Today’s enterprises are in the midst of digital transformation, but they’re hampered by monolithic, on-prem legacy applications that don’t have the speed, agility and responsiveness required for digital applications. To make the transition, enterprises are migrating to the cloud. MongoDB has partnered with PeerIslands to develop 1Data, a reference architecture and solution accelerator that helps users with their cloud modernization.
This post details the challenges enterprises face with legacy systems and walks through how working with 1Data helps organizations expedite cloud adoption.
Modernization Trends
As legacy systems become unwieldy, enterprises are breaking them down into microservices and adopting cloud native application development. Monolith-to-microservices migration is complex, but provides value across multiple dimensions. These include:
- Development velocity
- Scalability
- Cost-of-change reduction
- Ability to build multiple microservice databases concurrently
One common approach for teams adopting and building out microservices is to use domain driven design to break down the overall business domain into bounded contexts first. They also often use the Strangler Fig pattern to reduce the overall risk, migrate incrementally, and then decommission the monolith once all required functionality is migrated. While most teams find this approach works well for the application code, it’s particularly challenging to break down monolithic databases into databases that meet the specific needs of each microservice. There are several factors to consider during transition:
- Duration. How long will the transition to microservices take?
- Data synchronization. How much and what types of data need to be synchronized between monolith and microservice databases?
- Data translation in a heterogeneous schema environment. How do the same data elements are processed and stored differently?
- Synchronization cadence. How much data needs syncing, and how often (real-time, nightly, etc.)?
- Data anti-corruption layer. How do you ensure new data doesn’t corrupt the old data and ensures transaction data integrity?
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