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Containers and databases

In the last months we got more and more requests for supporting MariaDB/MySQL/Galera Cluster in (mostly Docker) containers.

Because of its additional layer and added complexity I do not like containers much. Containers are more complicated during troubleshooting and debugging problems.

Other people have already written more than enough about the advantages of containers. What is more difficult to find are the disadvantages of technologies. Thus I focus on those:

Wrong technology?

Container solutions were designed to deal with stateless applications that have ephemeral data. Containers spin up a quick microservice and then destroy it. This includes all the components of that container (including its cache and data). The transient nature of containers is because all of the components and services of that container are considered to be part of the container (essentially it is all or nothing). Serving the container a data volume owned by the underlying O/S by punching a hole through the container can be very challenging.
Most of the development efforts put into the various solutions had one goal in mind: Statelessness. There are solutions that can help keep your data persistent, but they are very quickly evolving. They require a high level of complexity, that negate any efficiency gains due to increased operational complexity (and risk). [1]


These container solutions are meant for quick development and deployment of applications that are broken into tiny components: microservices. Normally, these applications evolve very quickly in organizations that are very software/developer-driven. That seems to be how these container solutions (again, especially Docker) are developed as well. New features are pushed out with little testing and design. The main focus seems to be the latest feature set and being first to market. They “beg for forgiveness” instead of “ask for permission.” On top of that, backward compatibility is a distant concern (and even that might be an overstatement). This means that you are going to have to have a mature Continuous Delivery and testing environment as well as a known and tested image repository for your containers. [1]

We have seen complaints about Galera Cluster stability issues inside Docker containers. The signs were pointing without doubt to network issues. If these were real network issues or just container network issues we could not find out yet.

Networking can be tricky in containers world when you want to limit the access within containers and also have proper network communications where required. [3]

Docker might even make your application slower. If you are working with it, you should set limits on how much memory, CPU, or block I/O the container can use. Otherwise, if the kernel detects that the host machine’s memory is running too low to perform important system functions, it could start killing important processes. If the wrong process is killed (including the Docker itself), the system will be unstable.


We have heard reports that performance overhead of Docker containers can be up to 10%. If this is still true with the right configuration and and recent version must be shown. [2]

You should not expect Docker to speed up an application in any way. [5]


Since there is no full operating system people tend to overlook the security aspect of containers, but if you look up online, you will see that hackers are targeting systems that are hosted in containers and not secured properly.
Since the containers use the same kernel, they are not 100 isolated, so you should be aware of the risks if you are using multiple containers in one server, and make sure you know what you are doing and which containers are running on the same kernel along with your stuff! [3]

All containers share access to a single host operating system. You risk running Docker containers with incomplete isolation. Any malicious code can get access to your computer memory. [5]

Running applications with Docker implies running the Docker daemon with root privileges. Any processes that break out of Docker container will have the same privileges on the host as it did in the container. Running your processes inside the containers as a non-privileged user cannot guarantee security. It depends on the capabilities you add or remove. To mitigate the risks of Docker container breakout, you should not download ready-to-use containers from untrusted sources. [5]

Data storage is intricate – By design, all of the data inside a container leaves forever when it closes down except you save it somewhere else first. There are ways to store data tenaciously in Docker, such as Docker Data Capacities, but this is arguably a test that still has yet to be approached in a seamless manner. [6]

Container O/S is the same as host O/S. If the host O/S is upgraded all the containers get also a new O/S.

Popular docker images have many vulnerabilities. So build and harden your images yourself. [10, 11, 12]

One of the most famous Docker security vulnerabilities can be found here: Alpine Linux Docker Images Shipped for 3 Years with Root Accounts Unlocked and Alpine Linux Docker Image Vulnerability CVE-2019-5021 and Docker Image Vulnerability (CVE-2019-5021).


Containerization also means consolidation. And as in consolidated systems usually you can have side effects or effects caused by someone you did not expect.


Debugging problems in a container environment becomes more complex because the many additional layers added. Then the necessary information and metrics are not there or not available in the way as expected. This makes troubleshooting more complicated.


Docker implementation is quite complex. A load of technological supports are necessary for Docker implementation including orchestration, container management, app stack, data screenshots, networking of containers, and so on.

The container ecosystem is split – But the core Docker platform is open source, some container products do not work with other ones. [6]


Container technologies require kernel features which were not present in earlier kernels. This made system maintenance more complicated. This problem may have been solved in the meanwhile?

If you are aware of any other disadvantage not mentioned above please let us know. Some of these disadvantages might have been reduced in the recent years.


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Are containers so popular because application developers do not know how to write multi-threaded applications well? With containers you can circumvent this problem a bit. You ramp up man single threaded applications in containers and thus get a multi-threaded behaviour.
Databases ARE already multi-threaded. So no need to containerize them.