This document discusses application resiliency and introduces Yet Another Resilience Framework (YARF), which is inspired by Netflix Hystrix. It describes that applications must be resilient to failures in their dependencies. YARF embraces the natural occurrence of failures and manages them using resiliency patterns like bulkheads, timeouts, circuit breakers, retries, and fallbacks. These patterns help applications degrade gracefully under failure and improve the user experience. The document provides an overview of how to get started with YARF and links to a demo video and code on GitHub.

1. Application Resiliency
Yet Another Resilience Framework
Inspired By Netflix Hystrix

2. Resilience:
Systems easily “drift” from a state of resilience
and failure can emerge from component
relationships. Thus, applications (as components
of a complex system) must be resilient to latency
and failure on all of its system relationships and
not rely upon infrastructure alone to implement
this resilience

4. Application Resiliency

5. Philosophy
• Embrace failure as a natural state in the life-
cycle of the application
• Instead of trying to prevent it; manage it
• Let developers responsible for resiliency
• Process supervision
• Supervisor hierarchies

6. Resiliency Patterns
• Bulkheads
– Workload isolation with thread pools
• Dataflow Concurrency (Promises)
• Retry On Failure
• Timeouts
• Circuit Breaker
• Fallback
• Governor
– Overload Protection
– Throttling Concurrency & RateLimit

7. Bulkheads

8. Async task orchestration with Promises

9. Throttling

10. Fallback

11. Fail fast (Timeout)
• Avoid “slow responses”
• Separate:
– SystemError - resources not available
– ApplicationError - bad user input etc
• Verify resource availability before starting
expensive task
• Input validation immediately

12. Circuit Breakers

13. Retry on Failure
N
Improving User Experience and
Application Resiliency by Retrying
Dependency if Error recoverable
Retry Policy per service Call or Global defaults,
Transient errors should be retried
Service
Dependent Service Call
Transient Exception failures
Retry Call
1
2
Exception List:
Error 1
Error 2
Retry = Y
Retry Cnt = 2
Delay = 50ms
Policy: Service 1
Service
Framework
Application Service

14. Based on Netflix Hystrix

15. Our Approach
Fallback
CircuitBreaker
CircuitBreaker
Retry
Retry
Timeout
Timeout
Primary
Service
Alternate
Service
1 3 4 5
Component Order
bulkhead
(Thread Pool)
bulkhead
(Thread Pool)
Governor
Order Service
getBillingInfo()
getOrder()
getShippingInfo()
2 6

16. Future Patterns
• Request Caching
• Request Collapsing
– A mechanism, which combines multiple requests
into a single backend dependency call to reduce
the number of threads and network connections
required
– The primary driver of using request collapsing is to reduce the number of threads and network
connections needed to perform concurrent command executions and do so in an automated manner
without forcing all developers of a codebase to coordinate manually batching of requests.

17. Getting Started
Demo on YouTube
– http://youtu.be/ZyeEdjufSHE
Code on GitHub
– https://github.com/xmlking/Resilience
Follow me on Twitter
– @xmlking