When Developers Operate and Operators Develop

1. When developers operate, and operators develop… Adrian Cockcroft @adrianco Technology Fellow - Battery Ventures June 2015

2. “You build it, you run it.” Werner Vogels 2006

3. Key Goals of the CIO? Align IT with the business Develop products faster Try not to get breached

4. Security Blanket Failure Insecure applications hidden behind firewalls make you feel safe until the breach happens… http://peanuts.wikia.com/wiki/Linus'_security_blanket

5. What needs to change?

6. Developer responsibilities: Faster, cheaper, safer

7. Operator responsibilities: API driven platform automation

8. Product Development Processes

9. Assumption: Process prevents problems

10. Organizations build up slow complex “Scar tissue” processes

11. Observe Orient Decide Act Continuous Delivery

12. Observe Orient Decide Act Land grab opportunity Competitive Move Customer Pain Point Measure Customers Continuous Delivery

13. Observe Orient Decide Act Land grab opportunity Competitive Move Customer Pain Point INNOVATION Measure Customers Continuous Delivery

14. Observe Orient Decide Act Land grab opportunity Competitive Move Customer Pain Point Analysis Model Hypotheses INNOVATION Measure Customers Continuous Delivery

15. Observe Orient Decide Act Land grab opportunity Competitive Move Customer Pain Point Analysis Model Hypotheses BIG DATA INNOVATION Measure Customers Continuous Delivery

16. Observe Orient Decide Act Land grab opportunity Competitive Move Customer Pain Point Analysis JFDI Plan Response Share Plans Model Hypotheses BIG DATA INNOVATION Measure Customers Continuous Delivery

17. Observe Orient Decide Act Land grab opportunity Competitive Move Customer Pain Point Analysis JFDI Plan Response Share Plans Model Hypotheses BIG DATA INNOVATION CULTURE Measure Customers Continuous Delivery

18. 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 Measure Customers Continuous Delivery

19. 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

22. Breaking Down the SILOs

23. Breaking Down the SILOs QA DBA Sys Adm Net Adm SAN Adm DevUX Prod Mgr

24. Breaking Down the SILOs QA DBA Sys Adm Net Adm SAN Adm DevUX Prod Mgr Product Team Using Monolithic Delivery Product Team Using Monolithic Delivery

25. Breaking Down the SILOs QA DBA Sys Adm Net Adm SAN Adm DevUX Prod Mgr Product Team Using Microservices Product Team Using Monolithic Delivery Product Team Using Microservices Product Team Using Microservices Product Team Using Monolithic Delivery

26. Breaking Down the SILOs QA DBA Sys Adm Net Adm SAN Adm DevUX Prod Mgr Product Team Using Microservices Product Team Using Monolithic Delivery Platform TeamProduct Team Using Microservices Product Team Using Microservices Product Team Using Monolithic Delivery

27. Breaking Down the SILOs QA DBA Sys Adm Net Adm SAN Adm DevUX Prod Mgr Product Team Using Microservices Product Team Using Monolithic Delivery Platform Team A P I Product Team Using Microservices Product Team Using Microservices Product Team Using Monolithic Delivery

28. Breaking Down the SILOs QA DBA Sys Adm Net Adm SAN Adm DevUX Prod Mgr Product Team Using Microservices Product Team Using Monolithic Delivery Platform Team DevOps is a Re-Org! A P I Product Team Using Microservices Product Team Using Microservices Product Team Using Monolithic Delivery

29. Release Plan Developer Developer Developer Developer Developer QA Release Integration Ops Replace Old With New Release Monolithic service updates Works well with a small number of developers and a single language like php, java or ruby

30. Release Plan Developer Developer Developer Developer Developer QA Release Integration Ops Replace Old With New Release Bugs Monolithic service updates Works well with a small number of developers and a single language like php, java or ruby

31. Release Plan Developer Developer Developer Developer Developer QA Release Integration Ops Replace Old With New Release Bugs Bugs Monolithic service updates Works well with a small number of developers and a single language like php, java or ruby

32. Use monolithic apps for small teams, simple systems and when you must, to optimize for efficiency and latency

33. Developer Developer Developer Developer Developer Old Release Still Running Release Plan Release Plan Release Plan Release Plan Immutable microservice deployment scales, is faster with large teams and diverse platform components

34. Developer Developer Developer Developer Developer Old Release Still Running Release Plan Release Plan Release Plan Release Plan Deploy Feature to Production Deploy Feature to Production Deploy Feature to Production Deploy Feature to Production Immutable microservice deployment scales, is faster with large teams and diverse platform components

35. Developer Developer Developer Developer Developer Old Release Still Running Release Plan Release Plan Release Plan Release Plan Deploy Feature to Production Deploy Feature to Production Deploy Feature to Production Deploy Feature to Production Bugs Immutable microservice deployment scales, is faster with large teams and diverse platform components

36. Developer Developer Developer Developer Developer Old Release Still Running Release Plan Release Plan Release Plan Release Plan Deploy Feature to Production Deploy Feature to Production Deploy Feature to Production Deploy Feature to Production Bugs Deploy Feature to Production Immutable microservice deployment scales, is faster with large teams and diverse platform components

37. Developer Developer Run What You Wrote Developer Developer

38. Developer Developer Run What You Wrote Micro service Micro service Micro service Micro service Micro service Micro service Micro service Developer Developer

39. Developer Developer Run What You Wrote Micro service Micro service Micro service Micro service Micro service Micro service Micro service Developer Developer Monitoring Tools

40. DeveloperDeveloper Developer Run What You Wrote Micro service Micro service Micro service Micro service Micro service Micro service Micro service Developer Developer Monitoring Tools

41. DeveloperDeveloper Developer Run What You Wrote Micro service Micro service Micro service Micro service Micro service Micro service Micro service Developer Developer Site Reliability Monitoring Tools Availability Metrics 99.95% customer success rate

42. DeveloperDeveloper Developer Run What You Wrote Micro service Micro service Micro service Micro service Micro service Micro service Micro service Developer Developer Manager Manager Site Reliability Monitoring Tools Availability Metrics 99.95% customer success rate

43. DeveloperDeveloper Developer Run What You Wrote Micro service Micro service Micro service Micro service Micro service Micro service Micro service Developer Developer Manager Manager VP Engineering Site Reliability Monitoring Tools Availability Metrics 99.95% customer success rate

44. Change One Thing at a Time!

45. What Happened? Rate of change increased Cost and size and risk of change reduced

46. Low Cost of Change Using Docker Developers • Compile/Build • Seconds Extend container • Package dependencies • Seconds PaaS deploy Container • Docker startup • Seconds

47. Low Cost of Change Using Docker Fast tooling supports continuous delivery of many tiny changes Developers • Compile/Build • Seconds Extend container • Package dependencies • Seconds PaaS deploy Container • Docker startup • Seconds

48. Disruptor: Continuous Delivery with Containerized Microservices

49. Microservices

50. A Microservice Definition Loosely coupled service oriented architecture with bounded contexts

51. A Microservice Definition Loosely coupled service oriented architecture with bounded contexts If every service has to be updated at the same time it’s not loosely coupled

52. A Microservice Definition Loosely coupled service oriented architecture with bounded contexts If every service has to be updated at the same time it’s not loosely coupled If you have to know too much about surrounding services you don’t have a bounded context. See the Domain Driven Design book by Eric Evans.

53. Coupling Concerns http://en.wikipedia.org/wiki/Conway's_law ●Conway’s Law - organizational coupling ●Centralized Database Schemas ●Enterprise Service Bus - centralized message queues ●Inflexible Protocol Versioning

54. Speeding Up Deployments Datacenter Snowflakes • Deploy in months • Live for years

55. Speeding Up Deployments Datacenter Snowflakes • Deploy in months • Live for years Virtualized and Cloud • Deploy in minutes • Live for weeks

56. Speeding Up Deployments Datacenter Snowflakes • Deploy in months • Live for years Virtualized and Cloud • Deploy in minutes • Live for weeks Container Deployments • Deploy in seconds • Live for minutes/hours

57. Speeding Up Deployments Datacenter Snowflakes • Deploy in months • Live for years Virtualized and Cloud • Deploy in minutes • Live for weeks Container Deployments • Deploy in seconds • Live for minutes/hours AWS Lambda Events • Respond in milliseconds • Live for seconds

58. Speeding Up Deployments Measuring CPU usage once a minute makes no sense for containers… Coping with rate of change is the first challenge for monitoring tools. Datacenter Snowflakes • Deploy in months • Live for years Virtualized and Cloud • Deploy in minutes • Live for weeks Container Deployments • Deploy in seconds • Live for minutes/hours AWS Lambda Events • Respond in milliseconds • Live for seconds

59. Inspiration

60. Challenges for Microservice Platforms

61. Managing Scale

62. A Possible Hierarchy Continents Regions Zones Services Versions Containers Instances How Many? 3 to 5 2-4 per Continent 1-5 per Region 100’s per Zone Many per Service 1000’s per Version 10,000’s It’s much more challenging than just a large number of machines

63. Flow

64. Some tools can show the request flow across a few services

65. But interesting architectures have a lot of microservices! Flow visualization is a big challenge. See http://www.slideshare.net/LappleApple/gilt-from-monolith-ruby-app-to-micro-service-scala-service-architecture

66. Failures

67. ELB Load Balancer Zuul API Proxy Karyon Business Logic Staash Data Access Layer Priam Cassandra Datastore Simple NetflixOSS style microservices architecture on three AWS Availability Zones

68. ELB Load Balancer Zuul API Proxy Karyon Business Logic Staash Data Access Layer Priam Cassandra Datastore Simple NetflixOSS style microservices architecture on three AWS Availability Zones

69. ELB Load Balancer Zuul API Proxy Karyon Business Logic Staash Data Access Layer Priam Cassandra Datastore Simple NetflixOSS style microservices architecture on three AWS Availability Zones Zone partition/failure What should you do? What should monitors show?

70. ELB Load Balancer Zuul API Proxy Karyon Business Logic Staash Data Access Layer Priam Cassandra Datastore Simple NetflixOSS style microservices architecture on three AWS Availability Zones Zone partition/failure What should you do? What should monitors show? By design, everything works with 2 of 3 zones running. This is not an outage, inform but don’t touch anything! Halt deployments perhaps?

71. ELB Load Balancer Zuul API Proxy Karyon Business Logic Staash Data Access Layer Priam Cassandra Datastore Simple NetflixOSS style microservices architecture on three AWS Availability Zones Zone partition/failure What should you do? What should monitors show? By design, everything works with 2 of 3 zones running. This is not an outage, inform but don’t touch anything! Halt deployments perhaps? Challenge: understand and communicate common microservice failure patterns.

72. Testing

73. Testing monitoring tools at scale gets expensive quickly…

74. Simulation

75. Simulated Microservices Model and visualize microservices Simulate interesting architectures Generate large scale configurations Eventually stress test real tools See github.com/adrianco/spigo Simulate Protocol Interactions in Go Visualize with D3 ELB Load Balancer Zuul API Proxy Karyon Business Logic Staash Data Access Layer Priam Cassandra Datastore Three Availability Zones

76. Definition of an architecture { "arch": "netflixoss", "description":"A very simple Netflix service. See http://netflix.github.io/ to decode the package names", "version": "arch-0.0", "victim": "homepage", "services": [ { "name": "cassSubscriber", "package": "priamCassandra", "count": 6, "regions": 1, "dependencies": ["cassSubscriber", "eureka"]}, { "name": "evcacheSubscriber","package": "store", "count": 3, "regions": 1, "dependencies": []}, { "name": "subscriber", "package": "staash", "count": 6, "regions": 1, "dependencies": ["cassSubscriber", "evcacheSubscriber"]} { "name": "login", "package": "karyon", "count": 18, "regions": 1, "dependencies": ["subscriber"]}, { "name": "homepage", "package": "karyon", "count": 24, "regions": 1, "dependencies": ["subscriber"]}, { "name": "wwwproxy", "package": "zuul", "count": 6, "regions": 1, "dependencies": ["login", "homepage"]}, { "name": "www-elb", "package": "elb", "count": 0, "regions": 1, "dependencies": ["wwwproxy"]}, { "name": "www", "package": "denominator", "count": 0, "regions": 0, "dependencies": ["www-elb"]} ] } Header includes chaos monkey victim New tier name Tier package Region count: 1 Node count List of tier dependencies

77. Why Build Spigo/Simianviz? Generate test microservice configurations at scale Stress monitoring tools display capabilities Eventually (i.e. not implemented yet) Dynamically vary configuration: autoscale, code push Chaos monkey for microservice, zone, region failures D3 websocket dynamic browser interface

78. Simulated Game Day Testing and Training…

79. Conference Driven Development… OSCON Microservices Workshop

80. What’s Next?

81. Developer Concerns Agile, Lean & Rugged (Faster, Cheaper and Safer) See GOTO London Sept 2015

82. Forward Thinking

83. Forward Thinking

84. Any Questions? Disclosure: some of the companies mentioned may be Battery Ventures Portfolio Companies See www.battery.com for a list of portfolio investments ● Battery Ventures http://www.battery.com ● Adrian’s Tweets @adrianco and Blog http://perfcap.blogspot.com ● Slideshare http://slideshare.com/adriancockcroft ● Monitorama Opening Keynote Portland OR - May 7 th , 2014 ● GOTO Chicago Opening Keynote May 20 th , 2014 ● Qcon New York – Speed and Scale - June 11 th , 2014 ● Structure - Cloud Trends - San Francisco - June 19th, 2014 ● GOTO Copenhagen/Aarhus – Fast Delivery - Denmark – Sept 25 th , 2014 ● DevOps Enterprise Summit - San Francisco - Oct 21-23rd, 2014 #DOES14 ● GOTO Berlin - Migrating to Microservices - Germany - Nov 6th, 2014 ● AWS Re:Invent - Cloud Native Cost Optimization - Las Vegas - November 14th, 2014 ● O’Reilly Software Architecture Conference - Fast Delivery, Monitoring Challenge - Boston March 16th 2015

85. Security Visit http://www.battery.com/our-companies/ for a full list of all portfolio companies in which all Battery Funds have invested. Palo Alto Networks Enterprise IT Operations & Management Big DataCompute Networking Storage