Docker Monitoring Tools for Docker Container

Docker monitoring involves viewing and tracking metrics to ensure Docker containers are functioning optimally. Docker is a rapidly emerging DevOps tool. Docker packs, ships, and runs applications as lightweight, portable, self-sufficient containers capable of running on different platforms. The tool’s containers are especially useful for environments aiming to scale rapidly.

More lightweight than physical machines or virtual machines, these containers offer enhanced security by providing extra isolation. They act as “mini-hosts” to enable sets of applications to run independently. But since containers aren’t virtual machines (VMs) or physical machines, they bring new network and configuration issues. Docker containers are neither operating systems nor applications, and organizations cannot rely on traditional monitoring software to handle Docker performance monitoring.

Docker monitoring requires collecting different metrics from different system components affecting container performance, including data from hosts, containers, and databases. Docker performance monitoring is necessary to detect issues before they cause production-level issues and to ensure applications in Docker containers are running smoothly. 

Docker monitoring works by tracking metrics affecting the functioning of Docker containers. By ensuring problems are detected and addressed early on, organizations can optimize the performance of containerized applications. Containers have a shorter life span than typical hosts. Since Docker containers operate between hosts and applications, effective monitoring should include:

• Monitoring CPU and memory use in the host and applications. Docker performance can be impacted by the availability and performance of these resources.
• Monitoring performance metrics for individual Docker containers. Docker container monitoring can refer to tracking metrics pertaining to the individual containers running virtual hardware separately from one another. Tools like cAdvisor can be used as a metric collector.
• Monitoring containerized applications. Application monitoring helps identify issues with Docker environments and help troubleshoot problems before they become serious.

Docker performance monitoring can be done with different software—often including open source tools like Prometheus and visualization platforms like Grafana—usually offering an integrated dashboard for monitoring different metrics across your network architecture. Docker container monitoring tools can send alerts when resources are at low availability or when they exhibit performance issues, notify the user when individual containers are using excessive resources, and enable capacity planning. They often pull data from a dedicated API endpoint.

Docker monitoring is important because Docker containers are often used by organizations looking to scale often and release quickly. Throughout this process, they need to ensure their applications are running with maximum uptime.

Monitoring is an important way to optimize the performance of containers. But Docker monitoring can encounter limitations when using traditional monitoring tools for hosts and applications. Containers add a new tier to the infrastructure different from hosts and applications. At the same time, most organizations run multiple Docker containers. Monitoring host CPU and memory availability is important, but it’s not enough to show you individual containers hitting resource limits. Monitoring metrics for individual containers would alert users to critical problems with specific containers, including potential security vulnerabilities.

Docker container performance monitoring can also be difficult. Container orchestration tools like Kubernetes can allocate containers to different hosts and move them from one host to the next, depending on the availability of resources. It’s not enough just to monitor hosts. Docker container performance monitoring involves figuring out which hosts are running which containers, isolating individual containers exhibiting issues, and addressing them before they become critical.

Setting up Docker monitoring can be complicated. Instead of monitoring the server, Docker monitoring tools can be set up by tagging or labeling containers and collecting metrics for the container and neighboring containers instead of the host. Instead of treating containers like hosts, you can identify problems occurring in the container layer and troubleshoot them before they impact application performance.

Developers are generally seeking to figure out where application problems are coming from, whether they arise from the host, containers, or application servers. Effectively building Docker monitoring solutions requires three layers. You need to install tools to collect metrics from Docker containers (often using plugins or interacting with the Docker daemon), then correlate real-time metrics from Docker containers with metrics from the host and applications to identify issues and their impact. This often requires significant automation and integration into CI/CD pipelines (source code for many of these tools can be found on GitHub). You also need a tool to visualize performance metrics on a dashboard to run queries and receive alerts. Depending on the requirements and priorities of your environment, you may have to install multiple tools to carry out Docker performance monitoring. Check the official docs for specific tools like docker-compose for setup examples.

Docker monitoring tools help DevOps pros monitor the performance of Docker ecosystems by using different metrics. Monitoring Docker containers help ensure containerized applications run optimally and Docker containers are used efficiently and productively.

Since Docker containers require resources from hosts and enable the running of multiple applications, Docker performance monitoring requires full-stack monitoring and dealing with the changing placement of containers. Constant monitoring is necessary to ensure optimum system performance in different environments.

Instead of traditional server monitoring that looks at CPU utilization and memory use for the host, Docker monitoring tools can pull stats from individual containers at different moments during their runtime and visualize them on a dashboard. This way, users can tell if individual containers are failing and reallocate resources if necessary.

Some Docker container monitoring tools also enable users to employ metrics to improve server capacity planning by redeploying containers to different hosts and forecasting resource depletion. Docker monitoring tools can also contextualize container performance in relation to other performance metrics, for instance, host performance, application uptime, and server speeds. This way, users can identify problems and troubleshoot them quickly. The overall pricing of the solution is often tied to the volume of the collected data source. Many tools can run either integrated or standalone.

By using Server & Application Monitor, you can carry out Docker performance monitoring to help identify issues and improve availability. SAM is built to monitor applications using Docker container architecture to track key performance metrics to help ensure maximum uptime and optimize performance for containerized applications.

SAM offers a dashboard to enable users to monitor performance metrics through the added layer of Docker containers. It enables users to view underperforming containers exhibiting issues and nearby containers in the same host for troubleshooting purposes. SAM also logs performance information for historical analyses.

SolarWinds SAM Docker resource monitoring tool also helps forecast capacity depletion. By correlating metrics from multiple containers, users forecast future problems like capacity depletion. By figuring out average peak loads and times, users can also plan around the limited availability of resources.

SAM is built to allow you to more easily correlate metrics from containers, hosts, and applications. Users can then determine where the root cause of performance issues lies and limit any damage that may ripple from localized problems. By monitoring and alerting on server and infrastructure problems, SAM helps you optimize server application performance and get the most out of Docker containers.