Top 7 Docker Monitoring Tools

June 5, 2021

DevOps teams rely on monitoring systems to detect and address performance issues faster. The use of Docker containers is rising steadily, and it is critical to get docker container log management and monitoring right from the start.

A variety of Docker container monitoring tools are available. Each of them has its strengths and weaknesses that you should carefully evaluate before choosing a tool.

This article will explain why you should monitor Docker containers and deconstruct some of the top Docker container monitoring tools.

These being:

  • MetricFire
  • Docker CLI (docker stats)
  • cAdvisor
  • Scout
  • Datadog
  • Sensu monitoring framework
  • Sematext

Why should you monitor Docker containers?

Container monitoring tools track the operation of containerized applications. Monitoring your Docker container in real-time ensures optimal system performance all the time. Docker monitoring tools assess metrics such as CPU limit, memory limit, CPU usage, real-time logs, and memory utilization.

Monitoring Docker containers enables:

  • Proactive identification and fixing of issues, thus avoiding system outages and production risks.
  • Safe implementation of changes in an entirely monitored environment.
  • Fine-tuning of systems and applications to deliver better user experience and improved system performance. This is informed by insights derived from the monitoring of time-series data.
  • Optimization of resource allocation.

Container monitoring vs container orchestration

Orchestration and monitoring are two basic concepts related to container technology. Container orchestration involves the automation of all aspects of managing and monitoring containers.

While container monitoring is focused on tracking the operation of containerized applications, container orchestration is involved in the management of containers’ dynamic environments and life cycle.

Orchestration tools provide a specific layer to the containers’ toolchains. This layer ensures proper container networking, availability, scaling, and deployment.

Docker container monitoring tools

Docker container monitoring systems collect metrics to ensure the proper performance of applications running on docker containers. These tools track and analyze metrics in real-time to assess whether an application is meeting the expected goals.


MetricFire is built on the open-source versions of Grafana, Graphite, and Prometheus. It monitors Docker containers through hosted Graphite and Prometheus. Metrics are viewed through the Grafana dashboard in real-time.

By providing hosted versions of open source platforms, MetricFire offers the same features and functionality as open-source projects. The massive community of followers constantly develops plugins and adaptations which are significant to MetricFire’s functionality.

MetricFire’s integration with Kubernetes and cAdvisor has made it an attractive tool for monitoring Docker containers.


  • It offers infrastructure monitoring, business intelligence, and app monitoring.
  • Easy and quick setup.
  • A complete ecosystem of multiple open-source monitoring platforms including Graphite, Prometheus, and Grafana.
  • It integrates multiple plugins and services into a single hosted environment.


  • It offers less control compared to in-house Prometheus/ Graphite.
  • The hosted Graphite and Prometheus are not perfect monitoring tools for all circumstances.

Docker CLI (docker stats)

Docker provides an own monitoring tool known as the docker stats command. Users need to run the docker stats command on the terminal to access a data stream for running containers in real-time.

Plus the basic metrics depicting the usage of containers’ resources. Some of these metrics are network, memory, CPU usage, and container IDs for the containers running at that present moment.

These container IDs help select metrics for individual containers in a pool of many running containers. To do this, you append the ID of the container of your interest at the end of the command.

Docker stats command displays metrics as raw data in the terminal, and data visualization is not possible with this monitoring tool. This means that you only get a glance into the container status and health.


  • Useful when you need a glance at your container status and health.


  • It gives basic statistics about the status of your Docker container.
  • Does not support data visualization.


Container Advisor (cAdvisor) is an open-source Docker container monitoring tool offered by Google Inc. You need to access and run cAdvisor’s single shipped container through a graphical interface to view the statistics for ‘dockized’ applications. This tool collects, processes, aggregates, and exports data related to the running of containers.

cAdvisor offers metrics related to a single container. Those having more than one docker host may find cAdvisor unreliable to meet their docker monitoring needs.


  • It offers a simple way to visualize Docker container metrics.
  • It provides rich information about historical resource usage and resource isolation parameters.
  • Data is stored holistically to allow easier forecasting and analysis of past performance.


  • It supports one container per host, meaning that you cannot monitor more than one host or container.


Scout is a hosted monitoring service that can address some of cAdvisor’s limitations. Unlike cAdvisor, Scout aggregates metrics from many containers and hosts. It also presents data over longer time scales and creates alerts based on specific metrics.

The Scout tool reports metrics related to memory limit, network usage, the number of running containers, and CPU usage. It also compares performance between different deployments and sends alerts based on performance and capacity issues.


  • It aggregates metrics from many hosts and containers.
  • Scout can create alerts based on specified metrics.
  • It presents data over longer time scales.
  • Has a large set of plugins that pulls in data about docker container metrics and deployment.


  • The fact that Scout does not provide information about individual containers on each host is a disadvantage to users running heterogeneous containers on the same server.


Datadog offers support for Docker containers and provides a monitoring system for logs, applications, networks, and overall infrastructure. You need to install Datadog agent to start using the services of this monitoring tool.

Datadog, like other container monitoring tools, tracks metrics such as memory usage and CPU limit. This information is available on Datadog’s customizable dashboard that has a drag-and-drop functionality. The dashboard allows users to create the graphical presentations for metrics of their choice.


  • It allows alerting.
  • It can monitor non-docker resources.
  • Offers excellent data visualization.
  • Great dashboard functionality.


  • Expensive to run for large deployments.

Sensu monitoring framework

Sensu is an open-source framework providing centralized monitoring for Docker containers. If you’re dealing with large deployments, you may consider self-hosted Sensu framework over other hosted services such as Datadog and Scout. Hosted services may get expensive with large deployments.

Sensu offers unlimited data check configurations for hosts and containers. While Sensu does not store all the data over time, it allows users to use Handlers API to send information to other tools where they can access a better data visualization over time.


  • It is a self-hosted metrics service.
  • Allows you to collect as much information about your host and docker as you want.


  • A complicated system that is difficult to deploy.
  • Limited ability to monitor non-docker containers.


As a cloud-based infrastructure monitoring service, Sematext monitors cloud systems and supports remote management and monitoring of any networks.

Sematext Agent relies on containerization to collect data on Docker performance and overall system performance statistics.

This data relates to page swaps, errors, disk I/O, and CPU and memory usage.

This tool deploys containers itself and tracks Docker events, logs, and metrics for all auto-discovered cluster nodes and containers. It has an in-built log management solution and offers faster troubleshooting and a high-performance docker monitoring system.


  • Excellent machine learning-based notifications and alerting system.
  • Offers CI/CD integration.
  • Ease of integration with other tools.
  • Easy correlation of logs and performance metrics.


  • It has no browser extension for transaction recording.


Containerized architectures and Docker, in general, are becoming more popular, and developers are creating more Docker container monitoring tools. Settling on a specific tool from a pool of docker monitoring solutions partly depends on the metrics one needs to supervise.

Each tool focuses on specific aspects of analysis and observability. There is no single tool that can meet all Docker monitoring requirements. One needs to mix these tools and develop a solution that can meet individual Docker monitoring needs.

Happy learning!

Peer Review Contributions by: Mohan Raj