Uploaded byTimothy Perrett
Online Experimentation with Immutable Infrastructure
The document discusses the concept of immutable infrastructure and the necessity of experimentation in software deployment processes. It emphasizes the importance of testing in production to manage complexities and emergent behaviors in microservices while demanding agility, observability, and automation from development practices. The conclusions advocate for a codified experimentation infrastructure that enhances flexibility and operational efficiency.
More Related Content
Similar to Online Experimentation with Immutable Infrastructure
Online Experimentation with Immutable Infrastructure
- 1. Experimentation with ImmutableInfrastructure. Timothy Perrett @ Hashiconf 2017
- 2.
- 3. Immutable Infrastructure. thou shallnot change thy deployment!
- 4.
- 5.
- 6.
- 7.
- 8.
- 9. Workloads. • Users demand: •Blazing fast iteration. • High degree of observability. • Seamless traffic migration between application revisions. • Automated application cleanup. • Self-service DevOps experience.
- 10. Workloads. • Users demand: •Blazing fast iteration. • High degree of observability. • Seamless traffic migration between application revisions. • Automated application cleanup. • Self-service DevOps experience. 2017 minimum table stakes!
- 11. Ex·per·i·men·ta·tion Process of performinga scientific procedure to determine something.
- 12. Ex·per·i·men·ta·tion Process of performinga scientific procedure to determine something. Testing in production
- 14. Testing in Production. everyonedoes it. nobody wants to own up to it.
- 15. Emergent Behaviors. observation ofunpredictable, non-deterministic runtime artifacts. Testing in production.
- 16. – Conway’s Law “Anyorganization that designs a system will produce a design whose structure is a copy of the organization's communication structure”
- 17. – Hyrum’s Law “Witha sufficient number of users of an interface, all observable behaviors of your interface will be depended upon by somebody.”
- 18. Microservice Complexity. local containerizedtesting is a fable. Testing in production.
- 19. Inconceivable Scale. black friday.super bowl. popular cat memes. Testing in production.
- 20. Human Error. embrace theinevitable. http://queue.acm.org/detail.cfm?id=2839461 Testing in production.
- 21.
- 22.
- 23.
- 24.
- 25.
- 26.
- 27.
- 28.
- 29.
- 30.
- 31.
- 32.
- 33.
- 34.
- 40. I’m sold! where doI sign?
- 41.
- 42. Data Plane. envoy. linkerd.nginx+.
- 46.
- 48.
- 49. Challenges. • How youcollect results affects how you read them. • Twyman’s Law: “Any piece of data or evidence that looks interesting or unusual is probably wrong!”. • Disparate data collection in many organizations. • Instrument everything with segment identifiers. • Modify all applications to be experiment aware. • Such systems breed organizational change. Embrace it.
- 50. Conclusions. • Experimentation infrastructuremakes your workloads mobile. • Not only does this make experimentation viable and low-impact, but it makes your operation vastly more flexible. • Codify and automate an experimentation process. • You’re already doing it manually. • Tools are already available that form the building blocks.
- 51.
- 52. Links • Nelson: https://verizon.github.io/nelson/ •Istio: https://istio.io/ • Research: • Microsoft (2013): http://dl.acm.org/citation.cfm?id=2488217 • Etsy (2012): https://www.slideshare.net/danmckinley/design-for-continuous- experimentation • Google (2010): https://research.google.com/pubs/pub36500.html • Microsoft (2009): http://dl.acm.org/citation.cfm?id=2339653