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Distributed software services to the cloud without breaking a sweat

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José Ferreiro

The document contains the output of multiple "finger" commands run on the user "susan". It shows Susan Potter is logged in from tty1 and has been on since 1997, with no mail and social media accounts listed. The remaining content discusses the scope of a talk, covering approaches, best practices, pitfalls and possibilities, but not specific comparison topics. It also contains sections about cloud computing models, DevOps definitions and principles, deployment pipelines, common bottlenecks, and automation approaches.

Technology
Related topics:
Cloud Computing Insights
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Distributed software services to the cloud without breaking a sweat
Distributed software services to the cloud without breaking a sweat
Distributed software services to the cloud without breaking a sweat
# finger $(whoami) Login: susan Name: Susan Potter Directory: /home/susan Shell: /bin/zsh On since Mon 29 Sep 1997 21:18 (GMT) on tty1 from :0 No mail on me@susanpotter.net Plan: twitter: @SusanPotter github: mbbx6spp
# finger $(whoami) Login: susan Name: Susan Potter Directory: /home/susan Shell: /bin/zsh On since Mon 29 Sep 1997 21:18 (GMT) on tty1 from :0 No mail on me@susanpotter.net Plan: twitter: @SusanPotter github: mbbx6spp
# finger $(whoami) Login: susan Name: Susan Potter Directory: /home/susan Shell: /bin/zsh On since Mon 29 Sep 1997 21:18 (GMT) on tty1 from :0 No mail on me@susanpotter.net Plan: twitter: @SusanPotter github: mbbx6spp
# finger $(whoami) Login: susan Name: Susan Potter Directory: /home/susan Shell: /bin/zsh On since Mon 29 Sep 1997 21:18 (GMT) on tty1 from :0 No mail on me@susanpotter.net Plan: twitter: @SusanPotter github: mbbx6spp
# finger $(whoami) Login: susan Name: Susan Potter Directory: /home/susan Shell: /bin/zsh On since Mon 29 Sep 1997 21:18 (GMT) on tty1 from :0 No mail on me@susanpotter.net Plan: twitter: @SusanPotter github: mbbx6spp
Scope of Talk • Approaches
Scope of Talk • Approaches • Best Practices
Scope of Talk • Approaches • Best Practices • Pitfalls
Scope of Talk • Approaches • Best Practices • Pitfalls • Possibilities
Scope of Talk • Approaches • (not) Chef vs Puppet • Best Practices • Pitfalls • Possibilities
Scope of Talk • Approaches • (not) Chef vs Puppet • Best Practices • (not) Why Cloud? • Pitfalls • Possibilities
Scope of Talk • Approaches • (not) Chef vs Puppet • Best Practices • (not) Why Cloud? • Pitfalls • (not) Why DevOps? • Possibilities
Scope of Talk • Approaches • (not) Chef vs Puppet • Best Practices • (not) Why Cloud? • Pitfalls • (not) Why DevOps? • Possibilities • (not) Which Delivery Model?
Scope of Talk • Approaches • (not) Chef vs Puppet • Best Practices • (not) Why Cloud? • Pitfalls • (not) Why DevOps? • Possibilities • (not) Which Delivery Model? • (not) Release Management
Scope of Talk • Approaches • (not) Chef vs Puppet • Best Practices • (not) Why Cloud? • Pitfalls • (not) Why DevOps? • Possibilities • (not) Which Delivery Model? • (not) Release Management • (not) Monitoring
Cloud buzzzzz
Cloud: Delivery Models [1/2] Software (as a Service) Platform (as a Service) Infrastructure (as a Service)
Cloud: Delivery Models [1/2] Software (as a Service) Platform (as a Service) Infrastructure (as a Service)
Cloud: Delivery Models [1/2] Software (as a Service) Platform (as a Service) Infrastructure (as a Service)
Cloud: Delivery Models [1/2] Software (as a Service) Platform (as a Service) Infrastructure (as a Service)
Cloud: Delivery Models [2/2]
Cloud: Characteristics • Instant on-demand
Cloud: Characteristics • Instant • Virtualized on-demand performance, reliability
Cloud: Characteristics • Instant • Virtualized on-demand performance, reliability • Managed by others
Cloud: Characteristics • Instant • Virtualized on-demand performance, reliability • Managed • Lack control by others predictability, reliability, quality
Cloud: Characteristics • Instant • Virtualized on-demand performance, reliability • Managed • Lack control by others predictability, reliability, quality • Pay as you go
Cloud: Characteristics • Instant • Virtualized on-demand performance, reliability • Managed • Lack control by others predictability, reliability, quality • Pay • Pay as you go as you go!
DevOps Is it a command?
DevOps: Definition [1/2] • Share responsibility across organizational boundaries
DevOps: Definition [1/2] • Share responsibility across organizational boundaries • Invest in people by reducing finger pointing [togetherness] and human error [automation]
DevOps: Definition [1/2] • Share responsibility across organizational boundaries • Invest in people by reducing finger pointing [togetherness] and human error [automation] • Manage infrastructure not priority queues of production issues
DevOps: Definition [1/2] • Share responsibility across organizational boundaries • Invest in people by reducing finger pointing [togetherness] and human error [automation] • Manage infrastructure not priority queues of production issues • Make infrastructure predictable repeatable, testable, deterministic
DevOps: Definition [2/2]
Deployment Pipeline commit -> production
Deployment Pipeline: Prerequisites • Design for cloud e.g. decentralized, layered, parallelized, collaborating single purpose services, async I/O
Deployment Pipeline: Prerequisites • Design for cloud e.g. decentralized, layered, parallelized, collaborating single purpose services, async I/O • Always-ready codebase buildable, testable, deployable
Deployment Pipeline: Prerequisites • Design for cloud e.g. decentralized, layered, parallelized, collaborating single purpose services, async I/O • Always-ready codebase buildable, testable, deployable • Managed infrastructure read: SCM and consistent distribution to target nodes
Deployment Pipeline: Prerequisites • Design for cloud e.g. decentralized, layered, parallelized, collaborating single purpose services, async I/O • Always-ready codebase buildable, testable, deployable • Managed infrastructure read: SCM and consistent distribution to target nodes • Expect [system] failure handle failures sensibly, policies for timeouts, etc
Deployment Pipeline: Prerequisites • Design for cloud e.g. decentralized, layered, parallelized, collaborating single purpose services, async I/O • Always-ready codebase buildable, testable, deployable • Managed infrastructure read: SCM and consistent distribution to target nodes • Expect [system] failure handle failures sensibly, policies for timeouts, etc • Test early and often! outside-in development helps
Deployment Pipeline: Prerequisites • Design for cloud e.g. decentralized, layered, parallelized, collaborating single purpose services, async I/O • Always-ready codebase buildable, testable, deployable • Managed infrastructure read: SCM and consistent distribution to target nodes • Expect [system] failure handle failures sensibly, policies for timeouts, etc • Test early and often! outside-in development helps • Build from the ground up layer infrastructure, inject configuration at boot/load time
Deployment: Common Bottlenecks • Automation build, provision, configure, integrate Figure: http://www.flickr.com/people/laenulfean/
Deployment: Common Bottlenecks • Automation build, provision, configure, integrate • Distribution binaries, assets, configuration Figure: http://www.flickr.com/people/laenulfean/
Deployment: Common Bottlenecks • Automation build, provision, configure, integrate • Distribution binaries, assets, configuration • Timeframe restricted window of time Figure: http://www.flickr.com/people/laenulfean/
Deployment: Common Bottlenecks • Automation build, provision, configure, integrate • Distribution binaries, assets, configuration • Timeframe restricted window of time • Data schema updates, data migrations Figure: http://www.flickr.com/people/laenulfean/
Solution Approaches Solve problems, don’t use tools!
Automation Approaches • Full stack server-driven e.g. Chef/Knife, Puppet Master Figure: http://www.flickr.com/people/krazydad/
Automation Approaches • Full stack server-driven e.g. Chef/Knife, Puppet Master • Full stack client e.g. Chef Solo Figure: http://www.flickr.com/people/krazydad/
Automation Approaches • Full stack server-driven e.g. Chef/Knife, Puppet Master • Full stack client e.g. Chef Solo • Application-tier client e.g. Capistrano, Vlad the Deployer Figure: http://www.flickr.com/people/krazydad/
Automation Approaches • Full stack server-driven e.g. Chef/Knife, Puppet Master • Full stack client e.g. Chef Solo • Application-tier client e.g. Capistrano, Vlad the Deployer • Command & control e.g. Vertibrae (inactive), Nanite Figure: http://www.flickr.com/people/krazydad/
Distribution Approaches • Shared filesystem less security and reliability in community/public or across zones/regions Figure: http://www.flickr.com/people/nsalt
Distribution Approaches • Shared filesystem less security and reliability in community/public or across zones/regions • Pull from source control higher time variance as target nodes increase Figure: http://www.flickr.com/people/nsalt
Distribution Approaches • Shared filesystem less security and reliability in community/public or across zones/regions • Pull from source control higher time variance as target nodes increase • Bittorrent or similar e.g. Twitter’s Murder Figure: http://www.flickr.com/people/nsalt
Timeframe Approaches • Hot upgrades e.g. Erlang/OTP appup/code_change/3 Figure: http://www.flickr.com/people/athenicsword
Timeframe Approaches • Hot upgrades e.g. Erlang/OTP appup/code_change/3 • Rolling upgrades Software design considerations Figure: http://www.flickr.com/people/athenicsword
Timeframe Approaches • Hot upgrades e.g. Erlang/OTP appup/code_change/3 • Rolling upgrades Software design considerations • Environment replacement Flip a switch, acceptance <-> production Figure: http://www.flickr.com/people/athenicsword
Data Approaches • Scriptable schema Alternative: NoSQL, but. . . Figure: http://www.flickr.com/people/shanghaidaddy
Data Approaches • Scriptable schema Alternative: NoSQL, but. . . • Automated migrations e.g. Rails’ Migrations Figure: http://www.flickr.com/people/shanghaidaddy
Data Approaches • Scriptable schema Alternative: NoSQL, but. . . • Automated migrations e.g. Rails’ Migrations • Sanity checks e.g. cherry picked, consistency checks Figure: http://www.flickr.com/people/shanghaidaddy
Common Pitfalls & Workarounds
Organizational Culture Figure: http://www.flickr.com/people/lucgaloppin/
Organizational Culture [Workaround] Figure: http://www.flickr.com/photos/42682395@N04/
Feature Branching Figure: http://www.flickr.com/photos/33939293@N02/
Feature Branching [Workaround]
Feature Branching [Workaround] DON’T!
Live by the meter. Die by the meter. Figure: WARNING
Live by the meter. Die by the meter. [Workarounds] Figure: http://www.flickr.com/people/dirkjankraan/
Great Expectations Figure: http://www.flickr.com/people/atoxinsocks/
Great Expectations [Workaround] Figure: http://www.flickr.com/people/dirkjankraan/
Note: Design & Idempotency Figure: A Twitter dialog between me and @jlouis666
Possibilities Where.next?
Possibilities
Possibilities • Dynamic resource allocation allocate based on load, time of day, day of week/month
Possibilities • Dynamic resource allocation allocate based on load, time of day, day of week/month • Canary deployments (e.g. A/B testing)
Possibilities • Dynamic resource allocation allocate based on load, time of day, day of week/month • Canary deployments (e.g. A/B testing) • Multi-region or multi-provider relocate based on time of day, failover
Questions? Figure: http://www.flickr.com/photos/42682395@N04/
Questions? Figure: http://www.flickr.com/photos/42682395@N04/ @SusanPotter

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Distributed software services to the cloud without breaking a sweat

  • 4. # finger $(whoami) Login: susan Name: Susan Potter Directory: /home/susan Shell: /bin/zsh On since Mon 29 Sep 1997 21:18 (GMT) on tty1 from :0 No mail on me@susanpotter.net Plan: twitter: @SusanPotter github: mbbx6spp
  • 5. # finger $(whoami) Login: susan Name: Susan Potter Directory: /home/susan Shell: /bin/zsh On since Mon 29 Sep 1997 21:18 (GMT) on tty1 from :0 No mail on me@susanpotter.net Plan: twitter: @SusanPotter github: mbbx6spp
  • 6. # finger $(whoami) Login: susan Name: Susan Potter Directory: /home/susan Shell: /bin/zsh On since Mon 29 Sep 1997 21:18 (GMT) on tty1 from :0 No mail on me@susanpotter.net Plan: twitter: @SusanPotter github: mbbx6spp
  • 7. # finger $(whoami) Login: susan Name: Susan Potter Directory: /home/susan Shell: /bin/zsh On since Mon 29 Sep 1997 21:18 (GMT) on tty1 from :0 No mail on me@susanpotter.net Plan: twitter: @SusanPotter github: mbbx6spp
  • 8. # finger $(whoami) Login: susan Name: Susan Potter Directory: /home/susan Shell: /bin/zsh On since Mon 29 Sep 1997 21:18 (GMT) on tty1 from :0 No mail on me@susanpotter.net Plan: twitter: @SusanPotter github: mbbx6spp
  • 9. Scope of Talk • Approaches
  • 10. Scope of Talk • Approaches • Best Practices
  • 11. Scope of Talk • Approaches • Best Practices • Pitfalls
  • 12. Scope of Talk • Approaches • Best Practices • Pitfalls • Possibilities
  • 13. Scope of Talk • Approaches • (not) Chef vs Puppet • Best Practices • Pitfalls • Possibilities
  • 14. Scope of Talk • Approaches • (not) Chef vs Puppet • Best Practices • (not) Why Cloud? • Pitfalls • Possibilities
  • 15. Scope of Talk • Approaches • (not) Chef vs Puppet • Best Practices • (not) Why Cloud? • Pitfalls • (not) Why DevOps? • Possibilities
  • 16. Scope of Talk • Approaches • (not) Chef vs Puppet • Best Practices • (not) Why Cloud? • Pitfalls • (not) Why DevOps? • Possibilities • (not) Which Delivery Model?
  • 17. Scope of Talk • Approaches • (not) Chef vs Puppet • Best Practices • (not) Why Cloud? • Pitfalls • (not) Why DevOps? • Possibilities • (not) Which Delivery Model? • (not) Release Management
  • 18. Scope of Talk • Approaches • (not) Chef vs Puppet • Best Practices • (not) Why Cloud? • Pitfalls • (not) Why DevOps? • Possibilities • (not) Which Delivery Model? • (not) Release Management • (not) Monitoring
  • 19. Cloud buzzzzz
  • 20. Cloud: Delivery Models [1/2] Software (as a Service) Platform (as a Service) Infrastructure (as a Service)
  • 21. Cloud: Delivery Models [1/2] Software (as a Service) Platform (as a Service) Infrastructure (as a Service)
  • 22. Cloud: Delivery Models [1/2] Software (as a Service) Platform (as a Service) Infrastructure (as a Service)
  • 23. Cloud: Delivery Models [1/2] Software (as a Service) Platform (as a Service) Infrastructure (as a Service)
  • 25. Cloud: Characteristics • Instant on-demand
  • 26. Cloud: Characteristics • Instant • Virtualized on-demand performance, reliability
  • 27. Cloud: Characteristics • Instant • Virtualized on-demand performance, reliability • Managed by others
  • 28. Cloud: Characteristics • Instant • Virtualized on-demand performance, reliability • Managed • Lack control by others predictability, reliability, quality
  • 29. Cloud: Characteristics • Instant • Virtualized on-demand performance, reliability • Managed • Lack control by others predictability, reliability, quality • Pay as you go
  • 30. Cloud: Characteristics • Instant • Virtualized on-demand performance, reliability • Managed • Lack control by others predictability, reliability, quality • Pay • Pay as you go as you go!
  • 31. DevOps Is it a command?
  • 32. DevOps: Definition [1/2] • Share responsibility across organizational boundaries
  • 33. DevOps: Definition [1/2] • Share responsibility across organizational boundaries • Invest in people by reducing finger pointing [togetherness] and human error [automation]
  • 34. DevOps: Definition [1/2] • Share responsibility across organizational boundaries • Invest in people by reducing finger pointing [togetherness] and human error [automation] • Manage infrastructure not priority queues of production issues
  • 35. DevOps: Definition [1/2] • Share responsibility across organizational boundaries • Invest in people by reducing finger pointing [togetherness] and human error [automation] • Manage infrastructure not priority queues of production issues • Make infrastructure predictable repeatable, testable, deterministic
  • 37. Deployment Pipeline commit -> production
  • 38. Deployment Pipeline: Prerequisites • Design for cloud e.g. decentralized, layered, parallelized, collaborating single purpose services, async I/O
  • 39. Deployment Pipeline: Prerequisites • Design for cloud e.g. decentralized, layered, parallelized, collaborating single purpose services, async I/O • Always-ready codebase buildable, testable, deployable
  • 40. Deployment Pipeline: Prerequisites • Design for cloud e.g. decentralized, layered, parallelized, collaborating single purpose services, async I/O • Always-ready codebase buildable, testable, deployable • Managed infrastructure read: SCM and consistent distribution to target nodes
  • 41. Deployment Pipeline: Prerequisites • Design for cloud e.g. decentralized, layered, parallelized, collaborating single purpose services, async I/O • Always-ready codebase buildable, testable, deployable • Managed infrastructure read: SCM and consistent distribution to target nodes • Expect [system] failure handle failures sensibly, policies for timeouts, etc
  • 42. Deployment Pipeline: Prerequisites • Design for cloud e.g. decentralized, layered, parallelized, collaborating single purpose services, async I/O • Always-ready codebase buildable, testable, deployable • Managed infrastructure read: SCM and consistent distribution to target nodes • Expect [system] failure handle failures sensibly, policies for timeouts, etc • Test early and often! outside-in development helps
  • 43. Deployment Pipeline: Prerequisites • Design for cloud e.g. decentralized, layered, parallelized, collaborating single purpose services, async I/O • Always-ready codebase buildable, testable, deployable • Managed infrastructure read: SCM and consistent distribution to target nodes • Expect [system] failure handle failures sensibly, policies for timeouts, etc • Test early and often! outside-in development helps • Build from the ground up layer infrastructure, inject configuration at boot/load time
  • 44. Deployment: Common Bottlenecks • Automation build, provision, configure, integrate Figure: http://www.flickr.com/people/laenulfean/
  • 45. Deployment: Common Bottlenecks • Automation build, provision, configure, integrate • Distribution binaries, assets, configuration Figure: http://www.flickr.com/people/laenulfean/
  • 46. Deployment: Common Bottlenecks • Automation build, provision, configure, integrate • Distribution binaries, assets, configuration • Timeframe restricted window of time Figure: http://www.flickr.com/people/laenulfean/
  • 47. Deployment: Common Bottlenecks • Automation build, provision, configure, integrate • Distribution binaries, assets, configuration • Timeframe restricted window of time • Data schema updates, data migrations Figure: http://www.flickr.com/people/laenulfean/
  • 48. Solution Approaches Solve problems, don’t use tools!
  • 49. Automation Approaches • Full stack server-driven e.g. Chef/Knife, Puppet Master Figure: http://www.flickr.com/people/krazydad/
  • 50. Automation Approaches • Full stack server-driven e.g. Chef/Knife, Puppet Master • Full stack client e.g. Chef Solo Figure: http://www.flickr.com/people/krazydad/
  • 51. Automation Approaches • Full stack server-driven e.g. Chef/Knife, Puppet Master • Full stack client e.g. Chef Solo • Application-tier client e.g. Capistrano, Vlad the Deployer Figure: http://www.flickr.com/people/krazydad/
  • 52. Automation Approaches • Full stack server-driven e.g. Chef/Knife, Puppet Master • Full stack client e.g. Chef Solo • Application-tier client e.g. Capistrano, Vlad the Deployer • Command & control e.g. Vertibrae (inactive), Nanite Figure: http://www.flickr.com/people/krazydad/
  • 53. Distribution Approaches • Shared filesystem less security and reliability in community/public or across zones/regions Figure: http://www.flickr.com/people/nsalt
  • 54. Distribution Approaches • Shared filesystem less security and reliability in community/public or across zones/regions • Pull from source control higher time variance as target nodes increase Figure: http://www.flickr.com/people/nsalt
  • 55. Distribution Approaches • Shared filesystem less security and reliability in community/public or across zones/regions • Pull from source control higher time variance as target nodes increase • Bittorrent or similar e.g. Twitter’s Murder Figure: http://www.flickr.com/people/nsalt
  • 56. Timeframe Approaches • Hot upgrades e.g. Erlang/OTP appup/code_change/3 Figure: http://www.flickr.com/people/athenicsword
  • 57. Timeframe Approaches • Hot upgrades e.g. Erlang/OTP appup/code_change/3 • Rolling upgrades Software design considerations Figure: http://www.flickr.com/people/athenicsword
  • 58. Timeframe Approaches • Hot upgrades e.g. Erlang/OTP appup/code_change/3 • Rolling upgrades Software design considerations • Environment replacement Flip a switch, acceptance <-> production Figure: http://www.flickr.com/people/athenicsword
  • 59. Data Approaches • Scriptable schema Alternative: NoSQL, but. . . Figure: http://www.flickr.com/people/shanghaidaddy
  • 60. Data Approaches • Scriptable schema Alternative: NoSQL, but. . . • Automated migrations e.g. Rails’ Migrations Figure: http://www.flickr.com/people/shanghaidaddy
  • 61. Data Approaches • Scriptable schema Alternative: NoSQL, but. . . • Automated migrations e.g. Rails’ Migrations • Sanity checks e.g. cherry picked, consistency checks Figure: http://www.flickr.com/people/shanghaidaddy
  • 62. Common Pitfalls & Workarounds
  • 63. Organizational Culture Figure: http://www.flickr.com/people/lucgaloppin/
  • 64. Organizational Culture [Workaround] Figure: http://www.flickr.com/photos/42682395@N04/
  • 65. Feature Branching Figure: http://www.flickr.com/photos/33939293@N02/
  • 68. Live by the meter. Die by the meter. Figure: WARNING
  • 69. Live by the meter. Die by the meter. [Workarounds] Figure: http://www.flickr.com/people/dirkjankraan/
  • 70. Great Expectations Figure: http://www.flickr.com/people/atoxinsocks/
  • 71. Great Expectations [Workaround] Figure: http://www.flickr.com/people/dirkjankraan/
  • 72. Note: Design & Idempotency Figure: A Twitter dialog between me and @jlouis666
  • 73. Possibilities Where.next?
  • 75. Possibilities • Dynamic resource allocation allocate based on load, time of day, day of week/month
  • 76. Possibilities • Dynamic resource allocation allocate based on load, time of day, day of week/month • Canary deployments (e.g. A/B testing)
  • 77. Possibilities • Dynamic resource allocation allocate based on load, time of day, day of week/month • Canary deployments (e.g. A/B testing) • Multi-region or multi-provider relocate based on time of day, failover
  • 78. Questions? Figure: http://www.flickr.com/photos/42682395@N04/
  • 79. Questions? Figure: http://www.flickr.com/photos/42682395@N04/ @SusanPotter