Cloud cost management tools are a relatively new creation. Just a decade ago, the cloud was pitched as saving us the hassle of bidding, installing, and maintaining our own hardware. Prices per hour were specified in pennies. How could anything go wrong?
What we’ve come to find is that all those fractions of a penny can pile up into a number that breaks the budget. Cloud cost management platforms are here to help, tracking all the bills and 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 are going to 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 services of the cloud companies. 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 a bit bigger, independent 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 do a great job tracking 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. They also help govern the burgeoning empire of server instances that may stretch around the world. If you’ve ever wondered whether you can say, “The sun never sets on my cloud empire,” just like the British did so many years ago, you can answer that question with these reports.
What follows is an alphabetical list of many of the best cloud cost tracking tools. The area is rapidly expanding as enterprise managers recognize they need to get a grip on their cloud bills.
Apptio Cloudability
Apptio makes a large collection of tools for managing IT shops, and Cloudability is its tool for handling cloud costs. The tool accurately breaks down the various cloud instances in use, allocating them to your various teams for accounting purposes. Ideally, your teams will be able to control their own costs with the various reports and chart dashboards on offer. Cloudability’s True Cost Explorer, for instance, offers pivotable charts to switch between various aggregated variables in order to establish accurate plans and predict future usage. Cloudability also integrates with ticketing tools such as Jira for planning and tracking tools such as Datadog for monitoring.
CloudAdmin
The dashboards created by CloudAdmin are simple and direct. The tool’s backend tracks cloud usage and the web interface offers suggestions for right-sizing 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
CloudCheckr focuses on controlling cloud costs and security. Its cost management functionality tracks standard issues, such as consumption, forecasting, and the rightsizing of instances. The tool also 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 the public clouds used by governments.
Densify
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%, a number certain to make the finance team happy. Densify’s FinOps tool generates extensive reports to help keep application developers and bean counters happy.
Flexera One
The cloud management suite of products known as Flexera One has a section 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 provides some automated systems to put these observations into practice.
Harness
DevOps teams can use the pipeline included in 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, and generate 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.
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.
Nutanix Xi Beam
Organizations with large multicloud deployments can use Nutanix Xi 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.
Replex
Tracking and reining in the containers in a Kubernetes environment is the goal for Replex. The tool watches clusters in public clouds or running locally, gathering statistics about load in order to build reports that chargeback costs to the teams responsible for them. Replex 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.
Spot
The Spot marketplace is often the cheapest opportunity to acquire computing resources, but it can be tricky to manage. Spot automates some of the work of managing a collection of reserved instances and augmenting them with spot machines as needed. Its Elastigroup tool will offer scaling plans based on past performance while Cloud Analyzer generates reports to help understand just where the money is going.
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.
VMware CloudHealth
VMware built CloudHealth to manage deployments across all the major cloud platforms as well as hybrid clouds. The cost accounting module tracks spending and allocates it to business teams while optimizing deployments to minimize spending. The modeling layer can build out amortization and consumption schedules to accurately forecast future demand. Both financial managers and development teams can drill down into these forecasts to focus on specific applications or constellations of services.
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. 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 control the amount of disk space allocated to individual machines while buying and selling processor time on the spot from reserved instance marketplaces.
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