A large investment bank was on a legacy to cloud journey. As a result, they needed a way to whip a 20 year old, highly complex, manually managed legacy application into shape - ready to utilize cloud computing. Firstly, they were looking for a cost effective and simple way to transition from physical on-premise hardware to a scalable cloud solution. Interestingly, their project had a specific requirement for peak time performance elasticity and one-touch configuration validation for deployment checks. Most importantly, they wanted to achieve these checks in minutes, not days.
Challenges of moving from legacy to cloud
Significantly, this legacy to cloud investment bank project was critical for the customer's operational resilience. For instance, the platform was using a highly manual, complex and high-risk configuration data management strategy. At the same time, a huge amount of configuration data was being consumed at deployment (6000+ items per system which was a total of over 2.2 Million). Above all, this configuration data was being manually updated, with zero validation, while simultaneously being held within a complex architecture. Unsurprisingly, this meant that configuration data changes were directly impacting application performance.
What's more, there were frequent downtime issues and high levels of support tickets. A huge amount of time was spent diagnosing simple changes and their impact on performance. Due to the complexity of the architecture it wasn't possible to have an overview of all configuration data within the application estate. With such a swathe of configuration data, it was an impossible task to cope with manually.
Ultimately, users experienced downgraded performance, especially at peak times. Since they had to retroactively fix issues caused by configuration data changes, a heap of time, money and effort was wasted. Hence their goal of cloud adoption and migration seemed even more impossible.
Intelligent configuration data management platform
By transitioning their file based configuration data into the Sweagle platform, the built-in validation and testing policies of Sweagle enabled instant configuration data management. Sweagle's topological view of the configuration data showed the impact of a configuration data change. Sweagle's templates automatically maintained the configuration data integrity and prevented contaminated configuration data entering the different environments. Sweagle enabled standardization of configuration data so the team could drive deployments confidently in a cloud-based environment. Now they can scale up and scale down as required because Sweagle transparently handles the configuration data.