive such a process at scale, organizations must use analytics tools that can extract insights from large amounts of data.

Organizations will find many tools on the market that claim to deliver significant reductions of public cloud bills. Cost optimization is indeed becoming “table stakes” within the cloud management market. Large software vendors, traditional cloud management platforms (CMPs), new point software solutions and even cloud providers promise organizations compelling ROIs by driving cloud spend down with little investment. However, I&O professionals often wonder: which tool will allow us to achieve maximum cost savings without affecting workload performance?

This Solution Comparison assesses and compares the capabilities of public cloud cost optimization tools that are built and commercialized by third-party vendors. This document focuses on the following five vendors and solutions, which Gartner selected based on volume of Gartner client interest measured over the last 12 months (in alphabetical order):

  • Apptio (Cloud Business Management and Cloudability)

  • CloudCheckr

  • Flexera (Flexera Optima)

  • Turbonomic (Turbonomic Platform and ParkMyCloud)

  • VMware (CloudHealth by VMware and vRealize Operations)

Cloud providers also provide some cost optimization capabilities, which organizations should assess first before jumping into the selection of a third-party tool. To assess and compare the native cost optimization capabilities of major cloud providers, see

Cost optimization is just a part of the overall cost management discipline that organizations must develop as part of their cloud adoption framework. Cost management also includes areas such as cost comparison, forecasting, budgeting, tracking, allocation, reporting and anomaly detection. Other areas of cost management beyond optimization are out of scope of this report. Organizations can refer to for comprehensive research on cloud cost management. Furthermore, organizations can see how cost optimization is key to making cloud services cost-effective and cheaper than data centers in

This Solution Comparison is based on a Gartner-defined set of criteria grouped in the following main categories:

  • Rightsizing: Functionality to provide for the adjustment of provisioned capacity for cloud resources such as compute instances or cloud services nodes (such as database or caching nodes) to match observed utilization.

  • Resource decommissioning: Functionality to provide for the termination or suspension of unused resources such as idle compute instances or unattached storage volumes.

  • Multicloud capabilities: The amount of functionality that solutions provide on top of the main cloud platforms, namely Amazon Web Services (AWS), Google Cloud Platform (GCP) and Microsoft Azure, and on-premises stacks.

This assessment was conducted on features and capabilities as of September 2019. For a detailed description of the criteria used for this assessment, see the Methodology and Criteria section.

Figure 1 provides a summary of the comparison of the assessed offerings. The scores are based on a Gartner-defined scale with values of “High,” “Medium,” “Low” or “None,” where “High” is best. Note that “None” means that the provider does not meet the minimum requirements to get a “Low,” but it may still provide some functionality in that area, although not sufficient to qualify for scoring.

This comparison summary shows that the cost optimization market still has many unexplored areas. The vendors that achieve the best scores are those that focused exclusively on optimization (such as Turbonomic) or those that provide functionality through multiple products (such as Apptio and VMware).

Most vendors have developed good functionality to identify cost optimization opportunities. However, the lower scores have been determined by the lack of configurability of the policy that drives the identification of spending waste, by the lack of displaying the analysis of cost implications or by the lack of automation. This result is probably due to:

  • The low maturity of the cost optimization market: Many vendors are still exploring this space and building up functionality based on their customers’ demand.

  • The broader focus beyond cost optimization: Many of the assessed vendors provide other cloud management functions through the same software.

  • The lack of requirements from client organizations for full optimization automation: Gartner inquiries show that the majority of organizations don’t trust cloud cost optimization tools enough to aim at automating the recommendation execution. This may change in future, but it may have caused vendors to deprioritize automation capabilities.

  • The alternative and potentially “good enough” cost optimization functionality provided by cloud providers (see )

All vendors provide cost optimization beyond compute instances, specifically for software infrastructure services such as database, caching or container orchestration services. However, compute instance capabilities are usually more sophisticated than those for software infrastructure services. Block storage rightsizing capabilities are extremely limited across all vendors. Lastly, only one vendor (Flexera) provides capabilities for object storage optimization.

Most vendors have shown significant feature disparity among the supported cloud platforms. The degree of parity shows how consistent a vendor has been in building its optimization functionality for multiple cloud platforms. Flexera and Turbonomic have shown the highest degree of parity, and Flexera is the only vendor that has significantly invested in GCP.

Only Turbonomic and VMware provide strong support for on-premises cloud platform, and this doesn’t come as a surprise given their data center heritage. Although Apptio has traditionally provided software for on-premises cost management, its data center optimization capabilities are limited.

The Additional Guidance section details best practices and provides recommendations for the vendor selection process. The Solution Assessments section provides a detailed explanation of the scores each vendor receives in Figure 1. For a detailed description of the criteria and the scoring methodology, see the Methodology and Criteria section.

Solution Assessments


Apptio is a vendor in the IT financial management (ITFM) space (see Note 1). Two years after going public, Apptio was acquired and taken private by private equity firm Vista Equity Partners in November 2018. Apptio started to offer public cloud cost management capabilities with its acquisition of FittedCloud in October 2018 and, later, of Cloudability in May 2019. The intellectual property (IP) brought by the two acquisitions provided Apptio some degree of overlap.

FittedCloud was rebranded as Apptio Cloud Business Management (CBM). Since the acquisition of Cloudability, CBM is not represented in the vendor’s marketing website, and it is no longer the Apptio’s primary public cloud cost optimization solution. However, Apptio still provides CBM to clients requiring Federal Risk and Authorization Management Program (FedRAMP) certification. Apptio continues to support all existing CBM customers.

Cloudability is now Apptio Cloudability, and Apptio offers it as a stand-alone solution. Cloudability will be Apptio’s main public cloud cost optimization product going forward, and it will receive the majority of the investments. Apptio also plans to migrate all features of CBM into Cloudability. However, at the time of the writing, the two products have no common data model or UI consistency, and customers need to deal with two separate experiences. Cloudability and CBM are both delivered as SaaS.

In addition, Apptio offers Hybrid Business Management (HBM) as overarching product name that encompasses Cloudability in addition to on-premises resource optimization capabilities. This assessment is based on both CBM and Cloudability. The detailed scoring table (Table 1) clearly indicates which of the two product’s functionality contributes to the attained scores.

  • The combination of Cloudability and CBM presents a large breadth of functions, which allows Apptio to provide at least the minimum requirements in every area of cost optimization considered in this assessment except object storage optimization.

  • Apptio provides more transparency than other solutions assessed on how it achieves certain functionality such as rightsizing or reservation purchase management. Public blogs and articles showcase the complex decision framework that allows Cloudability to produce high-quality recommendations.

  • Apptio provides an array of widely adopted ITFM tools. Organizations selecting Apptio can count on a vendor with significant experience in managing the costs of IT and their business implications.

  • Organizations that already use Apptio for managing their IT financials can easily extend their use to embrace public cloud cost management. Apptio’s strategic acquisitions allowed the vendor to quickly ramp up its public cloud cost management functionality and make it comparable to other leading vendors in this space.

  • Apptio provides multiple solutions with a high degree of overlap. Despite Apptio’s direction being clearly focused on Cloudability, it will take some time before the vendor can effectively incorporate the CBM functionality within Cloudability and supply its customers with a single comprehensive solution. Furthermore, history shows that, post-acquisition, vendors direct their investment to the integration efforts and away from building new features to keep their product competitive. History also show that some functionality may be eventually left behind when it is difficult to integrate. Therefore, there is no guarantee that Apptio will preserve all functionality of both solutions once the integration is completed.

  • Apptio provides strong support for AWS but only minimal support for Microsoft Azure, GCP and on-premises stacks. This makes the multicloud management value proposition of Apptio weaker than vendors with higher feature parity between cloud platforms.

  • Apptio provides no public documentation for CBM, making it difficult for its customers to research and assess its features. Furthermore, CBM is no longer represented within Apptio’s marketing website. Despite the product having significantly contributed to the scores in this assessment, the vendor actively sells it only in limited scenarios (specifically, only where FedRAMP certification is required). As a consequence, the majority of customers may not be able to buy CBM functionality until the integration with Cloudability is completed.

  • Apptio Cloudability offers minimal configuration options to customize the policies that power the recommendation engine. Although the built-in policies are certainly applicable to the majority of use cases, customer organizations would benefit from a higher degree of configurability to handle exceptions and minimize false positives.


CloudCheckr is a cloud management vendor focused on cloud cost management and cloud security. The company was founded in 2011 and has raised almost $70 million to date with the latest round in August 2019 (Series B) primarily from private equity firm Level Equity.

CloudCheckr started as a cloud security product and expanded into cost management in a later stage. At the time of this writing, the vendor provides all of its functionality in a single product. The product spans cost tracking, optimization, resource inventory, security and compliance for public cloud platforms. The vendor has also added specific capabilities to help service providers with their public cloud managed services business. The CloudCheckr product is delivered as SaaS.

This assessment is based on the CloudCheckr product.

  • CloudCheckr provides advanced functionality for decommissioning old Amazon EBS snapshots. The functionality meets all requirements of the “old snapshot decommissioning” criterion except for the indication of estimated savings. However, customers can find cost information for each existing snapshot in the product’s inventory report.

  • CloudCheckr provides strong support for reservation portfolio management. Its RI “rebalancer” provides actionable recommendations on how to modify existing AWS reservation to maximize coverage and minimize waste.

  • CloudCheckr’s utilization heatmap for compute instances helps organizations visually identify utilization patterns and use those patterns to plan for scheduled shutdowns. However, CloudCheckr doesn’t provide recommendations for how to implement schedules.

  • CloudCheckr is a cloud management tool that goes beyond cost management. CloudCheckr provides more than out-of-the-box 500 best practices for cost and security concerns. This large number allows customers to quickly get their cloud deployments in control with minimal configuration burden. Its security capabilities allow customers to use the same tool to also enforce a security baseline and manage broader cloud governance, especially where cost and security intersect. This makes CloudCheckr a good choice for organizations that prioritize minimizing the number of management tools.

  • CloudCheckr scores low in the majority of the assessment criteria except for old snapshot decommissioning and reservation portfolio management (both features are available only for AWS). The majority of its cost optimization functionality is basic and fails to provide the depth that organizations require to maximize savings while preserving performance. CloudCheckr’s breadth of features, even beyond cost optimization, seems to be traded with lower depth in the cost optimization space.

  • CloudCheckr’s approach to policy-based management focuses primarily on reporting issues rather than solutions. With the exception of its rightsizing and snapshot cleanup functionality, CloudCheckr’s “best practice checks” do not include the indication of the recommended actions that customers should undertake to address the issues. This approach does not allow CloudCheckr to meet the minimum requirements in some of the criteria in this assessment.

  • CloudCheckr does not provide any cost optimization capability for GCP or on-premises cloud platforms. Organizations should not select CloudCheckr if either of these is their primary cloud platform.

  • CloudCheckr’s public documentation has proven to be incomplete. Specifically, most of the documentation for Azure-specific capabilities is missing. Only a few pages mention the availability of certain functions for Azure, but they do not provide any detail. This lack of documentation makes it difficult for organization to assess the available functionality prior to the adoption of the tool.


Flexera is a leading vendor in the software asset management (SAM) space. Flexera was founded in 2008 and was acquired by private equity firm TA Associates in September 2017.

Flexera started to offer public cloud cost management capabilities with its acquisition of RightScale in September 2018. RightScale provided a policy engine as part of its CMP offering and cost management capabilities as part of the Optima solution. Optima initially focused on using collaboration — rather than automation — to drive cloud spend down. At the time of writing, Flexera provides cloud cost management through the Flexera Optima brand. Flexera Optima is delivered as SaaS.

This assessment is based on Flexera Optima.

  • Flexera Optima is highly programmable and provides a proprietary policy language that customers can use to extend the product’s functionality. This extensibility comes with a comprehensive developer’s guide that makes developing extensions an approachable task. This capability allows client organizations to potentially support a larger set of cloud services than those included by default, without having to wait on Flexera to do that.

  • Flexera Optima provides great feature parity among supported cloud platforms. Flexera is the only vendor that scores “High” for AWS, Microsoft Azure and GCP support. Furthermore, it is the only vendor that supports cost optimization for GCP for more than 75% of its functionality.

  • Flexera is the leading vendor within the SAM space, according to Before the acquisition, RightScale was the leading vendor in the CMP space, according to The combination of two vendors that know how to establish leadership positions can certainly increase confidence in the resulting organization. Furthermore, Flexera’s latest acquisition of RISC Networks in June 2019 and the addition of cloud migration functionality has further enhanced the vendor’s cloud management portfolio. This makes Flexera a good choice for organizations that want to minimize the number of vendors in their cloud management strategy.

  • Flexera Optima’s documentation is excellent. It provides a dedicated documentation website that is comprehensive, well-organized and easy to navigate. Customers can easily find the information they need to assess product features or to learn how to operate the solution.

  • Flexera Optima does not provide the analysis of cost implications for most of its recommendations (with the exception of unused Amazon EBS volumes). Information such as estimated savings or additional expenditure is fundamental to help organizations decide whether to act on the suggested actions. Most of the criteria used in this assessment require the indication of estimated savings to allow a vendor to earn a “Medium” score.

  • The provided cost optimization policies are just a handful, and not all of them include the ability to execute on recommendations. Many of the criteria within this assessment could be met by developing the required code, but this effort is left to the customer. This is possibly due to the vendor’s initial strategy of providing Flexera Optima in conjunction with professional services.

  • Flexera Optima does not provide any reservation-related recommendation. Its reservation policies simply retrieve recommendations from AWS and Microsoft Azure and native cost optimization tools. With such an approach, it is the cloud provider that evaluates resource utilization and produces insights, while Flexera Optima simply retrieves and aggregates this information.

  • Flexera lacks functionality such as rightsizing of block storage volumes or software infrastructure services other than databases. Client organizations can implement such functionality only through the development of a custom policy.


Turbonomic is an IT management vendor focused on resource optimization. The company was founded in 2008 and has raised almost $150 million to date with the latest round in January 2017 (Series E) from investors including venture capital and growth equity firms.

Turbonomic was formerly known as VMTurbo and rebranded to its current name in August 2016.VMTurbo provided software to increase efficiency of data centers while preserving quality of service. Turbonomic extended its optimization functionality to public cloud services to achieve continuous cost optimization. The vendor provides a single platform that includes its legacy data center capabilities as well as new functions for public cloud. The Turbonomic Platform is delivered both as SaaS and as packaged software to be installed on customer’s managed infrastructure.

In addition, Turbonomic acquired ParkMyCloud in May 2019 to add cloud resource scheduling capabilities. Turbonomic currently offers ParkMyCloud as a stand-alone product. ParkMyCloud is delivered as SaaS.

This assessment is based on both the Turbonomic Platform and ParkMyCloud. The detailed scoring table (Table 5) clearly indicates which of the two product’s functionality contributes to the attained scores.

  • Turbonomic automation capabilities are superior to most of the other vendors assessed. Customers can automate the execution of recommended actions either directly or through an integration with external orchestration tools such as Ansible, ServiceNow (for reservation purchase approvals) or Terraform.

  • Turbonomic is the only vendor that provides feature parity between some public cloud platforms (namely AWS and Microsoft Azure) and on-premises environments through the same tool. However, this parity doesn’t apply to GCP, and it excludes the resource scheduling capabilities provided by ParkMyCloud.

  • Turbonomic is very focused on the mission of providing automated application resource management. For Turbonomic, cost optimization is just a benefit of the perfect alignment between infrastructure resource supply and performance requirements. This focus allows Turbonomic to achieve excellence in what it does and earn the highest score in some of this assessment’s criteria.

  • ParkMyCloud provides the most advanced resource scheduling capabilities. The acquisition of ParkMyCloud allowed Turbonomic to grow its functionality in line with its philosophy of staying focused on a few key areas and achieving excellence in each of them.

  • Turbonomic does not address some important areas of cost optimization. It does not address the decommissioning of unused resources other than compute instances and storage volumes. For example, it does not provide recommendations to decommission unused database services, load balancers, IP addresses or old snapshots.

  • Turbonomic does not provide reservation portfolio management. When using reservations, customers must continually evaluate their reservation coverage and change modifiable attributes, such as reserved allocation size, to maximize coverage and minimize waste. Turbonomic does not provide functionality to assess coverage and modify or exchange purchased reservations.

  • Turbonomic’s support for GCP is minimal. Although ParkMyCloud fully supports GCP for resource scheduling, the Turbonomic Platform provides minimal cost optimization for GCP. Specifically, the platform provides rightsizing and decommissioning for GKE clusters, as part of the platform’s functionality for Kubernetes and container management.

  • Turbonomic does not go beyond resource optimization. It does not address broader aspects of cost management such as budgeting, tracking or reporting. When using Turbonomic, organizations need to adopt other tools to address all of their cost management requirements.


VMware is a leading vendor in IT infrastructure and management software. VMware has historically provided some public cloud management capabilities as part of its vRealize Suite. However, the vendor started to provide significant functionality for public cloud cost management only since its acquisition of CloudHealth Technologies in August 2018.

VMware continues to offer public cloud cost management through the CloudHealth brand. CloudHealth is offered as SaaS. In addition, VMware provides resource optimization for on-premises environments through vRealize Operations. CloudHealth and vRealize Operations are only minimally integrated. The two products have separate identity management, data models and user interfaces. To achieve full automation, vRealize Operations requires an additional “Management Pack” that must be acquired separately. vRealize Operations is delivered as packaged software to be installed on customer’s managed infrastructure.

Some Gartner client organizations have expressed concerns over the vested interest that VMware may have in keeping its customers on-premises. Clients are concerned that VMware could use CloudHealth to show cost data that would drive decisions against the use of public cloud services. Although this concern is legitimate, one year after the acquisition, Gartner found no evidence of that.

This assessment is based on both CloudHealth and vRealize Operations. The detailed scoring table (Table 5) clearly indicates which of the two product’s functionality contributes to the attained scores. However, the methodology in use requires that the vendor provide functionality on at least one public cloud provider in order to consider it also for on-premises environments. As a consequence, vRealize Operations capabilities that exceed those of CloudHealth have not been considered in this assessment. For example, vRealize Operations’ upsizing recommendations for on-premises virtual machines did not contribute to the score calculation because CloudHealth does not provide upsizing recommendation for any public cloud provider. For more details on the methodology in use, see the Methodology and Criteria section.

  • CloudHealth’s new rightsizing engine provides a highly configurable policy that customers can use to define an “efficiency target.” At the time of writing, CloudHealth uses this new engine only for Microsoft Azure SQL Database rightsizing. However, the vendor expects to extend it to all supported resource types in the near future.

  • CloudHealth excels in reservation purchase and portfolio management for AWS, meeting all the requirements in this assessment. AWS clients using CloudHealth can count on mature functionality to suggest purchase and subsequent ongoing management of reservations.

  • VMware provides strong resource optimization for on-premises environments through vRealize Operations. Sometimes, like in the case of compute instance rightsizing, vRealize Operations exceeds the capabilities that CloudHealth provides for public cloud services.

  • Between internal development and acquisitions, VMware has built a broad portfolio of public cloud management tools. Customers can select CloudHealth for cost management in addition to Secure State (cloud security), Cloud Assembly (provisioning and orchestration), Code Stream (continuous integration/continuous delivery [CI/CD]) and Service Broker (service request management). This makes VMware a good choice for organizations that want to minimize the number of vendors in their cloud management strategies.

  • CloudHealth provides uneven breadth of functionality for each supported public cloud platform. Although support for AWS is strong, with nearly all functionality available, less than 75% of its functionality is available for Microsoft Azure. Furthermore, some functionality available for Microsoft Azure is not available for AWS (such as database as a service rightsizing). Cost optimization support for GCP is negligible. Such uneven support makes the multicloud management value proposition of VMware weaker than vendors with higher feature parity between cloud platforms.

  • CloudHealth’s built-in actions that execute and automate optimization opportunities are limited. Missing actions include the ability to change size for storage volumes and the ability to change size or decommission software infrastructure services such as databases. Furthermore, the list of available actions differs significantly for each supported cloud platform.

  • CloudHealth does not provide resource scheduling recommendations. Although it does provide a scheduling engine, it’s up to the user to decide which schedules to apply to which resource, and CloudHealth provides no help with this decision.

  • VMware provides on-premises resource optimization through a separate product (vRealize Operations), which is only minimally integrated with CloudHealth. The two products have separate identity management, data models and user interfaces. The only available integration allows vRealize Operations to visualize dashboards by pulling data from CloudHealth. As a consequence, organizations that want a hybrid cost management solution through a single vendor still have to deal with two separate tools.

Additional Guidance

Buy, Don’t Build

Gartner recommends against building your own cost optimization tools due to the high complexity that goes with it. You can easily get overwhelmed by the number of metrics available from cloud providers and the number of rules that you will need to define and enforce. The current technology trends show that the available data will just continue to increase, as will the configuration and pricing options to choose from when procuring cloud services. Furthermore, besides the cost of development and maintenance, there are additional costs for all the optimization opportunities that you wouldn’t be able to pursue due to the low maturity of your tooling.

Organizations may aim to succeed in a do it yourself (DIY) cost optimization project only if they keep the scope of functionality extremely small. In all other cases, Gartner recommends buying cost optimization functions from cloud providers and software vendors. These vendors have built software for years and tested it across many deployments, allowing you to achieve higher efficiency in shorter time and at lower cost.

Use Native Capabilities First, Fill the Gaps With Third-Party Tools

Cloud providers continue to develop their portfolio of management tools. These native tools are available as part of the cloud service subscriptions and, as a consequence, don’t require potentially complex deployments. However, they typically support only one cloud platform, and some of them are overly simplified and may lack functionality.

In accordance to Gartner’s guidance on selecting cloud management tools, organizations should first try to address their management requirements using the cloud provider’s native tools. This approach gives organizations faster access to management capabilities at the lowest cost. Once organizations are familiar with native tools, they can integrate them with third-party tools to augment or replace functionality as needed. Third-party tools may include point solutions or broader CMPs. For more information on tooling selection strategies, see

For cloud cost optimization, organizations must define their requirements using the criteria in this document (see Methodology and Criteria section) and try to address them first with what cloud providers offer natively. See for a comprehensive assessment of the major cloud providers’ offerings. Subsequently, organizations can use this document to assess third-party cost optimization tools against the same set of criteria and select those that can fill identified gaps.

Assess Functionality Beyond Cost Optimization

Some of the tools assessed in this report focus only on cost optimization. Others provide broader cost management, including budgeting, tracking and reporting. Others even stretch out of cost management and address aspects of cloud security and compliance.

Organizations must assess these tools beyond cost optimization and identify other areas of management that they need to address. You can use Gartner’s to build a list of requirements across all areas of cloud management and map them to the tools you intend to use. Gartner recommends keeping the number of these tools to the minimum, without leaving requirements uncovered.

As a consequence, organizations should prefer tools that provide broader functionality. Such tools can minimize the number of vendors to manage and simplify the organization’s learning curve. Furthermore, Gartner believes that cost optimization is just part of the overall cloud governance discipline and that it will not continue to run as a stand-alone practice due to potentially conflicting policies. For example, a cost optimization policy may recommend moving a workload into a cloud provider’s region that is not allowed by a security policy.

However, you should also be cautious when selecting tools that cover a broad portion of the cloud management spectrum. Such tools spread their focus and development efforts across multiple disciplines and are at risk of providing shallower capabilities in favor of breadth of functionality. Therefore, prioritize tools that go beyond cost optimization but also provide enough capabilities, for example through integration with other third-parties.

Look for Integrations Within a Vendor’s Portfolio

Some of the larger vendors assessed in this report (such as Flexera or VMware) provide a broader portfolio of cloud management tools, each of them specialized in one area of management. Such vendors have the ambition to become a one-stop shop for organizations looking to address their overall cloud management requirements.

However, organizations must assess the level of integration between each of the vendor’s management solutions. Gartner research has shown that most of these vendors provide little to no integration between their products and that client organizations still have to deal with multiple products with different interfaces, state databases and learning curves. Although such vendors will certainly continue to integrate their portfolio tools, this is not the case yet.

Prioritize Quality of Insights, Then Automate

The primary value of cost optimization tools resides in the ability to handle a large amount of data from multiple sources, make sense of it and suggest actions to achieve maximum savings. Therefore, when evaluating cost optimization tools, organizations must concentrate on their “secret sauce” to extract actions from data.

Conversely, the ability to execute and automate suggested actions is indeed fundamental, but it is not where their core value stands. Automation per se is not hard to implement if you know which actions you want to accomplish. But automating the wrong action can be dangerous and lead to additional costs or performance degradation. Therefore, prioritize quality of insights in your assessments and how tools come to the conclusion that a certain action should be executed.

Once you have implemented your cost optimization tool, you’ll probably spend the first few months monitoring and scrutinizing the provided recommendations. Gartner inquiries show that most organizations don’t manage to fully trust potentially disruptive operation tools to turn on full automation from the start. At the beginning, you will execute most of the recommended actions manually and possibly even after engaging approval workflows and scheduling maintenance windows. But once you have developed trust in your selected tool and its ability to produce high-quality insights, you must aim to implement full automation.

Only full automation will allow you to achieve scale and maximize efficiency. Recommended actions can achieve maximum impact (hence, savings) if you execute them as soon as a recommendation is produced. Therefore, having the “human in the loop” can slow you down and miss opportunities. Manual execution also constitutes a management overhead because, most of the time, the recommended actions are repetitive.

On the assumption that you will eventually automate, you can already select tools that also provide the ability to automatically execute upon recommendations. Alternatively, you can look to automate using an external automation engine.

Methodology and Criteria

This Solution Comparison is based on a Gartner-defined and fixed set of criteria. Gartner assessed all the defined criteria consistently and methodically across all solutions compared, and each solution has been assessed against the same set of criteria.

Each criterion is made up of one or more attributes. Each attribute as described in this assessment has been examined separately, but all attributes of a single criterion translate to a single rating. The criteria are scored on a Gartner-defined scale with values of “None,” “Low,” “Medium” and “High,” where “High” is most capable and “None” signifies a lack of capability to satisfy the minimum requirements of the criterion.


This Solution Comparison is based on data gathered through vendor surveys and interviews with the respective vendors as well as online documentation, blogs and articles.

This document evaluates the public cloud cost optimization capabilities of the following third-party vendors and solutions (in alphabetical order):

  • Apptio (Hybrid Business Management and Cloudability)

  • CloudCheckr

  • Flexera (Flexera Optima)

  • Turbonomic (Turbonomic Platform and ParkMyCloud)

  • VMware (CloudHealth by VMware and vRealize Operations)

Gartner selected these five vendors and solutions based on Gartner client interest measured over the last 12 months. To be included in this report, these vendors must sell globally and actively maintain one or more software solutions for public cloud cost optimization. Furthermore, the vendor solutions must support at least one public cloud platform among AWS, GCP and Microsoft Azure.

This report also assesses and rewards vendors that provide resource optimization for on-premises cloud platforms. However, to contribute to the scores, the on-premises functionality must be provided in addition to the one available for public cloud platforms. For example, if a vendor provides upsizing recommendations only for on-premises environments, this capability would not contribute to the score calculation.

This report does not differentiate between generally available and beta capabilities. This assessment considers all functionality that is publicly available to each vendor’s customers as of September 2019.


This solution comparison makes use of the following terms:

  • Rightsizing: The action of adjusting the size of a compute instance or a software infrastructure service allocation to match the actual performance demand. Rightsizing can happen in both directions: “down” (for smaller recommended sizes) or “up” (for bigger recommended sizes).

  • Downsizing: Rightsizing action in the “down” direction (for smaller recommended sizes).

  • Upsizing: Rightsizing action in the “up” direction (for bigger recommended sizes).

  • Same-sizing: Rightsizing action that doesn’t actually include the change of resource size. Same-sizing is typically performed to change other resource parameters that may affect cost, such as a cloud provider’s subregion.

  • Subregions: Distinct cloud provider’s regions that are geographically close enough to deliver a cloud service with equivalent performance and latency but may have different costs associated. For example, AWS US-West-1 (N. California) and US-West-2 (Oregon).

  • Utilization policy: The utilization-based conditions that determine when a cost optimization opportunity should be pursued. Utilization policies can be based on multiple metrics such CPU, memory, storage space or hours of running time.

  • Observation period: The time period during which a resource is observed and its utilization is tracked to match it against the utilization policy.

  • Risk profile: A combination of utilization policy attributes that determines the risk of producing a wrong recommendation. Higher risk profiles can lead to more cost benefits but may affect performance (like in the case of rightsizing) or may generate spending waste (like in the case of reservations).

  • Software infrastructure services: Software infrastructure includes databases, middleware and other infrastructure elements typically delivered as software. Some of these services may be classifiable as PaaS. Some examples of software infrastructure services are Amazon ElastiCache, Azure Load Balancer and Google Cloud Spanner.

  • Allocation-based software infrastructure services: A software infrastructure service for which end users must specify an allocation size at the time of resource provisioning. End users pay for these services on the basis of the provisioned allocation, regardless of the service utilization. For example, Amazon RDS is allocation-based, while AWS ELB is not.

  • Scheduling engine: A cron-like engine that can be configured to issue specific cloud operations (such as resource start/stop) at certain date and time.

  • Warmer class: A cloud provider’s object storage class that is designed for more frequent access to the objects. Warmer classes normally deliver faster retrieval time but are more expensive than colder classes.

  • Colder class: A cloud provider’s object storage class that is designed for less frequent access to the objects. Colder classes normally deliver slower retrieval time but are less expensive than warmer classes.

  • On-premises cloud platform: An on-premises environment that supports the dynamic provisioning of (at a minimum) compute, network and storage resources through an API. VMware vSphere and Microsoft Azure Stack are examples of on-premises cloud platforms.


This solution comparison is based on 16 criteria grouped into four categories. Gartner’s defined set of criteria is based on common topics of discussion on public cloud cost-optimization and related inquiry calls, in concert with what Gartner believes is important for organizations evaluating ways to optimize their public cloud spend.

Cost optimization tools are part of the larger category of analytics tools. The value of analytics tools grows as they take on more responsibilities of the processes that lead from data to actions. A basic analytic tool will tell you what happened. An advanced one will tell you what you should do about it and automate the entire decision process.

Gartner used a similar framework to distribute the features that allow vendors to move between the scores of “Low,” “Medium” and “High” based on the growing value provided by the vendor’s solution. Additionally, with some exceptions, Gartner used the following scoring principles:

  • Recommendations must be original and independent. Simply collecting information from other sources, such as the provider’s API (e.g., AWS Trusted Advisor or Microsoft Azure Advisor), does not qualify for the criteria in this assessment.

  • The configurability of the utilization policy that drives the identification of optimization opportunities is often required to earn a “Medium” score. Although vendors apply default values to their policies that cover the majority of use cases, customers may require the customization of certain utilization parameters to fine-tune the analytics engine.

  • The ability to display cost implications of identified optimization opportunities is often required to earn a “Medium” score. Information such as estimated savings or additional expenditure is fundamental to help organizations decide whether to act on the provided recommendations.

  • The ability to execute actions with “one click” directly from the console of the cost optimization tool is often required to earn a “Medium” score.

  • Criteria that relate to compute instances are often more “prescriptive” than criteria for software infrastructure services, storage or other resources. This is due to the higher maturity of the IaaS market and the more sophisticated management requirements that organizations have in this area.

  • Functionality for software infrastructure services often requires specific support for database solutions to earn a “Low” score and for caching or container orchestration services to earn higher scores.

  • The availability of parameters that can be used to define a risk profile is often required to earn a “High” score. Such parameters allow the tool to produce more or less aggressive recommendations that prioritize savings over performance or vice versa.

  • The ability to automate optimization actions is often required to earn a “High” score. To meet these automation criteria, customers must be able to configure the solution to execute actions automatically without user interaction. It is not sufficient for vendors to provide the availability of actions in their API. They must orchestrate the entire automation workflow.

This assessment exclusively considers features that vendors provide out-of-the-box and that are accessible via the tool’s point-and-click interface. This methodology excludes all features that can only be accomplished through the development of code such as an AWS Lambda function or similar. The exclusion also applies to features that can only be accomplished by modifying lines of vendor-provided code.

The criteria have been developed to evaluate vendor support for the following capabilities:

  • Compute instance rightsizing: This criterion assesses recommendations, execution and automation of rightsizing for compute instances. The assessed functionality includes downsizing, upsizing, utilization policy configuration (including externally injected metrics), cross-family and cross-region rightsizing.

  • Block storage rightsizing: This criterion assesses recommendations, execution and automation of rightsizing for block storage volumes. The assessed functionality includes size-based and IOPS-based volume type changes and utilization policy configuration.

  • Software infrastructure services rightsizing: This criterion assesses recommendations, execution and automation of rightsizing for allocation-based software infrastructure services. Assessed services include database solutions, caching services and container orchestration services.

  • Idle compute instance decommissioning: This criterion assesses recommendations, execution and automation of the decommissioning of idle compute instances. The assessed functionality includes the configuration of utilization metrics to define the “idle” state.

  • Unused storage decommissioning: This criterion assesses recommendations, execution and automation of the decommissioning of unused block storage volumes. The assessed functionality includes the configuration of when a storage volume should be considered “unused” (i.e., the number of days it has been unattached to instances).

  • Old snapshot decommissioning: This criterion assesses recommendations, execution and automation of the decommissioning of old snapshots. The assessed functionality includes the configuration of when snapshots should be considered “old” (i.e., the number of days from creation).

  • Unused service decommissioning: This criterion assesses recommendations, execution and automation of the decommissioning of provisioned capacity for allocation-based software infrastructure services that are not being used. Assessed services include database solutions, caching services and container orchestration services.

  • Unused resource decommissioning: This criterion assesses recommendations, execution and automation of the decommissioning of provisioned resources that are not being used. Assessed resource types include IP addresses, network gateways and load balancers.

  • Resource scheduling: This criterion assesses the ability to determine and configure resource scheduling. The assessed functionality includes the identification of utilization patterns and the schedule configuration using an internal or external scheduling engine. In addition, this criterion assesses auto shutdowns (after a time from the start), resource grouping, dependency support and the ability to execute arbitrary commands before and after start/stop operations.

  • Reservation purchase management: This criterion assesses the ability to recommend and execute the purchase of reservations such as Amazon EC2 RI, Google CUDs and Microsoft Azure RIs. The assessed functionality includes the configuration of the utilization policy, the definition of a risk profile and the ability to handle reservations for software infrastructure services (when these are supported by the provider).

  • Reservation portfolio management: This criterion assesses the ability to modify the flexible attributes of purchased reservations (when these are supported by the provider). The assessed functionality includes reservation expiration alerts, backward analysis of past coverage and waste and the ability to automate the modifications.

  • Object storage optimization: This criterion assesses the ability to move storage objects between available classes based on time or utilization conditions. The assessed functionality includes the movement within three storage classes (hot, warm and cold) based on access patterns and the ability to automate the movement in all directions.

  • AWS support: This criterion assesses the solution’s functionality coverage for AWS. To achieve higher scores, the solution must provide at least 50% (for a “Medium” score) or 75% (for a “High” score) of its features for AWS.

  • Microsoft Azure support: This criterion assesses the solution’s functionality coverage for Microsoft Azure. To achieve higher scores, the solution must provide at least 50% (for a “Medium” score) or 75% (for a “High” score) of its features for Microsoft Azure.

  • GCP support: This criterion assesses the solution’s functionality coverage for GCP. To achieve higher scores, the solution must provide at least 50% (for a “Medium” score) or 75% (for a “High” score) of its features for GCP.

  • On-premises cloud platform support: This criterion assessed the solution’s functionality coverage for one or more on-premises cloud platforms such as VMware vSphere. Because not all of the criteria are applicable to on-premises environments, only the capabilities marked as “[OP]” in Table 6 are considered for this score. To achieve higher scores, the solution must provide at least 50% (for a “Medium” score) or 75% (for a “High” score) of its features (also marked as “[OP]”) for an on-premises cloud platform.

Each criterion corresponds to a set of features or capabilities that solutions must implement to attain a particular rating for that criterion. The rating for each criterion is based on compliance with the attributes that belong to a particular rating value. The reader should note that the criteria’s attributes are cumulative. To achieve a higher rating, a solution must implement the features or capabilities required by the preceding rating and then add additional ones.

Table 6 provides the definitions for each rating for each criterion evaluated in this Solution Comparison. Attributes marked as “[OP]” in the following table are those relevant for the “on-premises cloud platform support” criterion.

Gartner Recommended Reading

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IT financial management (ITFM) tools provide CIOs with the detailed cost and consumption analysis required to run IT like a business. These tools are designed to improve IT financial decision making by providing multiple views into the total cost of IT. This means the aggregation of all relevant IT costs, whether at the technology, application or services level or from an investment perspective.

ITFM tools do not replace enterprise financial systems, nor should they require modification to corporate systems of record like the general ledger. Rather, they provide a purpose-built application designed to aggregate all IT spend and consumption data from disparate systems of record and allocate that data against a cost model designed to provide transparency into IT spending.

ITFM tools often replace customized spreadsheet-based tools when the spreadsheets and data imports become too difficult to manage and maintain as new datasets are added, data hygiene degrades or allocation models change.

ITFM tools do not provide continuous cost optimization functionality as described in this assessment.

For more information on ITFM tools see

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