The Hardest Part of Microservices: Your Data - Christian Posta, Red Hat
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Christian Posta, principal architect at Red Hat discusses how to manage your data within a microservices architecture at the 2017 Microservices.com Practitioner Summit.
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The Hardest Part of Microservices: Your Data - Christian Posta, Red Hat
- 2. Full slide deck here: h"p://bit.ly/ceposta-hardest-part
- 3. Twitter: @christianposta Blog: http://blog.christianposta.com Email: christian@redhat.com Christian Posta Principal Architect – Red Hat • Author “Microservices for Java Developers” • Committer/contributor Apache Camel, Apache ActiveMQ, Fabric8.io, Apache Kafka, Debezium.io, et. al. • Worked with large Microservices, web-scale, unicorn company • Blogger, speaker about DevOps, integration, and microservices
- 6. “Microservices” is about optimizing … for speed.
- 12. Focus on domain models, not data models • Break things into smaller, understandable models • Surround a model and its “context” with an explicit boundary • Implement the model in code or get a new model • Explicitly map between different contexts • Model transactional boundaries as aggregates
- 17. But ... • Load/size is too great to fit on one box • Modules/use cases have different read/write characterisBcs • Queries/joins are geOng too complex • Security issues • Lots of conflicBng changes to the model/schema • Need denormalized, opBmized indexing engines • We want to explicitly reduce dependencies on data between our services
- 18. From here on out, what we’re saying is “thank you old work-horse database, we’ve got it from here”…
- 27. Consistency models… h"ps://en.wikipedia.org/wiki/Consistency_model • Strict consistency (Linearizability) • Sequential consistency • Causal consistency • Processor consistency • PRAM consistency (FIFO) • Bounded staleness consistency • Monotonic read consistency • Monotonic write consistency • Read your writes consistency • Eventual consistency
- 28. Replicated Data Consistency Explained through Baseball (Doug Terry) h"ps://www.microsoa.com/en-us/research/publicaBon/ replicated-data-consistency-explained-through-baseball/ • What consistency model do you need, depending on what role you’re playing? • What consistency model are you willing to pay for? • Official score keeper? (Linearizability or RMW) • Umpire? (Linearizability) • Sports writer? (Bounded staleness, Eventual consistency) • Radio updates? (Monotonic read, Bounded staleness) • Statistician (Bounded staleness) • Friends in the pub (Eventual consistency)
- 32. And this is what the internet companies did also. (some even opensource!!) • Yelp – MySQL Streamer https://github.com/Yelp/mysql_streamer • LinkedIn – Databus https://github.com/linkedin/databus • Zendesk – Maxwell https://github.com/zendesk/maxwell
- 33. Meet debezium.io
- 35. Meet debezium.io
- 37. Twitter: @christianposta Blog: http://blog.christianposta.com Email: christian@redhat.com Thanks for listening! Time for demo? Full slide deck here: h"p://bit.ly/ceposta-hardest-part