Difficulties with managing Multiple Environments
One of the well-known pain points is ensuring the correct reproducibility of configurations across all environments where the working code is executed. Each environment usually requires different configurations (development, testing, staging, production). Managing and tracking configurations for multiple environments is challenging. Configurations in various environments may diverge over time, leading to inconsistency and unexpected behavior of the application, some modules, or infrastructure when releasing the final code version to production. Even with containers, infrastructure, and environment configurations may drift without a well-thought-out automation mechanism for the entire development cycle.
It is worth noting that complaints about reproducibility issues are more often observed in projects that work without containers or those hosted on-premises with unsuitable schemes and tools when the entire development and deployment cycle is not automated.
Solutions for the optimal balance
Technically, there are several possible ways to address this issue:
a) hosting each environment in a separate K8S cluster;
b) using a single cluster with multiple namespaces.
The drawback of the first approach is its high cost, but it provides:
- separation of production, development, and testing environment: for example, specifically for testing you can use a new version of Kubernetes, a service mesh, or other cluster software;
- compliance with requirements: if, according to rules, certain applications must run in separate clusters/separate VPNs;
- better security isolation;
- cloud/on-prem advantages: splitting the load between on-premise services;
This option doesn’t work for many clients because of budget limits, so there is a second approach. It involves using a single cluster with multiple namespaces. Such compromise solution allows:
- reduce setup, maintenance, and administration costs;
- decrease delays between programs in multiple clusters;
There is also another option with moderate environmental and maintenance costs. It provides secure isolation for production applications:
c) one cluster for DEV and STAGING (separated by namespaces, possibly even isolated, using network policies), another cluster for PROD.
As we can see, there are several solutions for solving reproducibility issues. They include code containerizing and automating the environment. Using for example, GitLab CI/CD with AutoDevops, you’ll ensure powerful integration with Kubernetes, allowing you to manage multiple Kubernetes clusters already supported by Helm. You can use the flexibility of Helm values to set default configurations by simply replacing them with new ones.
However, this may be difficult with low budget limits. It is desirable to gradually expand limits, using hybrid solutions, and combining different cloud services to avoid vendor lock.
What are your thoughts and experiences?
