Although there are many great tools out there to get on top of application monitoring, there’s one vital metric that’s often overlooked by us technical folks – cost. In the days of running apps on servers in private datacenters, the kit was a one-time purchase that the systems team had to deal with. But running apps in public clouds is a different story. Whether you’re running on VMs, containers in Kubernetes, or entirely serverless, execution of your code adds to the bill.
Although reducing costs is one of the benefits organizations seek in deploying Kubernetes in the cloud, many organizations find it difficult or impossible to monitor and control their costs. The problem typically stems from a lack of visibility. For example, 53% of respondents in the Anodot State of Cloud Cost Report 202 2 said their biggest challenge to controlling costs is gaining visibility into their cloud usage and associated costs.
One of the key advantages of cloud services versus on premise deployments is the wide range of purchasing options and pricing models. While it’s an attractive advantage, it can be complicated for organizations to determine the best blend of service pricing models. The ability to define the organization’s blend of purchasing strategies and display the target versus actual performance is critical for optimizing cloud cost management efforts.