Stability anti patterns in cloud-native applications
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GDG DevFest 2020 Romania
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Stability anti patterns in cloud-native applications
- 1. Stability anti-patterns in cloud-native applications #devfestRO @ammbra1508
- 2. I am Ana Solutions Architect @ IBM Co-founder of Bucharest Software Craftsmanship Community HELLO! #devfestRO @ammbra1508
- 3. #devfestRO @ammbra1508 • I am Ana • Solutions Architect @ IBM • Co-founder of Bucharest Software Craftsmanship Community HELLO! #devfestRO @ammbra1508 What are anti-patterns? An anti-pattern is a common response to a recurring problem that is usually ineffective and risks being highly counterproductive. Wikipedia
- 4. #devfestRO @ammbra1508 • I am Ana • Solutions Architect @ IBM • Co-founder of Bucharest Software Craftsmanship Community HELLO! #devfestRO @ammbra1508 STABILITY Continue to work with a SYSTEM DISRUPTIONS OCCUR TEMPORARY SHOCKS CONTINUOUS LOAD STRESS COMPONENT FAILURES Users can Even when System Stability
- 5. Application deployments in a specific order #devfestRO @ammbra1508
- 7. #devfestRO @ammbra1508 #devfestRO @ammbra1508 A specific order to the start and stop processes when bringing up applications. A deployment depends on previous successful deployment of another application. A service waits for another component to be available. kubectl wait --for=condition=ready pod -l app=backend Examples and symptoms
- 8. #devfestRO @ammbra1508 #devfestRO @ammbra1508 Why is it bad? Wait time between deployments equals application not fully functional When the condition is never met, the next deployment cannot proceed and the process breaks.
- 9. #devfestRO @ammbra1508 #devfestRO @ammbra1508 Solutions at design level Concurrently deploy and start all parts of an application. Use retry patterns. Use circuit-breaker patterns.
- 10. #devfestRO @ammbra1508 #devfestRO @ammbra1508 Choose a deployment strategy Blue/green deployments for instant rollout/rollback LB Pod v2 Pod v2 1. Pod v3 Pod v3 LB Pod v2 Pod v2 2. Pod v3 Pod v3 LB Pod v3 Pod v3 3. Pod v2 Pod v2 LB Pod v3 Pod v3 4. Pod v2 Pod v2
- 11. #devfestRO @ammbra1508 #devfestRO @ammbra1508 Choose a deployment strategy Canary deployments when the user does the testing LB Pod v3 Pod v3 1. Pod v4 LB Pod v3 Pod v3 2. Pod v4 LB Pod v3 Pod v3 Pod v4 3. LB Pod v4 Pod v4 Pod v4 4.
- 12. Integration communication and composition #devfestRO @ammbra1508
- 13. #devfestRO @ammbra1508 HELLO! #devfestRO @ammbra1508 Synchronous call-and-response based system Queue-based messaging systems System-to-System messaging via SMTP or SMS Integration via synchronous communication with a software that forces the calling system to wait/stop from what is doing. Containerizing the middleware as is. Distorted usage of declarative deployment pattern. Examples and symptoms
- 14. #devfestRO @ammbra1508 • I am Ana • Solutions Architect @ IBM • Co-founder of Bucharest Software Craftsmanship Community HELLO! #devfestRO @ammbra1508 Requests may be sent but not receive a reply. The provider claims to send a different response format. Synchronous calls are vicious amplifiers that facilitate blockages. Tightly coupled middleware amplifies shocks to the system. Why is it bad?
- 15. #devfestRO @ammbra1508 • I am Ana • Solutions Architect @ IBM • Co-founder of Bucharest Software Craftsmanship Community HELLO! #devfestRO @ammbra1508 Application Level Solutions (1) Circuit Breaker pattern ✚ Consider delayed retries. ✚ Report, record and correlate state changes.
- 16. #devfestRO @ammbra1508 • I am Ana • Solutions Architect @ IBM • Co-founder of Bucharest Software Craftsmanship Community HELLO! #devfestRO @ammbra1508 Application Level Solutions (2) Failure rate threshold Configuration example for SpringBoot with Resillience4j Allowed number of calls in half- open state Sliding window Wait duration
- 17. #devfestRO @ammbra1508 • I am Ana • Solutions Architect @ IBM • Co-founder of Bucharest Software Craftsmanship Community HELLO! #devfestRO @ammbra1508 Is this enough? Yes, if your end-user is happy that <<real>> data is not present in the response. Yes, if your fallback method retrieves a unified satisfying response.
- 18. #devfestRO @ammbra1508 • I am Ana • Solutions Architect @ IBM • Co-founder of Bucharest Software Craftsmanship Community HELLO! #devfestRO @ammbra1508 Transition Solutions (1) DETERMINE THE OUTAGE PATTERN BASED ON MAINTENANCE WINDOW CACHE SOLUTION Stress testing + Load Testing
- 19. #devfestRO @ammbra1508 • I am Ana • Solutions Architect @ IBM • Co-founder of Bucharest Software Craftsmanship Community HELLO! #devfestRO @ammbra1508 Transition Solutions (2) Cache Hit: Check if TTL of first layer cache expired NO: Return the response from Redis. YES: Go at 2nd layer cache and find entry: Try to call the real method On Success: Store the new result with a proper TTL On Failure: Extend the existing TTL to put it back into the first layer and return the result. Cache miss: Try to call the real method On Success: Store the new result with a proper TTL On Failure: Return a result covering the miss. Record the failure. helm3 install my-redis stable/redis
- 20. Source: “Inside out” animation by Pixar https://www.psychologies.co.uk/inside-out-interview-creators
- 21. #devfestRO @ammbra1508 • I am Ana • Solutions Architect @ IBM • Co-founder of Bucharest Software Craftsmanship Community HELLO! #devfestRO @ammbra1508 Circuit breaker Traefik Solutions at Kubernetes level(1)
- 22. #devfestRO @ammbra1508 • I am Ana • Solutions Architect @ IBM • Co-founder of Bucharest Software Craftsmanship Community HELLO! #devfestRO @ammbra1508 Circuit breaker Istio Traefik Solutions at Kubernetes level(2)
- 23. Unlimited resources mirage #devfestRO @ammbra1508
- 25. Not setting memory or CPU can result into scheduling an unlimited number of pods on any node. The container could use all of the available memory on its node, possibly invoking the OOM (out of memory) Killer. The default memory limit of the namespace (in which the container is running) is assigned to the container. #devfestRO#devfestRO @ammbra1508 Why is it bad?
- 26. #devfestRO @ammbra1508 #devfestRO @ammbra1508 Solutions at Kubernetes level Set memory and CPU requests below their limits Control resource limits via ResourceQuotas and LimitRange in the namespace settings. Keep the CPU request at 1 core or below and use ReplicaSets to scale it out.
- 28. #devfestRO @ammbra1508 • I am Ana • Solutions Architect @ IBM • Co-founder of Bucharest Software Craftsmanship Community HELLO! #devfestRO @ammbra1508 2 hosts, 2 instances, 300 threads 3000 threads 70 instances 20 hosts Anytime you have a “many-to-one” or “many-to-few” relationship. Amplify the scaling effects through “shared resource” or ”commons project”. Dangerously combining horizontal and vertical autoscaling. Counterproductive usage of predictable demands and elastic scale patterns. Examples and symptoms
- 29. #devfestRO @ammbra1508 • I am Ana • Solutions Architect @ IBM • Co-founder of Bucharest Software Craftsmanship Community HELLO! #devfestRO @ammbra1508 One service can flood another with requests beyond its capacity. Shared resources are a capacity constraint. Why is it bad?
- 30. #devfestRO @ammbra1508 • I am Ana • Solutions Architect @ IBM • Co-founder of Bucharest Software Craftsmanship Community HELLO! #devfestRO @ammbra1508 Solutions at design level Approximate a shared-nothing architecture through reducing the number of callers of the shared resource. Design for pairs of applications that each act as a failover for the other.
- 31. #devfestRO @ammbra1508 • I am Ana • Solutions Architect @ IBM • Co-founder of Bucharest Software Craftsmanship Community HELLO! #devfestRO @ammbra1508 Provision cluster nodes to have the same resource footprint. Ensure that the cluster autoscaler pod has enough resources. To avoid delays in provisioning, over-provision your cluster. https://github.com/kubernetes/autoscaler/blob/master/cluster- autoscaler/FAQ.md#how-can-i-configure-overprovisioning-with- cluster-autoscaler Solutions at Kubernetes level(1)
- 32. #devfestRO @ammbra1508 • I am Ana • Solutions Architect @ IBM • Co-founder of Bucharest Software Craftsmanship Community HELLO! #devfestRO @ammbra1508 Ensure that every pod has resource requests defined. Validate that resource requests are close to actual usage. Install metrics-server and configure custom/external metrics. Specify PodDisruptionBudget for application pods. Solutions at Kubernetes level(2)
- 33. #devfestRO @ammbra1508 Takeaways Avoid deploying things in a specific order: applications should not wait because a dependency is not ready. Consider setting memory and CPU limits to reduce the risk of resource contention and that resource requests are close to actual usage. Utilize Kubernetes’s self-healing mechanism, implement retries and circuit breakers both at application and Kubernetes level. Avoid using both HPA and VPA; consider installing metrics-server and adding custom metrics for horizontal scaling.