Continuously validated configuration data

Customer success stories

How an insurance provider continuously validated configuration data to reduce risk, cost & bottlenecks

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.

Consolidated config CICD landscape

How did Sweagle integrate with the CI/CD pipeline?

Firstly, the Sweagle platform seamlessly integrated into the Jenkins pipeline. Thanks to Sweagle's API-based technology, it imported all configurations automatically each time a deployment was made. Sweagle's data model auto-generated to provide the customer with a full picture of their application estate. Indeed, this insight was something the customer had never achieved before.

In the next step, Sweagle expanded to 100+ applications. The platform automatically imported configuration elements for every deployment, continuously. Sweagle's in-built validators checked for configuration changes. For instance, it discovered and encrypted any sensitive data. This gave the customer immediate security and management of secrets within all their configuration data files.

Example data model auto-generated by Sweagle

Dealing with automated deployments

To recap, the configuration data files required for the automated deployments were auto-generated by Sweagle. This entire process was controlled through Sweagle's granular RBAC capabilities. Then, the right teams had the appropriate level of access to edit and make changes. What's more, Sweagle automatically created a fully auditable history of configuration data changes. With just a click, they could interrogate the configurations from any environment, at any point in time. Not only did Sweagle auto-generate the configuration data but, at the same time, it validated it. Importantly, Sweagle applied its validation rules before any changes were ever applied. Consequently, the customer had more confidence in their releases, more agility and higher throughput to their CI/CD pipeline.

The outcome

The insurance provider's DevOps teams are now autonomous. They have real time read access to Production configuration data for debugging and monitoring purposes. Put another way, the customer realised its vision for DevOps to edit DEV/TEST environments, whilst only seeing PROD configuration data (minus sensitive data). In addition, the Sweagle configuration data management platform generated accurate files for deployment and removed any configuration data files from legacy repositories. In conclusion, all configurations now run through Sweagle with every item managed, validated and secured - on demand - regardless of format.

Harnessing the hidden force of machine learning

Technical video

Learning outcomes of the session:

  • Pay back from a machine-learning enabled configuration data management strategy (short, medium, long-term)
  • Get your configuration data management down to zero effort with machine-learning intelligence
  • Gain insights that you could never come up with alone

Don't miss this opportunity to enhance your configuration data management across the application estate.