Operations | Monitoring | ITSM | DevOps | Cloud

By kickstarting a monitoring project with Prometheus, you might realize that you get an initial set of out-of-the-box metrics with just Node Exporter and Kube State Metrics. But, this will only get you so far since you will just be performing black box monitoring. How can you go to the next level and observe what’s beyond? They are an essential part of the day-to-day monitoring of cloud-native systems, as they provide an additional dimension to the business and app level.

Since the very first version, Epinio has made use of an internal S3 endpoint to store the user’s projects in the form of aggregated tarballs. Those objects are then downloaded and staged by the internal engine’s pipeline and, finally, they are deployed into the Kubernetes cluster as consumable applications. Epinio makes use of S3 as an internal private service. In this scenario, S3 can be thought of as an internal ephemeral cache with the purpose of storing temporary objects.

StormForge Optimize Live is a machine learning-powered performance and resource optimization solution for Kubernetes workloads. Optimize Live ingests and analyzes production observability data and recommends specific actions to optimize CPU and memory utilization. You can take these actions manually or set them to occur automatically, making it easier to maintain a high level of application performance while minimizing cloud costs.

Have you ever wondered how you can help Kubernetes manage your pods in the most efficient way? Kubernetes can do a decent job “out of the box,” but it can be optimized just like any other system. One such optimization in the Kubernetes world is introducing liveness probes, and in this post, you’ll learn everything about them.