Evolving systems for new products

  • A common anti-pattern to avoid is preemptively optimizing systems for the future while still trying to establish the current market fit. It leads to slower iterations between product experiments.
  • You can try to expedite the development by reusing existing systems and tooling.
  • Evaluate your business logic performed at read time to identify what data was shared with an application to enable better data modeling and quick, small product changes.
  • Be alert to scaling challenges and set new goals accordingly. For example, you might perform nightly load tests to catch issues and decide to reduce the complexity of a system to quickly develop on the backend in response to new feature requests.
  • For a design that lasts in the future, you might relate data in what used to be disparate stores so that a single request suffices instead of a string of orchestrated calls by a read service. You might need to modify your ETL pipeline to consolidate data (which can be complex and risky) for sharing and passing downstream. And while you migrate, you may want to use a dual write pattern to old and new databases, but it will reduce dependencies and make it easier to triage issues.

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