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Monitoring Kubernetes cert-manager Certificates With BotKube

The monitoring and alerting stack is a crucial part of the SRE practices. That’s where BotKube helps you monitor your Kubernetes cluster and send notifications to your messaging platform or any other configured sink. In this blog post, we will be configuring BotKube to watch the Kubernetes cert-manager certificates CustomResources.

What is BotKube?

BotKube is a messaging tool for monitoring and debugging Kubernetes clusters. BotKube can be integrated with multiple messaging platforms like - Slack, Mattermost, or Microsoft Teams to help you monitor your Kubernetes cluster(s), debug critical deployments, and gives recommendations for standard practices by running checks on the Kubernetes resources.

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Kubernetes Autoscaling with Custom Metrics (Updated)

In the previous blog post about Kubernetes autoscaling, we looked at different concepts and terminologies related to autoscaling such as HPA, cluster auto-scaler, etc. In this post, we'll do a walkthrough of how Kubernetes autoscaling can be implemented for custom metrics generated by the application.

Why Custom Metrics?

The CPU or RAM consumption of an application may not indicate the right metric for scaling always. For example, if you have a message queue consumer that can handle 500 messages per second without crashing. Once a single instance of this consumer is handling close to 500 messages per second, you may want to scale the application to two instances so that load is distributed across two instances. Measuring CPU or RAM is a fundamentally flawed approach for scaling such an application and you would have to look at a metric that relates more closely to the application's nature. The number of messages that an instance is processing at a given point in time is a better indicator of the actual load on that application. Similarly, there might be applications where other metrics make more sense and these can be defined using custom metrics in Kubernetes.

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Introducing : Tracing Cassandra With Jaeger

Monitoring and debugging microservices and distributed systems is not trivial. With the rise of containers and ephemeral infrastructure, it is even more critical to have all the data available for the applications. The monitoring as of today is usually done across three axes: metric monitoring, logs, and distributed tracing

Stop reverse engineering applications and start monitoring from the inside.

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Monitoring YugabyteDB in Kubernetes With the Prometheus Operator and Grafana

Using the Prometheus Operator has become a common choice when it comes to running Prometheus in a Kubernetes cluster. It can manage Prometheus and Alertmanager for us with the help of CRDs in Kubernetes. The kube-prometheus-stack Helm chart (formerly known as prometheus-operator) comes with Grafana, node_exporter, and more out of the box.

In a previous blog post about Prometheus, we took a look at setting up Prometheus and Grafana using manifest files. We also explored a few of the metrics exposed by YugabyteDB. In this post, we will be setting up Prometheus and Grafana using the kube-prometheus-stack chart. And we will configure Prometheus to scrape YugabyteDB pods. At the end, we will take a look at the YugabyteDB Grafana dashboard that can be used to visualize all the collected metrics.

Posted on

Monitoring YugabyteDB in Kubernetes

monitoring YugabyteDB

Using the Prometheus Operator has become a common choice when it comes to running Prometheus in a Kubernetes cluster. It can manage Prometheus and Alertmanager for us with the help of CRDs in Kubernetes. The Kube-Prometheus-stack Helm chart (formerly known as Prometheus-operator) comes with Grafana, node_exporter, and more out of the box.

In a previous blog post about Prometheus, we took a look at setting up Prometheus and Grafana using manifest files. We also explored a few of the metrics exposed by YugabyteDB. In this post, we will be setting up Prometheus and Grafana using the Kube-Prometheus-stack chart. And we will configure Prometheus to scrape YugabyteDB pods. In the end, we will take a look at the YugabyteDB Grafana dashboard that can be used to visualize all the collected metrics.