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· 9 min read
Muskan Paliwal

In this tutorial, we will learn about Docker container lifecycle. But first, let me share a personal anecdote. On a hot summer afternoon in 2021, my manager called me out of the blue and said, “Muskan, the project file you shared with me is not working on my machine. Could you please come over and fix the setup? It’s really urgent.” I rushed to his cabin and tried my best but could not fix the dependencies issues.

· 7 min read
Ankit Anand

Single pane of glass monitoring is a term used to denote monitoring applications with a single tool that provides a comprehensive set of dashboards for the entire software system of an organization. Managing multiple monitoring tools for different aspects of the IT system becomes too cumbersome. And that’s how the concept of a single pane of glass monitoring evolved.

· 7 min read
Ankit Anand

OpenTelemetry is a Cloud Native Computing Foundation(CNCF) project aimed at standardizing the way we instrument applications for generating telemetry data(logs, metrics, and traces). However, OpenTelemetry does not provide storage and visualization for the collected telemetry data. An APM that can ingest telemetry data collected by OpenTelemetry can help you set up a robust observability stack.

· 7 min read
Favour Daniel

Docker containers are transient (lasting for a very short time), spawning quickly and in high numbers, which causes metrics bursts. This makes monitoring a challenge due to Docker's scaling and redeployment features. Docker stats is a built-in feature of Docker containers. The docker stats command returns a live data stream of your running containers.

· 6 min read
Ankit Anand

OpenTelemetry is a Cloud Native Computing Foundation(CNCF) project aimed at standardizing the way we instrument applications for generating telemetry data(logs, metrics, and traces). However, OpenTelemetry does not provide storage and visualization for the collected telemetry data. For OpenTelemetry visualization, you need to use a backend that can ingest the collected data and provide a web UI to visualize it.

· 11 min read
Favour Daniel
Ankit Anand

Both Kibana and Grafana are data visualization tools providing users capabilities to explore, analyze and visualize data with dashboards. The difference between Kibana and Grafana lies in their genesis. Kibana was built on top of the Elasticsearch stack, famous for log analysis and management. In comparison, Grafana was created mainly for metrics monitoring supporting visualization for time-series databases.