Resiliency and Availability Design Patterns for the Cloud

We have traditionally built robust software systems by trying to avoid mistakes and by dodging failures when they occur in production or by testing parts of the system in isolation from one another. Modern methods and techniques take a very different approach based on resiliency, which promotes embracing failure instead of trying to avoid it. Resilient architectures enhance observability, leverage well-known patterns such as graceful degradation, timeouts and circuit breakers but also new patterns like cell-based architecture and shuffle sharding. In this session, will review the most useful patterns for building resilient software systems and especially show the audience how they can benefit from the patterns.

Transcript

1. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Resiliency and Availability Design Patterns for the Cloud Sébastien Stormacq Senior Technical Evangelist Amazon Web Services @sebsto
2. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Can you guess what will happen?
3. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Distributed Systems are hard
4. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Failures are a given and everything will eventually fail over time. Werner Vogels CTO – Amazon.com “ “
5. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Resiliency: Ability for a system to handle and eventually recover from unexpected conditions
6. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Partial failure mode
7. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. People Application Network & Data Infrastructure
8. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Let’s talk about Geo Availability
9. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
10. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. AWS Region and availability zones Region Availability zone a Availability zone b Availability zone c data center data center data center 1 or more data centers per AZ 2 or more AZs per region (new regions min 3) data center data center data center data center data center data center
11. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Availability in parallel Component Availability Downtime X 99% (2-nines) 3 days 15 hours Two X in parallel 99.99% (4-nines) 52 minutes Three X in parallel 99.9999% (6-nines) 31 seconds
12. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Multi-AZ architecture Region Availability zone a Availability zone b Availability zone c Instances Instances Instances DB Instance DB instance standby Elastic Load Balancing (ELB)
13. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Multi-AZ architecture X Region Availability zone a Availability zone b Availability zone c Instances Instances Instances DB Instance DB instance standby Elastic Load Balancing (ELB)
14. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Multi-AZ architecture Region Availability zone a Availability zone b Availability zone c Instances Instances Instances DB Instance DB instance standby Elastic Load Balancing (ELB) X
15. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Multi-AZ architecture Region Availability zone a Availability zone b Availability zone c Instances Instances Instances DB Instance DB instance new master Elastic Load Balancing (ELB) X
16. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Multi-AZ architecture • Enables fault-tolerant applications • AWS regional services designed to withstand AZ failures • Leveraged by AWS regional services such as Amazon S3, Amazon DynamoDB, Amazon Aurora, Amazon ELBs, etc. Region Availability zone a Availability zone b Availability zone c Instances Instances Instances DB Instance DB instance standby Elastic Load Balancing (ELB)
17. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Let’s talk about auto scaling
18. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Auto-Scaling Fixed Variable
19. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Availability zone 1 Auto Scaling group AWS Region Availability zone 2 Auto-scaling for self-healing Elastic Load Balancing (ELB) X
20. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Let’s talk about decoupling and async
21. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Process A Process B Process A Process B Synchronous Asynchronous Waiting Working Continues get or fetch result Get result Decoupling with async pattern
22. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. API: {DO foo} PUT JOB: {JobID: 0001, Task: DO foo} API: {JobID: 0001} GET JOB: {JobID: 0001, Task: DO foo} {JobID: 0001, Result: bar} Cache node Worker Instance Worker Instance Queue/Streaming API Instance API Instance API Instance
23. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Push Notification User Worker Instance Worker Instance API Instance API Instance Cache node Fetch results API Instance Queue/Streaming
24. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Degrade & prioritize traffic with queues Worker Instance Worker Instance API Instance API Instance API Instance High Priority Queue Low Priority Queue
25. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Let’s talk about timeouts, backoff & retries!
26. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Users App DB Conn Pool INSERT INSERT INSERT INSERT What happens if the DB “slows down”? Timeout client side Timeout backend side ? ?
27. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. User 1 App DB Conn Pool INSERT Timeout client side = 10s Timeout backend side = default = Infinite Retry INSERT Retry INSERT ERROR: Failed to get connection from pool Retry
28. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. https://docs.microsoft.com/en-us/dotnet/api/system.net.httpwebrequest.timeout
29. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
30. https://dev.mysql.com/doc/connector-j/5.1/en/connector-j-reference-configuration-properties.html
31. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. @timeout_decorator.timeout(5, timeout_exception=StopIteration) def timed_get(url): return requests.get(url) https://pypi.org/project/timeout-decorator/
32. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Set the timeouts!
33. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. How else could we have prevented the error? User 1 DB Conn Pool INSERT Retry INSERT Retry INSERT Retry ERROR: Failed to get connection from pool
34. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. User 1 DB Conn Pool INSERT Timeout client side = 10s Timeout backend side = 10s Wait 2s before Retry INSERT INSERT Wait 4s before Retry Wait 8s before Retry Wait 16s before Retry Backing off between retries Releasing connections Backoff
35. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. No jitter With jitter https://aws.amazon.com/blogs/architecture/exponential-backoff-and-jitter/ Simple Exponential Backoff is not enough: Add Jitter
36. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Example: add jitter 0-1000ms MAX_TRIES = 12 def get_item(self, url, n=1): try: res = requests.get(url) except: if n > MAX_TRIES: return None n += 1 time.sleep((2 ** n) + (random.randint(0, 1000) / 1000.0)) return self.get_item(url, n) else: return res
37. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
38. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Idempotent operation No additional effect if it is called more than once with the same input parameters.
39. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Circuit Breaker • Wrap a protected function call in a circuit breaker object, which monitors for failures. • If failures reach a certain threshold, the circuit breaker trips. Producer Circuit Breaker Consumer Connection Monitoring Timeouts Breaking Circuit
40. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. https://github.com/Netflix/Hystrix
41. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. https://spring.io/guides/gs/circuit-breaker/
42. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Let’s talk about health checking!
43. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Auto Scaling group Service A Availability zone 1 Auto Scaling group AWS Region Service A Availability zone 2 Service B Service B database Email Probing for health Cluster
44. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Shallow health check Instance Cache node Email database Cluster Are you healthy? yes
45. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Shallow health check Instance Cache node Email database Cluster Are you healthy? yes
46. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Deep health check Instance Cache node Email database Cluster Are you healthy? yes Are you healthy? yes yes yes yes
47. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Deep health check Instance Cache node Email database Cluster Are you healthy? no Are you healthy? no yes yes yes
48. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Prioritize shallow health checks during hard times. Cache and be careful with logging.
49. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Let’s talk about load shedding.
50. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
51. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
52. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
53. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Don’t be overly optimistic and take on more than you can. Find an operational metric to reject what you cannot take in. Favor cached and static content Prioritize ELB health check (shallow) pings In an overload situation you have precious resources, do not let any of it go to waste. Load Shedding
54. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Service Degradation & Fallbacks
55. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. https://twitter.com/redditstatus/status/1116204502703493120
56. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Let’s talk about shuffle sharding.
57. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
58. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. X X X X X X X X ♤ ♡ ♢ ⚀ ⚁ ⚂ ⚃ ♧ ♢
59. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Measure for this: blast radius
60. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Blast radius • How many customers? • What functionality? • How many locations?
61. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
62. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Cell-based architecture X X ♤ ♡ ♢ ⚀ ⚁ ⚂ ⚃ ♧ ♢
63. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Shuffle sharding X X ♤ ♡ ♢ ⚀ ⚁⚂ ⚃ ♡ ♤ ♧ ♢ ⚀⚂ ♧ ⚁⚃ ♢ ♢ ♡ ♧ ♢
64. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Shuffle sharding Nodes = 8 Shard size = 2 Combinations = 28 Overlap % customers 0 53.6% 1 42.8% 2 3.6%
65. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Shuffle sharding Nodes = 100 Shard size = 5 Combinations = 75 million! Overlap % customers 0 77% 1 21% 2 1.8% 3 0.06% 4 0.0006% 5 0.0000013%
66. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Shuffle sharding
67. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Let’s talk about chaos!
68. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. GameDay at Amazon Creating Resiliency Through Destruction https://www.youtube.com/watch?v=zoz0ZjfrQ9s
69. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Chaos engineering https://github.com/Netflix/SimianArmy
70. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. “Chaos Engineering is the discipline of experimenting on a distributed system in order to build confidence in the system’s capability to withstand turbulent conditions in production.” http://principlesofchaos.org
71. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Failure injection Start small & build confidence •Application level •Host failure •Resource attacks (CPU, memory, …) •Network attacks (dependencies, latency, …) •Region attacks
72. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Learn more.
73. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. https://medium.com/@adhorn
74. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Plan for the worst, prepare for the unexpected.
75. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Get $50 AWS Credit -- http://bit.ly/xebi-aws
76. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Thank you Sébastien Stormacq @sebsto