Presentation: Polyglot Persistence Powering Microservices
What You’ll Learn
- How to decide between these [persistence] solutions to work for their microservices?
- How to build expertise in providing polyglot persistence as a service so that developers can focus on building great applications and not worry about tuning, tweaking, and capacity planning of various backends.
- Deeper insights into the key components needed for operating the various persistence stores at scale and challenges involved with it.
- Inside look at Netflix’s common platform which drives operational excellence in managing, maintaining, and scaling persistence infrastructures (including building reliable systems on unreliable infrastructure).
Abstract
Netflix’s architecture involves thousands of microservices built to serve unique business needs. As this architecture grew, it became clear that the data storage and query needs were unique to each area; there is no one silver bullet which fits the data needs for all microservices. Netflix embraced polyglot persistence, which promises to offer ideal matches between problem spaces and persistence solutions.
No longer do developers struggle with mapping graph data into relational tables, adapting document-oriented data into columnar stores, or mashing key-value data into blob stores. Unlocking these benefits comes with costs, from operational complexity to cognitive overload and more. Building on our years of running and scaling thousands of microservices in the cloud at Netflix, we’ll share:
- Specific examples of how we at Netflix solved the unique business use cases and represented the data to adhere to best model for the use case.
- Challenges around offering the database as a service specially in polyglot persistence
- Benefits, pitfalls, and lessons learned from our polyglot persistence architectures to shape the success of various services.
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