Docker containers are well known for their speed, and this is the main reason that Docker containers are preferred over virtual machines. One needs to carry out Docker performance tuning to get lightning-fast docker container speeds. Even Though when we compare docker vs kubernetes we realize that both of these can be simultaneously utilized at different levels for better performance, here in this article we will focus mainly on improving docker speed by performance tuning.
Do not add extra information in a container image, only add the necessary information. The fewer number of components and code inside the image the faster and better the performance. To do this you have to build a docker file that will consist of: files to be added, important environment variables, steps for installation, networking details, and the codes or commands to use. The file context of a docker file also affects the performance. To modify this section add the unnecessary files to the docker ignore file so that this can be excluded from your over final build.
speed of a docker container you can use the build cache option. If some docker files having changed the existing layers of your local image stored in the cache can be reused. Once again you need to design a docker file to use the cache. You need to ensure that you minimize the cashier invalidation by only copying the file that is required for the next step. Adding a command early in the docker file that always changes, can also invalidate the cache accidentally. Avoiding these two steps can ensure that your cache is utilized in a proper way to improve the speed of the docker container.
Docker has excellent community support and has a build for microservices. A docker container will have to run very few codes if it hosts a microservice. if you use microservices and dockers together one of the most fruitful outcomes is high speed.
Dockers that are hosted on virtual machines are slower than the ones that hosted on bare metal servers. Another thing that you can do is to install a docker using the hyper version and run the docker inside it.
Sometimes apart from the docker other factors that affect the docker speed also need optimization. The infrastructure or the application affects the overall speed of the docker too. If even after Docker performance tuning the speed doesn’t improve you can solve the problem by solving other issues. Visualization tools help you understand the software execution. Application logs also display the application performance details. These two things come in handy while troubleshooting and testing other parameters to improve docker speed.
every software docker also comes with its own set of default settings. To improve the memory I need to configure your talk accordingly to recover the memory lost when the host machine runs. You have together container metrics for which you can use docker stats commands or docker REST API. These statistics and data mainly help us for the purpose of performance debugging.
We have gone through various techniques like reducing docker build time creating our own files and also studying container data for performance assessment. Apart from the internal docker factors when the external services and applications play a key role in determining the docker container speed. You can also do docker online training to learn more about docker performance tuning. Keeping all this in mind I will help you understand your docker container better and improve its build and run time performance.