Continuously validated configuration data supports DevOps integration
A large global insurance company has improved the way they manage their integrated DevOps application estate. Thanks to Sweagle, they are achieving faster, more secure, and more reliable technology releases. Mounting industry competition was pressuring them to invest in technology-driven reinsurance. This would help to handle client risk assessments. They knew they needed to apply automation of configuration data to their CI/CD pipeline. Consequently, they would achieve their business goals and deliver value back to their clients. But how?
With more than 100 applications deployed automatically through Jenkins, from DEV to PROD, the number of configuration data items was well over 35,000. As a result, it was impossible to check all parameters - for every application - before each new release. Inevitably, issues crept into the SDLC. So, how did they move from a semi-automated DevOps organisation to a fully optimised one with empowered teams?
Why did they need continuous validation throughout the release pipeline?
First of all, there were a few requirements that were high on their list. A high rate of errors in their build pipeline was causing issues, delays and time to investigate. The route cause was most frequently caused by configuration data issues. The customer knew they could gain faster releases, greater reliability and an improved performance if they put in a quality gate.
What's more, their technical requirements included the following aims:
- Seamless integration into the pipeline
- Continuous and automatic validation of configuration data
- Quicker root cause analysis with environment comparison
- Security with role based access control (RBAC) and automatic encryption
Alternatively, they could continue to manage the process manually, or simply do nothing at all. However, to maintain market position as a leading reinsurance provider, the latter was clearly not an option.
What was the CI/CD landscape?
As an illustration, CI/CD pipeline tooling of the customer is laid out in this diagram. On the left, it shows examples of key sources from where Sweagle consumed configuration data. While on the right side, there are the CI/CD tools that consumed the validated configuration data once it was consolidated. Sweagle handled this without intruding on the CI/CD set up. Similarly, Sweagle performed its validations in a fully automated manner.