Gke

Production systems are being monitored for reliability and performance tracking to say the least. Monitored metrics ‒ a set of measurements that are related to a specific attribute of a system being monitored, are first captured in the executing code of the system and then are ingested to the monitoring backend. The selection of the backend often dictates the methods(s) of ingestion. If you run your workloads on Google Cloud and use self-managed Prometheus server and metric collection, this post will help you to reduce maintenance overhead and some billing costs by utilizing Google Cloud Managed Service for Prometheus for collecting and storing Prometheus metrics.

Google Cloud lets you run Kubernetes in three flavors:

• Vanilla is when you do all on your own. This is also the quickest “lift and shift” strategy to migrate your cluster to cloud. Essentially it is just a group of virtual machines that run on Google Compute Engine (GCE).
• Managed that shifts administration and maintenance tasks from DevOps teams to the cloud service. See Google Kubernetes Engine (GKE) Standard cluster architecture and Autopilot for more details.
• Knative, that is sometimes referred to as cloud native, which hides control plane and other infrastructure details behind the familiar interface of workload launching. Cloud Run offers running service and job workloads using the GKE platform behind the Knative interface.

Many DevOps teams prefer the managed flavor to enjoy a balance between carefree administration and the level of control that is very close to vanilla Kubernetes. Comparing GKE Autopilot and Standard, many prefer Standard due to higher control granularity over node management, security and version configuration and other options. In the cluster observability domain, these differences are less distinctive since both come with a rich set of monitoring and logging capabilities including control plane metrics.