Top 17 cloud cost management tools — and how to choose
Standout features:
Carefully filtered data feeds extract the key details about spending to save time wading through too much information
Automated alerts can stop runaway spending when it crosses thresholds
CloudCheckr
CloudCheckr focuses on controlling
Standout features:
- Carefully filtered data feeds extract the key details about spending to save time wading through too much information
- Automated alerts can stop runaway spending when it crosses thresholds
CloudCheckr
CloudCheckr focuses on controlling cloud costs and security. The tool is part of NetApp’s Spot constellation for cloud management and is responsible for cost management by tracking standard spending events, such as consumption, forecasting, and the rightsizing of instances. The tool supports reselling for companies that add their own layers to commodity cloud instances. A white label option makes it possible to pass through all the reporting and charts to help your customers understand their billing. There’s also a focus on supporting public clouds used by governments.
Standout features:
- Monitor compliance with privacy regulations by tracking security configuration
- Rightsize reserved instances by tracking baseline consumption
Datadog
Watching over cloud machines, networks, serverless platforms, and other applications is the first job for Datadog’s collection of tools. Tracking cloud costs is just one part of the workload. Its telemetry gathers data about performance and cost, and Datadog builds this into a dashboard to help organizations understand both application cost and performance. The goal is to facilitate decisions about application performance with an eye on the price of delivering it. Understanding the tradeoff can lead to cost savings.
Standout features:
- Broad suite for infrastructure monitoring across multiple clouds
- Monitoring of real users and simulated users make it easier to deliver a better user experience
Densify
Densify builds a collection of tools for managing cloud infrastructure by juggling containers and VMware instances. The best way to run your clusters, according to Densify, is to keep precise, meticulous records of load and then use this data to scale up and down quickly. Densify’s optimizers focus on cloud resources such as instances, Kubernetes clusters, and VMware machines. Densify suggests this approach improves scaling by 30%. Densify’s FinOps tool generates extensive reports to help keep application developers and bean counters happy.
Standout features:
- Track loads on machines to ensure rightsized instance allocation
- Build reports summarizing consumption to help developers rightsize hardware
Flexera One
The Flexera One cloud management suite tackles many cloud management tasks, such as tracking assets or organizing governance to orchestrate control. An important section of the suite is devoted to controlling the budget. The tool offers multicloud accounting for tracking spending with elaborate reporting broken down by team and project. Flexera One also offers suggestions for optimizing consumption by targeting wasteful allocations, and it provides automated systems to put these observations into practice. The tool also integrates machine learning and artificial intelligence to help analyze consumption patterns across multiple clouds.
Standout features:
- Integrates reporting across multiple clouds to help business groups understand costs
- Identifies options for rightsizing instances and eliminating wasteful spending
Harness
DevOps teams can use the CI/CD pipeline that’s the central part of Harness to automate deployment and then, once the code is running, track usage to keep budgets in line. Harness’s cost management features watch for anomalies compared to historic spending, generating alerts for teams. A feature for automatically stopping unused instances can work with spot machines, effectively unlocking their potential for cost savings while working around their ephemeral nature.
Standout features:
- Deep integration with the development pipeline to make cost savings part of the software creation process
- Automated compliance integrates cost management with regulatory and governance work
Kubecost
Teams that rely on Kubernetes to deploy pods of containers can install Kubecost to track spending. It will work across all major (and minor) clouds as well as pods hosted on premises. Costs are tracked as Kubernetes adjusts to handle loads and are presented in a unified set of reports. Large jumps or unexpected deployments can trigger alerts for human intervention.
Standout features:
- Optimized for tracking how Kubernetes deployments affect costs
- Dynamic recommendations track opportunities for lowering spending
ManageEngine
DevOps teams rely on ManageEngine to track a range of potential issues from security to API endpoint overload. Its CloudSpend tool will extract data from cloud spreadsheet bills and aggregate it to provide a useful, actionable level of understanding. Costs can be charged back to the specific teams, and ManageEngine’s predictive analytics will plan reserved instances based on historical data. Currently available for AWS and Azure.
Standout features:
- Spend Analysis drills down deeply into the data to granular detail
- Multi-currency support for worldwide deployment
Nutanix
Organizations with large multicloud deployments can use Nutanix Cost Governance (formerly Beam) to track costs across a range of installations, including private cloud machines hosted on premises. The tool can be customized to generate accurate cost estimates of private installations by taking into account heating and cooling costs, hardware, and data center rent. This makes it easier to make accurate decisions about allocating workloads to the lowest-cost deployment. The process can be automated to simplify management and forward-planning for budgeting for reserved instances.
Standout features:
- Metering of private clouds builds direct insight into the costs of on-prem hardware
- Budget alerting and dynamic optimization help rightsize consumption to minimize costs
ServiceNow
Teams running extensive collections of microservices rely on ServiceNow to manage some of the stack. Many of the tools are customer-facing solutions like IT automation, but there are also more backend tools for optimizing IT operations by intelligently managing performance. Newer AIOps can deliver artificial intelligence solutions too.
Standout features:
- Broad selection of tools for tracking and optimizing IT assets
- Risk management well integrated with governance tools
Turbonomic
IBM relies on Turbonomic to deliver an AI-powered solution for managing deployment to match application demand with infrastructure. The tool will automatically start, stop, and move applications in response to demand. The data driving these decisions is stored in a warehouse to train the AI that will be making future decisions. The latest version includes a new dashboard and reporting framework based on Grafana.
Standout features:
- Full-stack integrated graphics to understand demand and cost across an application
- Designed to automate resource allocation to save engineering teams from the chore
VMware Aria CloudHealth
VMware built Aria Cost and Aria Automation under the CloudHealth brand to manage deployments across all major cloud platforms as well as hybrid clouds. The cost accounting module tracks spending, allocating it to business teams while optimizing deployments to minimize costs. The modeling layer can build out amortization and consumption schedules to forecast future demand. Financial managers and development teams can drill down into these forecasts to focus on specific applications or constellations of services. The larger product line integrates the cost management with automated deployment and security enforcement.
Standout features:
- Spending governance ensures that teams are following individual budgets for resource consumption
- Integrate cloud costs with business metrics and key performance indicators to understand the connection between computational costs and the bottom line
Yotascale
Much of the responsibility for cloud costs comes from the engineers who write and deploy the code. They make the granular decisions to startup more instances and store more data. Yotascale wants to put more information in their hands to enable them to optimize their hardware consumption with tools designed to track machines and allocate their costs directly to the teams responsible. The forecasting tools can also spot anomalies, raising alerts to prevent any surprise bills at the end of the month.
Standout features:
- Engineer-targeted tools deliver budget information directly to the teams building the software and starting up the machines
- Automated tracking delivers forecasts and flags problems and overconsumption
Zesty
While many cloud managers offer insights through sophisticated reports, Zesty is designed to automate the work of spinning up and shutting down extra instances. A key feature enables it to watch the reserved market for deeply discounted instances with excess capacity on the cloud. It offers a tool informed by artificial intelligence algorithms that can work with AWS’s API to make decisions that keep just enough machines running to satisfy users without breaking the budget. The tool can even control the amount of disk space allocated to individual machines while buying and selling processor time on the spot from reserved instance marketplaces.
Standout features:
- Deep management of details such as storage space allocation to minimize costs
- Integration with spot market to take advantage of the lowest possible costs
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