In our 2023 Container Report, we analyzed over 2.4 billion containers and determined that 65% of these containers were using less than half of their requested resources, leading to wasted resources and inefficient cloud spend. When deploying applications on Kubernetes, application and platform teams often choose to overprovision resources for their containers as a way to avoid infrastructure capacity issues from impacting their end users. For this reason, it’s critical for organizations to have a solution in place to constantly monitor their resource usage in order to strike the right balance between performance and cost. 

With Datadog Kubernetes Autoscaling, you’re able to continuously monitor and automatically optimize Kubernetes workloads, ensuring both optimal application performance and cost savings in your cloud infrastructure. 

In this session, we’ll learn about how Datadog enables platform and application teams to achieve outcomes such as:

• Reduced cloud costs and improved application performance with automated resource scaling for Kubernetes workloads
• Improved collaboration between teams who can leverage a unified view to make resource allocation decisions together
• Full visibility into the downstream impact of rightsizing decisions by correlating service health with resource metrics