You are currently viewing What is Docker Memory Limits: A Comprehensive Guide

What is Docker Memory Limits: A Comprehensive Guide

When you’re running Docker on your system, it tends to accumulate a significant amount of files, filling up system memory. To keep your storage clean and free up space, one of the best strategies is to set a memory limit. There are a lot of situations in which we need to restrict the amount of resources that are used on the distributed container host system.

As the leading experts in Docker consulting services, we’ve made this in-depth guide on Docker memory limits to make the process easy for you. In this blog, we’ll walk you through the steps to set memory limits, ensuring a smoother and more efficient Docker experience. Take a moment to explore this blog and get a clear understanding of the entire process.

Understanding Docker Memory Limits

What Are Docker Memory Limits?

In the Docker ecosystem, memory limits refer to the maximum amount of RAM (Random Access Memory) that a container can use while running. Docker allows you to set these limits to ensure that a container doesn’t consume excessive memory, which could potentially impact the performance of the host system and other containers. Docker’s memory management is crucial for maintaining system stability and ensuring that your applications run smoothly within their allocated resource boundaries.

Why Are Docker Memory Limits Important?

1. Resource Isolation: Containers share resources with the host and other containers. Setting memory limits ensures that a container doesn’t monopolize the system’s memory, allowing for fair resource allocation.

2. Predictable Performance: Docker Memory limits help maintain predictable performance. When a container exceeds its memory limit, it can slow down or even crash, potentially affecting other containers.

3. Resource Efficiency: By defining memory limits, you prevent resource waste. Containers use only the memory they need, reducing the chances of over-provisioning.

4. Enhanced Stability: Keeping memory usage in check enhances the overall stability of the host system and other containers. It minimizes the risk of out-of-memory issues.

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Set Docker Memory Limits

You can set how much memory a Docker container uses in different ways. These are some things that you can do:

  • You can set the most memory a container is allowed to use.
  • You can decide how much memory a container can use from your computer’s storage.
  • You can set a soft limit for the amount of memory a container gets.

Let’s learn how to set or configure Docker memory limits.

Set Maximum Memory Access

If you want to restrict how much memory a container can use, you can do this by adding the –memory option when you run the container using the docker run command. You can also use the shorter version, -m. In this command, you need to specify the amount of memory you want to assign to that particular container. Here’s how the command should look:

sudo docker run -it --memory="[memory_limit]" [docker_image]

When you set the memory_limit, the value should be a positive whole number followed by a suffix: ‘b’ for bytes, ‘k’ for kilobytes, ‘m’ for megabytes, or ‘g’ for gigabytes. For instance, if you want to limit a container to use 1 gigabyte (GB) of RAM, you would use –memory=”1g”.

For example, if you want to run an instance of an Ubuntu container with a docker memory limit of 1 GB, you’d use the following command:

sudo docker run -it --memory="1g" ubuntu

This ensures the container doesn’t use more than 1 GB of memory.

Set Swap to Disk Memory Limit

You can use the swap option to allocate extra memory space on your disk even when your container’s RAM limit has been reached. This can be helpful, but it’s not the best practice because it can slow down your container’s performance.

To configure this additional RAM space, you should first set your maximum RAM limit using –memory. The swap memory includes both the non-swap memory and the backup swap memory.

For instance, if you’ve set –memory to 1 gigabyte (GB), as shown in the previous example, your swap memory should be greater than that. To run a container with an additional 1 GB of swap memory, you’d set the swap memory to 2 GB.

To run a container with limited memory and additional swap memory, you can use the following syntax:

sudo docker run -it --memory="[memory_limit]" --memory-swap="[memory_limit]" [docker_image]

This command ensures that the container can use up to 1 GB of RAM and an additional 1 GB of swap memory if needed.

If you want to run a container using the Ubuntu image, providing 1 gigabyte (GB) of RAM for the container to use and reserving an extra 1 GB of RAM for swap memory, you can do it like this:

sudo docker run -it --memory="1g" --memory-swap="2g" ubuntu

This command sets up the container with a maximum of 1 GB of RAM and an additional 1 GB of swap memory in case it’s needed.

Set Soft Limit to Container Memory

When you use –memory to limit a container’s memory usage, you’re essentially creating a strict, unbreakable limit that the container can’t exceed. However, you can also set a soft limit using –memory-reservation. This soft limit serves as a warning that alerts you when the container is approaching its allocated memory but doesn’t halt any of its processes if it exceeds that limit.

If you haven’t set any –memory limitations, using –memory-reservation won’t fully restrict the container’s memory usage. When both –memory and –memory-reservation are active, the soft limit is always lower than the maximum memory capacity.

For example, to run an Ubuntu container with a memory reservation of 750 megabytes (MB) and a maximum RAM capacity of 1 gigabyte (GB), you can use this command:

sudo docker run -it --memory="1g" --memory-reservation="750m" ubuntu

This command sets a strict 1 GB memory limit with a soft limit of 750 MB for the container. If the container’s memory usage approaches 750 MB, you’ll receive a warning, but it won’t stop any container processes.

Monitoring Memory Usage

Setting docker memory limits is just the first step. Monitoring memory usage is equally important to ensure that your containers operate within their defined limits.

Docker provides tools and commands to monitor memory usage:

1. docker stats

The docker stats command displays real-time container resource usage, including memory. It provides a quick overview of how much memory each container is consuming.

docker stats

2. Docker Dashboard

Docker Desktop and Docker Enterprise offer graphical interfaces where you can view resource usage for containers. The dashboard provides detailed insights into memory consumption and other resources.

3. Third-party Monitoring Tools

There are third-party monitoring and orchestration tools, such as Prometheus and Grafana, that can provide more advanced insights into container resource usage, including memory.

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Best Practices for Managing Docker Memory

To ensure effective memory management in Docker, consider the following best practices:

1. Size Containers Appropriately: When creating containers, ensure they are appropriately sized to match the workload. Overly large containers can waste resources, while overly small ones can lead to performance issues.

2. Define Memory Limits: Always set docker memory limits for your containers to prevent them from consuming excessive resources. Define limits based on the application’s requirements.

3. Monitor Resource Usage: Regularly monitor memory usage using Docker’s built-in tools or third-party solutions. This helps you detect and address issues early.

4. Optimize Application Code: Review and optimize your application code to be memory-efficient. Eliminate memory leaks and unnecessary resource usage.

5. Implement Auto Scaling: Consider implementing container autoscaling to dynamically adjust the number of containers based on resource demands. This helps maintain performance during traffic spikes.

6. Regularly Update Containers: Keep your containers and their base images up to date to benefit from performance and security improvements.


Docker memory limits are a fundamental aspect of effective container management. By understanding their importance, setting appropriate limits, and monitoring memory usage, you can ensure that your containers run efficiently and do not impact the performance of the host system or other containers. With these best practices in mind, you can harness the full power of Docker while maintaining control over memory resources.

With this blog, we’ve provided you with easy-to-follow steps on how to set docker memory limits, making your Docker usage more efficient and hassle-free. If you want to know more information and guidance on Docker memory management, you can explore our Docker consulting services on our official website. We offer expert support and solutions to optimize your containerized applications and infrastructure.


Q1. What are Docker memory limits?

Docker memory limits define the maximum amount of RAM a container can use while running. They prevent containers from monopolizing system memory, ensuring fair resource allocation.

Q2. Why are Docker memory limits important?

Docker memory limits are crucial for resource isolation, predictable performance, resource efficiency, and enhanced stability. They prevent containers from using excessive memory, maintaining a stable and efficient environment.

Q3. How can I set maximum memory access for a Docker container?

Use the –memory option with the docker run command. For example, docker run –memory=”1g” limits a container to 1 gigabyte of RAM.

Q4. How can I set a soft limit for Docker container memory?

Use –memory-reservation to set a soft limit. It warns when approaching the limit but doesn’t halt processes if exceeded.

Q5. What are the best practices for managing Docker memory?

Size containers appropriately, define memory limits, monitor usage, optimize application code, implement auto-scaling, and regularly update containers for efficient Docker memory management.

Q6. Why is setting Docker memory limits important for efficiency?

Setting Docker memory limits ensures efficient resource usage, prevents performance issues, and allows for effective management of containerized applications.