Cloud-native development and microservices enable development teams to work more efficiently and innovate faster. Operators appreciate the container environment because it increases infrastructure utilization, enabling them to accomplish more with less while managing critical applications at unprecedented scale. Kubernetes and containers adoption growing fast in the last few years.

When there’s an incident, Grafana is often the starting point for figuring out a response. Users look at a time series panel and form a hypothesis. And in many situations, they’d like to dive deeper. To help make that easier, Grafana Labs has created the Explore UI, which allows you to iterate quickly through Prometheus queries, while leaving your dashboards intact.

We covered how to install a complete ‘Kubernetes monitoring with Prometheus’ stack in the previous chapters of this guide. But using the Prometheus Operator framework and its Custom Resource Definitions has significant advantages over manually adding metric targets and service providers, which can become cumbersome for large deployments and doesn’t fully utilize Kubernetes’ orchestrator capabilities.

Ready to deploy an AppD application agent to OpenShift? These detailed examples show you how. There are several ways to instrument an application on OpenShift with an AppDynamics application agent. The most straightforward way is to embed the agent into the main application image.

Kubernetes and OpenShift are powerful and flexible. They’re also complex to setup, monitor and maintain at scale. Here’s a sneak peek into what we monitor in OpenShift, as well as some hard-earned advice on how our strategy might benefit your own environments.

Sensu Summit 2018 was a two-day extravaganza, with keynotes, workshops, donuts, and all the monitoring love.

In this blog post we’ll cover how to implement Docker Scanning for Jenkins with the Sysdig Secure Jenkins plugin. The plugin can be used in both freestyle and pipeline jobs to scan images and fail the build if the image fails a policy evaluation.

The adoption of microservices and container technologies has increased rapidly as DevOps teams look into faster release cycles for application delivery. However, these ephemeral technologies dramatically increase the complexity of managing, visualizing and mapping dependencies between components in your IT infrastructure. Microservices are dynamic and can scale horizontally in an instant, which poses challenges in monitoring when the locations of containers and services are constantly changing.