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Migrating to Microservices


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Adrian Cockcroft discusses strategies, patterns and pathways to perform a gradual migration from monolithic applications towards cloud-based REST microservices. Filmed at

Adrian Cockcroft has had a long career working at the leading edge of technology. At Battery, he advises the firm and its portfolio companies about technology issues and also assists with deal sourcing and due diligence. Before Battery, Adrian helped lead Netflix's migration to a large scale, highly available public-cloud architecture and the open sourcing of the cloud-native NetflixOSS platform.

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Migrating to Microservices

  1. 1. Migrating to Microservices Adrian Cockcroft @adrianco QCon London – 6th March 2014
  2. 2. News & Community Site • 750,000 unique visitors/month • Published in 4 languages (English, Chinese, Japanese and Brazilian Portuguese) • Post content from our QCon conferences • News 15-20 / week • Articles 3-4 / week • Presentations (videos) 12-15 / week • Interviews 2-3 / week • Books 1 / month Watch the video with slide synchronization on! /migration-cloud-native
  3. 3. Presented at QCon London Purpose of QCon - to empower software development by facilitating the spread of knowledge and innovation Strategy - practitioner-driven conference designed for YOU: influencers of change and innovation in your teams - speakers and topics driving the evolution and innovation - connecting and catalyzing the influencers and innovators Highlights - attended by more than 12,000 delegates since 2007 - held in 9 cities worldwide
  4. 4. 3 | Battery Ventures What I learned from my time at Netflix ●  Speed wins in the marketplace ●  Remove friction from product development ●  High trust, low process ●  Freedom and responsibility culture ●  Don’t do your own undifferentiated heavy lifting ●  Simple patterns automated by tooling ● Microservices for speed and availability
  5. 5. 4 | Battery Ventures
  6. 6. 5 | Battery Ventures Typical reactions to my Netflix talks… “You guys are crazy! Can’t believe it” – 2009 “What Netflix is doing won’t work” – 2010 It only works for ‘Unicorns’ like Netflix” – 2011 “We’d like to do that but can’t” – 2012 “We’re on our way using Netflix OSS code” – 2013
  7. 7. 7 | Battery Ventures Demands on IT Increased 1000x Compete or lose in the market!
  8. 8. 8 | Battery Ventures Colonel Boyd USAF, on Combat “Get inside your adversaries' OODA loop to disorient them” Observe Orient Decide Act
  9. 9. 10 | Battery Ventures How fast can you act?
  10. 10. 15 | Battery Ventures Process Hand-Off Steps for Product Development on IaaS Product Manager Development Team QA Integration Team Operations Deploy Team BI Analytics Team
  11. 11. 16 | Battery Ventures Process Hand-Off Steps for Feature Development on PaaS Product Manager Developer BI Analytics Team
  12. 12. 17 | Battery Ventures What Happened? Rate of change increased Cost and size and risk of change reduced
  13. 13. 18 | Battery Ventures Observe Orient Decide Act Land grab opportunity Competitive Move Customer Pain Point Analysis JFDI Plan Response Share Plans Incremental Features Automatic Deploy Launch AB Test Model Hypotheses BIG DATA INNOVATION CULTURE CLOUD Measure Customers Continuous Delivery on Cloud
  14. 14. 19 | Battery Ventures OK, how do I get there?
  15. 15. 20 | Battery Ventures "This is the IT swamp draining manual for anyone who is neck deep in alligators.” Adrian Cockcroft, Cloud Architect at Netflix
  16. 16. 22 | Battery Ventures Continuous Deployment for Speed ● There is no time for handoffs between teams ● IT is a cloud API providing DevOps automation ● “Run what you wrote” – root access and Pagerduty ● High trust culture for fast local action ● Freedom and responsibility for developers ● Lean Enterprise – coming May 2014
  17. 17. 23 | Battery Ventures Open Source Ecosystems ● The most advanced, scalable and stable code is OSS ● No procurement cycle, fix and extend it yourself ● Github is your company’s online resume ● Extensible platforms create ecosystems ● Give up control to get ubiquity – Apache license ● Don’t miss Simon Wardley’s Cloud Expo and QCon talks! Innovate, Leverage and Commoditize
  18. 18. 25 | Battery Ventures Cloud Native for High Availability ● Business logic isolation in stateless micro-services ● Immutable code with instant rollback ● Auto-scaled capacity and deployment updates ● Distributed across availability zones and regions ● De-normalized single function NoSQL data stores ● NetflixOSS at and ● Details from Netflix team at Qcon London March 4-8 2014
  19. 19. Cloud Native Benchmarking Write intensive test of cross region replication capacity 16 x hi1.4xlarge SSD nodes per zone = 96 total 192 TB of SSD in six locations up and running Cassandra in 20 minutes Cassandra Replicas Zone A Cassandra Replicas Zone B Cassandra Replicas Zone C US-West-2 Region - Oregon Cassandra Replicas Zone A Cassandra Replicas Zone B Cassandra Replicas Zone C US-East-1 Region - Virginia Test Load Test Load Validation Load Inter-Zone Traffic 1 Million writes CL.ONE (wait for one replica to ack) 1 Million reads After 500ms CL.ONE with no Data loss Inter-Region Traffic Sustained 9Gbits/s, 83ms 18TB takes about 5hrs 18TB backups from S3
  20. 20. 27 | Battery Ventures Team BTeam A Team C Team D NetflixOSS Style Microservices Deployment API Proxy Zuul Karyon1 Staash1 Cassandra Karyon2 Karyon3 Karyon4 Karyon5 Staash2 MySQL Karyon6 EVcache S3 Eureka Edda Platform Services for service registry and black box recorder External API defined by proxy which routes to various backends
  21. 21. 28 | Battery Ventures Separate Concerns Using Micro-services ● Inverse Conway’s Law – teams own service groups ● One “verb” per single function micro-service ● Size doesn’t matter ● One developer independently produces a micro-service ● Each micro-service is it’s own build, avoids trunk conflicts ● Stateless business logic ● Stateful cached data access layer
  22. 22. 29 | Battery Ventures Micro-service Interaction Swimlane Diagram Two Karyon based services keeping state in an EVcache
  23. 23. 31 | Battery Ventures Microservices Development Architecture ●  Versioning Leave multiple old microservice versions running Fast introduction vs. slow retirement asymmetry ●  Client libraries Even if you start with a protocol, a client side driver is the end-state Best strategy is to own your own client libraries from the start ●  Multithreading and Non-blocking Calls Reactive model RxJava using Observable to hide threading Try migration from Tomcat to Netty to get non-blocking I/O speedup ●  Enterprise Service Bus / Messaging Message buses are CP with big problems getting to AP Use for send and forget over high latency links
  24. 24. 32 | Battery Ventures Microservice APIs ●  API Patterns RPC, REST, Self-describing overhead, public vs. in-house XPATH, jsonpath adds some flexibility but not as useful in-house ●  Scripted API Endpoints - Dynamic Client RPC Pattern See Daniel Jacobson’s talks at March 3rd 2014 post by Sangeeta Narayanan ●  Service discovery Build time Ivy, Gradle and Artifactory Run time Zookeeper for CP, Eureka for AP ●  Understanding existing code boundaries Structure 101 – buy a bigger printer and wallpaper a room
  25. 25. 33 | Battery Ventures Microservice Datastores ●  Book: Refactoring Databases SchemaSpy to examine schema structure Denormalization into one datasource per table or materialized view ●  CAP – Consistent or Available when Partitioned Look at Jepsen models for common systems AP as default for distributed system unless downtime is explicitly OK ●  Circuit Breakers – See for code examples NetflixOSS Hystrix, Turbine, Latency Monkey, Ribbon/Karyon Also look at Finagle/Zipkin from Twitter and Metrics, Graphite Speed of development vs. scale driving resilience ●  Microservice lifecycle Mature slow changing, new fast changing Number increase over time, services increase in size then split
  26. 26. 34 | Battery Ventures Micro-services Bring-Up Strategy Simplest and Soonest
  27. 27. 35 | Battery Ventures Strategies for impatient product managers ● Carrot “This new feature you want will be ready faster as a microservice” ● Stick “This new feature you want will only be implemented in the new microservice based system” ● Shiny Object “Why don’t you concentrate on some other part of the system while we get the transition done?”
  28. 28. 36 | Battery Ventures Shadow Traffic Backend Redirection ● First attempt to send traffic to cloud based microservice Real traffic stream to validate cloud back end Uncovered lots of process and tools issues Uncovered Service latency issues ● Modified Monolithic Datacenter Code Path Returns Genre/movie list for a customer Asynchronously duplicates request to cloud Start with send-and-forget mode, ignore response ● Dynamic Consistent Traffic Percentage If (customerid % 100 < threshold) shadow_call()
  29. 29. 37 | Battery Ventures Shadow Redirect Pattern Cloud Data Source micro-services Shadow Cloud API front end micro- service Modified Monolithic Datacenter Instances Monolith Cloud API micro- service Video list by user Metadata by video One request per visit
  30. 30. 38 | Battery Ventures Metadata Shim Micro-service ●  Metadata server isolates new platform from old codebase Isolate/unblock cloud team from metadata team schedule Monolithic code only supports obsolete movie object ●  VMS subsets the metadata Only load data used by cloud micro-services Fast bulk loads for VMS clients speed startup times ●  VMS pre-processes the metadata Explore next generation metadata cache architecture Distribute metadata to micro-services using S3 or memcached
  31. 31. 39 | Battery Ventures Microservices Deployment ●  Deployment tooling Vagrant for small services on machine testing Cloud based Asgard tag/developer routing Dependencies described with CFengine promises or Puppet Coordinated deployments with Fabric or CloudFormation ●  Production updates and Immutability Monolithic breaks everything at once Microservice add a new microservice, no impact, route test traffic to it Version aware routing, eventual retirement ●  Systems vs. Goals and Learning from Failure Conways law, Speed/Agility, A|B test based improvements Scott Adams “How to fail at almost everything and still win big”
  32. 32. 40 | Battery Ventures Automatic Canary Red/Black Deployment ●  Developer checks in code then get email notifications of progress ●  Jenkins build launches AMI in test account and starts tests ●  If tests pass launch canary signature analysis in production Start one new instance of the old code per zone Start one new instance of the new code per zone Ramp up traffic and analyze metrics on all six ●  If canary signature looks good replace current production Scale canary build up to full capacity Send all the traffic to the new code Wait until after peak traffic time then remove old code instances ●  Security team tools notice the new build via Edda query Automatic penetration test scan In use at Netflix for tens of large fleet microservices in active development
  33. 33. Netflix Bad Canary Signature
  34. 34. Netflix Happy Canary Signature
  35. 35. Netflix Global Deploy-to-Prod Automation Cassandra Replicas Zone A Cassandra Replicas Zone B Cassandra Replicas Zone C West Coast Load Balancers Cassandra Replicas Zone A Cassandra Replicas Zone B Cassandra Replicas Zone C East Coast Load Balancers Cassandra Replicas Zone A Cassandra Replicas Zone B Cassandra Replicas Zone C Europe Load Balancers Afternoon in California Code checked in Night-time in Europe Next day on East CoastAfter peak on West Coast After peak in Europe If passes test suite, canary then deploy Canary then deployCanary then deploy
  36. 36. 44 | Battery Ventures Monitoring Micro-services ●  Appdynamics Instrument the JVM to capture everything including traffic flows Insert tag for every http request with a header annotation guid Visualize the over-all flow or the business transaction flow ● and Lyatiss CloudWeaver Instrument the packet flows across the network Capture the zone and region config from cloud APIs and tags Correlate, aggregate and visualize the traffic flows ●  Instrumented PaaS Communication Mechanisms CloudFoundry and Apcera route all traffic through NATS NetflixOSS ribbon client and karyon server http annotation guid Scales beyond capabilities of centralized vendor based tools Visualizing the request flow
  37. 37. 45 | Battery Ventures Scaling Continuous Delivery Models ●  Etsy – 8 devs per train ●  Everyone runs the monolith ●  Queue for the next train ●  Coordination chat session ●  Need to learn deploy process ●  Copy code to existing servers ●  Few concurrent versions ●  50 monolithic updates/day ●  Roll-forward only ●  “Done” is released to prod ●  Everyone has their own build ●  Dev runs their own microservice ●  No waiting, no meetings ●  API call to update prod timeline ●  Automated hands-off deploy ●  Immutable code on new servers ●  Unlimited concurrent versions ●  100s of independent updates ●  Roll-back in seconds ●  “Done” is retired from prod Monolithic – Etsy, Facebook Microservices – Netflix, Gilt
  38. 38. 46 | Battery Ventures Separation of Concerns Bounded Contexts
  39. 39. 47 | Battery Ventures Summary ●  Speed wins in the marketplace ●  Remove friction from product development ●  High trust, low process ●  Freedom and responsibility culture ●  Don’t do your own undifferentiated heavy lifting ●  Simple patterns automated by tooling ●  Microservices for speed and availability
  40. 40. 49 | Battery Ventures Any Questions? Upcoming Presentations by @adrianco ●  Battery Ventures ●  Adrian’s Blog ●  Netflix Tech Blog ●  Netflix Slideshare ●  Migrating to Microservices – Qcon London - March 6th, 2014 ●  Monitorama Keynote Portland OR - May 7th, 2014 ●  GOTO Chicago Opening Keynote May 20th, 2014 ●  DevOps Summit at Cloud Expo New York – June 10th, 2014 ●  GOTO Copenhagen/Aarhus – Denmark – Oct 25th, 2014
  41. 41. Watch the video with slide synchronization on! -cloud-native