Self-hosted runner enables you to use your own infrastructure for running jobs. If your team has unique security or compute requirements, you can use self-hosted runner to build, test, and deploy your applications from your own infrastructure.

The latest Netdata Agent release v1.36 introduces anomaly rates on every chart, a centralized admin interface, metric correlation improvements, and a new tiering mechanism that allows almost unlimited metrics for your nodes. Want to know more? Hit "Subscribe" and post a comment or ask your question below.

In this video, Ben Wilcock (@benbravo73) looks at how VMware Tanzu Application Platform levels up your Kubernetes and allows you to inspect, debug, and fix your code live - while it's running on the platform.

Kubernetes® monitoring with AppDynamics Cloud provides you with the visibility you need into your Kubernetes infrastructure. It provides you the capability to monitor metrics on clusters, namespaces, workloads, pods and ingress controllers. You also have the capability to cross validate metrics from your servers and network interfaces as well as cloud providers. Monitor your pod resources for performance issues or identify needs to scale. Kubernetes, as well as App Service Monitoring, is supported by using an OpenTelemetry™ Operator.

Splunk’s Product Manager Priit Potter walks you through how to identify memory bottlenecks in Java applications, in this detailed product walkthrough. See how Priit troubleshoots his own application, visualizes memory performance problems, and uses flame graphs to detail the line of code responsible for the problem, all with the help of Splunk Application Performance Monitoring.

Discover how container resource requests and limits work and what we can do to maintain them.

Link to Postgre SQL Plugin: https://pandorafms.com/library/postgresql-plugin/

Want to test the power of all-in-one monitoring? Request a free trial of the Enterprise version on our website: https://bit.ly/2O9hoRf

What are the basics of creating a container probe and how the process changes depending on the container probe used.

Change Lead Time can be considered the most insightful of the four DORA metrics. But how do you measure it most accurately? In this video, Don Brown shows you how Sleuth measures Change Lead Time for code changes and how Sleuth breaks down that time into multiple buckets for the most detailed insight on what's slowing your team down. Check out these videos on how Sleuth measures other DORA metrics.

Before you can measure the DORA metric for Change Failure Rate, you need to define what failure means. In this video, Sleuth's CTO Don Brown explains how Sleuth defines and measures Change Failure Rate, and how it ties failure back to deployments. Check out these videos on how Sleuth measures other DORA metrics: Give Sleuth a try and see why it's a deploy-based Accelerate / DORA metrics tracker both managers and developers love.