Cloud cost analysis tools help your organization keep on top of its overall cloud use and associated costs, which can add up rapidly.
It feels like just yesterday that we were promised that cloud servers cost just pennies. You could rent a rack with the spare change behind the sofa cushions and have money left for ice cream. Horizontal Completion
Those days are long gone. When the monthly cloud bill arrives, CFOs are hitting the roof. Developer teams are learning that the pennies add up, sometimes faster than expected, and it’s time for some discipline.
Cloud cost management tools are the answer.
Cloud cost management is a business discipline aimed at monitoring, analyzing, and optimizing an organization’s cloud computing spend. It gives organizations greater visibility into how cloud resources are being used and can also help identify and eliminate unused or overprovisions services, as well as predict future cloud costs to provide more fine-tuned forecast budgets.
Cloud cost management tools aid organizations in this practice by tracking all the bills associated an organization’s cloud use, allocating them to the various teams responsible for their accumulation. That way the group that added too many fancy features that need too much storage and server time will have to account for their profligacy. The good programmers who don’t use too much RAM and disk space can be rewarded.
Smaller teams with simple configurations can probably get by with the stock cloud cost management services provided by their cloud vendor of choice. Cost containment is a big issue for many CIOs now and the cloud companies know it. They’ve started adding better accounting tools and alarms that are triggered before the bills reach the stratosphere. See Azure Cost Management, Google Cloud Cost Management, and AWS Cloud Financial Management tools for the big three clouds.
Once your cloud commitment gets bigger, stand-alone cost management tools start to become attractive. They’re designed to work with multiple clouds and build reports that unify the data for easy consumption. Some even track the machines that run on premises so you can compare the cost of renting versus building out your own server room.
In many cases, cloud cost managers are part of a larger suite designed to not just watch the bottom line but also enforce other rules such as security. Some are not marketed directly as cloud control tools but have grown to help solve this problem. Some tools for surveying enterprise architectures or managing software governance now track costs at the same time. They can offer the same opportunities for savings that purpose-built cloud cost tools do — and they help with their other management chores as well.
What follows is an alphabetical list of the best cloud cost tracking and analysis tools. The market is rapidly expanding as enterprise managers recognize the need to get a grip on their cloud spend. All of these tools can help govern the burgeoning empire of server instances that your organization relies on for its cloud operations, which may stretch around the world.
The first job for Anodot’s collection of cloud monitoring tools is to track the flow of data through the various services and applications. If there’s an anomaly or hiccup that will affect users, it will raise a flag. Tracking the cost of instances and pods across your multiple clouds is part of this larger job. The dashboard produces a collection of infographics that make it possible to study each microservice or API and determine just how much it costs to keep it running in times of high demand and low. This granular detail gives you the ability to spot the expensive workloads and find a way to prune them.
Tracking and reining in containers in a Kubernetes environment is the goal for Cisco’s AppDynamics, formerly known as Replex. The tool is now part of a larger system that watches clusters in public clouds or running locally to ensure they are performing correctly. Tracking costs is just one small part of a system that is constantly gathering statistics and watching for anomalies. One important reporting process charges back costs to the teams responsible for them so everyone can understand what’s creating the monthly bill. AppDynamics also offers a proprietary machine learning engine to turn historical data into a plan for efficient deployment. A policy control layer offers granular restrictions to ensure teams have access to what they need but are locked out of what they don’t.
Apptio makes a large collection of tools for managing IT shops, and Cloudability is its tool for handling cloud costs. The tool breaks down the various cloud instances in use, allocating them to your teams for accounting purposes. Ideally, teams will be able to control their own costs and predict future usage with the reports and dashboards on offer. Cloudability’s True Cost Explorer, for instance, offers pivotable charts to switch between aggregated variables to establish accurate plans and predict future usage. Cloudability integrates with ticketing tools such as Jira for planning and with tracking tools such as PagerDuty or Datadog for monitoring.
Dashboards created by CloudAdmin are simple and direct. The tool tracks cloud usage and offers suggestions for rightsizing your servers or converting them to reserved instances. Server instances can be allocated to teams and then tracked with a budget. If spending crosses a defined line, alerts are integrated with email or other common communication tools such as PagerDuty to notify personnel of the need for attention.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
Inclination Sensor 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.