Docker is a platform that enables developers to run software in packaged environments called containers. These containers are operating system (OS)-level virtualized elements that share a common Linux server yet have their software, libraries, and configuration files bundled within them. These containers can communicate with each other and exchange information, making it easier to develop and host multiple applications through the CI/CD DevOps methodology. This eliminates the need for multiple virtualized environments that have significantly high resource consumption due to multiple operating systems.
Why monitoring Docker is important
Docker’s rise in the software development sphere since its launch in 2013 has been phenomenal. Recent reports suggest that the increased adoption of Docker and containers could lead to the Global Application Container Market registering a compound annual growth rate (CAGR) of 29 percent from 2020 to 2025. The rise in adoption is not just associated with the cost benefits in deploying containers over virtual servers, but also with the flexibility of enabling applications to run in any environment: physical, public, or private cloud. When organizations rely on containerized applications like Docker to run their business services or applications, container monitoring becomes essentialto ensure high availability and performance of the applications running on them.
Why monitoring Docker is a different challenge
The Docker platform is essentially an abstraction layer for your code that enables you to make your code more portable. It makes it easier for developers to create an environment on their laptops that looks more like a production environment, easily spin containers up and down, and move them around. The orchestration layers that have been built around Docker, such as Kubernetes, make it easy to move and scale these containers without intervention. You can then build microservices made up of many containers.
While this level of abstraction offered by Docker is great for developers, it becomes a limitation for operations teams as they can’t easily determine what’s going on within their Docker environments. With full-stack docker monitoring capabilities, they can discern which hosts are running which containers, isolate individual containers exhibiting issues, and fix them before they become serious.
Monitoring your Docker host instance and its associated containers with Applications Manager
The most important parameter to consider while running any application is its server memory consumption. Deployments could fail if a cluster manager such as Docker Swarm is unable to find a host with sufficient resources for the container, so it’s vital to understand the host memory usage and the memory limits of containers. Monitoring the total memory used in each Docker host helps you know the current state of operations, and also helps in capacity planning. With Docker monitoring in Applications Manager, a quick overview of memory usage can be seen by analyzing the total number of containers and the total number of actively running containers contributing to the memory usage.
However, while a quick performance overview of your Docker instance can give you a fair idea about the status of the containers, delving into the details of individual containers can yield significant insights about their performance. Monitoring the memory utilization of containers helps you recognize differences in the application’s runtime resource consumption. The memory usage drill-down of containers can help identify if they are contributing to the heavy usage of the server memory. It’s also a good practice to understand the memory limit of a container. If out of memory (OOM) events happen, you can increase the memory limit to avoid a memory-intensive container taking up all available memory, or debug further to identify the reasons for high memory consumption.
If your container is performing slowly, you should also track the amount of CPU consumed by your containers. If no CPU limits are set on individual Docker containers, one container can use up all the available CPU on the server—mostly due to buggy applications or insufficient hardware—and affect the applications running on other containers. You can then restrict CPU utilization for particular containers to have a better handle over hardware utilization.
Monitoring network traffic is crucial to debug issues in communication and exchange of resources, especially if the communication endpoints go beyond just the browser and client. High spikes in network traffic could indicate denial-of-service (DoS) attacks, load tests, or failures in client apps.
Monitor the performance of Dockerized applications
Since the Docker container architecture can be complex and dynamic in nature, you will need to monitor across the full stack to analyze the performance of containerized applications. Let’s say your Docker production environment has a Java application that has a MySQL database as a backend. You will need to track application-level metrics and identify erroneous lines of application code while keeping an eye on the MySQL operations. Tracking key performance metrics of your applications in this fashion will help you ensure maximum availability and optimize performance for containerized applications.
Identifying performance anomalies and taking troubleshooting actions
To troubleshoot problems effectively in Docker environments, you need to become aware of problems with the hosts, container resources, and the application to accurately assess user experience. Diagnosing an issue is often the most time-consuming part of a troubleshooting process, and Docker monitoring software can help a great deal in this regard. Along with identifying and notifying users about a performance issue, an ideal Docker performance monitoring tool should be able to both notify you about threshold breaches, and automate corrective actions such as starting, stopping, or restarting Docker containers.
Forecasting performance trends
Predicting the resource usage and growth of your Docker instances in the future is only possible by analyzing historical performance trends. Daily, weekly, and monthly performance trends can help you understand trends based on given time periods, and reveal insights about capacity planning. This can help you stay proactive with regards to Docker performance monitoring by ensuring that the hosted applications always have the resources and memory available for smooth functioning.
The incredible efficiency and portability of containers and microservices in the software development field has led to organizations increasingly adopting technologies like Docker. Given the importance of these platforms for application development and hosting, it’s prudent to employ a comprehensive Docker monitoring solution to steer clear of errors that might compromise performance.
ManageEngine Applications Manager offers in-depth monitoring for your Docker instances and its containers, among over 130 other business applications, ensuring that you gain full visibility into your stack. It enables you to correlate container and host metrics, alongside application performance metrics and Kubernetes metrics, helping you to identify root causes for poor application performance and better understand overall availability and performance, all from a single dashboard. It also supports both static and adaptive thresholds, and enables you to send alerts to email, Slack, or use a JSON-based webhook.
If you’re new to Applications Manager, learn more or explore on your own with a 30-day free trial!