In a production environment, a downtime of even a few microseconds is intolerable. Debugging such issues is time-critical. Proper logging and monitoring of infrastructure help in debugging such scenarios. It also helps in optimizing cost and other resources proactively, as well as helps to detect any impending issue which may arise in the near future. There are various logging and monitoring solutions available in the market. In this post, we will walk through the steps to deploy Grafana Loki in a Kubernetes environment. This is due to its seamless compatibility with Prometheus, a widely used software for collecting metrics. Grafana Loki consists of three components: Promtail, Loki, and Grafana (PLG), which we will see in brief before proceeding to the deployment. This article provides a better insight into the architectural differences of PLG and other primary logging and monitoring stack like Elasticsearch-FluentD-Kibana (EFK).
Logging, Monitoring, and Alerting With Grafana Loki
Before proceeding with the steps for deploying Grafana Loki, we will see each tool briefly.