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Markus77
Mission Specialist
Mission Specialist
  • 4,461 Views

Optimize container image in Openshift

Hi everyone, how can I optimize a container image in openshift?

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14 Replies
Matthee
Mission Specialist
Mission Specialist
  • 2,445 Views

A container image in OpenShift can be optimized in a number of ways to increase performance, decrease size, and boost overall effectiveness. The following are some strategies you can use:

  1. You can start with a Minimal basis Image: Create a minimal basis image that only contains the elements that your application need. Popular options include Red Hat Universal Base Image (UBI) and Alpine Linux. The size of your final container image can be drastically reduced by using these small base images.
  2. Remove Unnecessary Dependencies: Examine the dependencies of your application and remove any unused libraries or packages. By reducing the attack surface and shrinking the image size, security is enhanced.
  3. Use multi-stage builds to keep the build environment isolated from the runtime environment. This enables you to create your application in a single step and copy only the runtime artifacts that are required. You can produce pictures that are smaller and more effective by removing build-time dependencies.
  4. Pay attention to your Dockerfile's instructions and make sure they are optimized for maximum performance. Use multi-line commands to group together related instructions, for instance, and take advantage of caching to minimize needless rebuilds when the source code hasn't changed.
  5. Utilize Image Layers: Recognize how Docker image layers function and organize your image to maximize layer reuse. To have the least amount of influence on cache and layer reuse, move frequently changing components to the end of the Dockerfile.
  6. Utilize Build Strategies: Source-to-Image (S2I) and buildah are two build strategies offered by OpenShift that offer quicker methods for creating container images. Investigate these possibilities to streamline the creation of images and possibly lower the size of the final product.
  7. Image Compression: To reduce the size of your container image, use programs like gzip or zstd. In order to further reduce picture size, OpenShift additionally offers options for image compression during the build process, such as the oc new-build --compression flag.
  8. Configure a Secure Registry Pull policies in OpenShift to make sure that only essential images are downloaded and saved locally. By doing so, network overhead is decreased and storage space is preserved.
  9. Implement CI/CD pipelines to automate image creation, testing, and deployment. CI/CD stands for continuous integration and continuous deployment. By doing this, it is ensured that throughout the development and deployment lifecycles, optimized pictures are consistently produced.
  10. Monitoring and Analysis: Analyze the resource utilization and performance of your container images on a regular basis. You can find chances for improvement by using tools like the built-in monitoring and logging features of OpenShift as well as third-party tools like Prometheus and Grafana.

These methods can help you optimize your container images in OpenShift, which will boost performance, use fewer resources, and be more effective all around.

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YogeshKadiya
Flight Engineer Flight Engineer
Flight Engineer
  • 1,062 Views

* You can build an application and then transfer it to a new clean environment to deploy. It will ensure that only the necessary runtime libraries and dependencies are part of the final image.

* When building an image, pay attention to the layers created by ContainerFile. Each RUN command creates a new layer. So combining the layers can reduce the image size.

* Enable image caching. If you need multiple instances of the same layers, it’s a good idea to look at optimizing the layers and creating a custom base image. It will speed up load times and make it easier to track.

* Test images require more tools and libraries to test out features. It’s a good idea to use the production image as the base and create test images on top of it. The unnecessary test files will be outside of the base. So production images will stay small and clean for deployment.

* Storing application data in the container will balloon up your images. For production environments, always use the volume feature to keep the container separate from the data.

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otaviokr
Cadet
Cadet
  • 985 Views

Hi @Markus77 

This is a question that touches a lot of different topics, and probably, there will always be that "one more thing" you could fine tune to improve it even better.

Starting with the very basic and more generic subjects:

- use the correct base image. If you have a very simple Python script that just perform some text files operation, you don't need to use a base image that comes with a complete installation of Django. On the other hand, don't go always for the bare minimum Linux image and install everything you need manually - if there is already a base image that contains everything you need (or, at least, most of the things you need), use that as a base image and add just the missing details, if any.

- split the build process. This is a very common use case when you are working with Go applications, for example. Instead of having an image that will contain all the libraries to compile you Go application (and that you won't need once the application is ready for deploy), you can create a temporary contianer that will just compile and package your application and then generate an image with the newly compiled application copied into it, without the additional libs and packages.

- understand the layered composition of an image. This could be a little too much for someone who just got started, but it is easier than it looks. Basically, each instruction in an image becomes a layer on top of the previous. This can be improved by grouping some instructions together or changing the order some instructions are executed, but this is a very big topic, and we can talk about this later and focusing more on your use case, if you wish. Just keep in mind that not all images are created equally

Like I said, this is a very big topic and it has many possible subtopics to cover. My suggestion is to give it a try to each of the options I posted to see which one has the best result. Even better, try mixing more than one of those!

Of course, if you are willing to share more details about your particular case, we could discuss other, more specific, possible alternatives...

Marnord
Mission Specialist
Mission Specialist
  • 867 Views

Hi Markus,

this is sometimes a mix of science and art, as you probably already understood from the above replies.

Most of the tips usually focus on optimizing the image size, which is very important with S2I or DevOps pipeline that retrieve the image during frequent rebuilds and redeployments.

Since you already have a lot of tips on that, I would address your question from a different angle: what does optimisation means to you this case?

Optimising may mean securing, not only by lowering the footprint (deleting and cleaning unneeded packages as part of the Containerfile) but also by limiting user access and including code/package security analysis.

It may mean faster builds, therefore limiting the Containerfile lines rather than trying to slim the image at all costs.

In the end... it may even mean easier container troubleshooting (in the case of dev images, not in production!), thus adding basic tools that may ease your life if you're forced to analyze the internal runtime behaviour.

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Marnord
Mission Specialist
Mission Specialist
  • 867 Views

Hi Markus,

this is sometimes a mix of science and art, as you probably already understood from the above replies.

Most of the tips usually focus on optimizing the image size, which is very important with S2I or DevOps pipeline that retrieve the image during frequent rebuilds and redeployments.

Since you already have a lot of tips on that, I would address your question from a different angle: what does optimization mean to you this case?

Optimising may mean securing, not only by lowering the footprint (deleting and cleaning unneeded packages as part of the Containerfile) but also by limiting user access and including code/package security analysis.

It may mean faster builds, therefore limiting the Containerfile lines rather than trying to slim the image at all costs.

In the end... it may even mean easier container troubleshooting (in the case of dev images, not in production!), thus adding basic tools that may ease your life if you're forced to analyze the internal runtime behaviour.

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