Moving a monolithic application to a modern cloud architecture can be difficult and often result in a greenfield development effort. However, it is possible to move towards a cloud architecture using Docker Enterprise Edition (EE) with no code changes and gain portability, security and efficiency in the process.
Part 4 takes advantage of the messaging service I added in part 3. In this installment, I’ll add self service analytics powered by the open source Elasticsearch / Kibana stack. The reporting database and analytics UI run in containers and the worker is updated to also store data in Elasticsearch. The Docker platform supports adding new components to a running deployment without shutting down the application containers that are currently running. You’ll learn how Docker lets you add new capabilities to the application with zero downtime in production.
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