Red Hat has extended a free software-as-a-service (SaaS) offering included with Red Hat OpenShift Container Platform subscriptions designed to make it easier to control cloud costs.
Sergio Ocón-Cárdenas, principal product manager for IT business management at Red Hat, says the reach of the cost containment tools provided via the Red Hat Insights service has been extended to include integration with application programming interfaces (APIs) surfaced by Amazon Web Services (AWS) and Microsoft Azure cloud services. That integration also enables Red Hat to tag specific services running on those clouds, he says.
That data is then fed into a console through which it already surfaces cost analyses for the Red Hat OpenShift Container Platform, which is based on Kubernetes. That console is based on Prometheus, an open source monitoring platform being advanced under the auspices of the Cloud Native Computing Foundation (CNCF).
Collectively, IT teams are now provided with a more comprehensive view of the total cost for deploying the Red Hat OpenShift Container Platform, Ocón-Cárdenas says.
Ocón-Cárdenas notes that predicting costs when deploying containerized applications is challenging because containers are being replaced constantly. The cost management tools provided by Red Hat apply markup ratios to monitored infrastructure to reflect the real costs of a production environment.
Interest in containing cloud costs is on the rise in response to the economic downturn brought on by the COVID-19 pandemic. The paradox is that more workloads are now heading into the cloud as organizations in the wake of the pandemic look to deploy applications that are both more flexible and resilient. However, if those deployments are not carefully managed, an IT organization can wind up spending more money on cloud infrastructure than it does in an on-premises IT environment.
In many cases, cloud services are spun up by developers often using a credit card, and before too long all the developers in the employ of that organization are incurring a significant monthly cost, ultimately surprising IT teams and financial executives when the bill comes in. Most IT teams want to be able to rein in those costs without adversely impacting developer productivity. The first step toward achieving that goal is undoubtedly visibility.
There may, of course, come a day when machine learning algorithms and other forms of artificial intelligence automate cloud cost optimization. AWS, for example, has made available a tool dubbed Amazon CodeGuru that employs machine learning algorithms to recommend ways to improve code quality and identify which lines of code are the most expensive to run on its cloud service.
Regardless of the platform employed, there’s no doubt sensitivity to IT costs is higher now than any other time in recent memory. IT teams can either get in front of this issue now by proactively managing IT costs or waiting for an edict from the finance team that may not take into account the importance of one workload over another.