Log analysis is a very powerful feature for an application when it comes to debugging and finding out which flow is working properly in the application and which is not. In a world of containerization and cloud computing, it is essential to understand logs generated by a Docker environment to maintain healthy performing applications.
Logs are useful for troubleshooting and identifying issues in applications, as they provide a record of events and activities. However, managing log data can be challenging due to the large volume of log events generated by modern applications, as well as the need to balance the level of detail in the logs and the impact on the application's performance.
Modern-day software systems emit millions of log lines per minute. Cloud computing and containerization have made it easy to have distributed systems. Distributed systems emit logs from multiple sources. While developers have always used logs to debug stand-alone applications, centralized logging solves the challenges of modern-day distributed software systems.
Kubernetes has since emerged as “THE” container orchestration platform for deploying and managing containerized workloads as a result of its robust capabilities. However, the complexity of its architecture and its dynamic nature present significant challenges in monitoring deployed workloads and the platform itself.
Information about the containers and pods on your cluster may be obtained using the kubectl logs command. These logs allow you to know the performance of your applications, whether they are failing or healthy, and are particularly useful for debugging and troubleshooting purposes.
Kubectl Top command can be used to retrieve snapshots of resource utilization of pods or nodes in your Kubernetes cluster. Resource utilization is an important thing to monitor for Kubernetes cluster owners. In order to monitor resource utilization, you can keep track of things like CPU, memory, and storage.
The kubectl logs tail command is a tool that allows users to stream the logs of a pod in real-time while using Kubernetes. This command is particularly useful for debugging and monitoring applications, as it enables users to view log output as it is generated and quickly identify any issues or problems with their application.
Microservices logging is the practice of tracking and recording the activities of specific services in a distributed microservices architecture. Logging is an important aspect of any software system, and it is more critical for a microservices architecture as there are many small, independent services interacting with each other.
Elasticsearch is primarily a search engine optimized for fast, complex search queries, especially text searches, and is often used for log and event data analysis. MongoDB, on the other hand, is a general-purpose, document-oriented database that excels in storing and retrieving structured and semi-structured data. It is commonly used for mobile, social, and IoT applications. While Elasticsearch provides superior search capabilities, MongoDB offers more robust data processing and storage features.
It is essential to configure log rotation for Docker containers. Log rotation is not performed by default, and if it’s not configured, logs on the Docker host can build up and eat up disk space. This guide will teach us how to set up Docker log rotation.