Where is my cache architectural patterns for caching microservices by example

1. Where is my cache? Architectural patterns for caching microservices by example Rafał Leszko @RafalLeszko rafalleszko.com Hazelcast

2. About me ● Cloud Software Engineer at Hazelcast ● Worked at Google and CERN ● Author of the book "Continuous Delivery with Docker and Jenkins" ● Trainer and conference speaker ● Live in Kraków, Poland

3. About Hazelcast ● Distributed Company ● Open Source Software ● 140+ Employees ● Products: ○ Hazelcast IMDG ○ Hazelcast Jet ○ Hazelcast Cloud @Hazelcast www.hazelcast.com

4. ● Introduction ● Caching Architectural Patterns ○ Embedded ○ Embedded Distributed ○ Client-Server ○ Cloud ○ Sidecar ○ Reverse Proxy ○ Reverse Proxy Sidecar ● Summary Agenda

5. Why Caching? ● Performance ○ Decrease latency ○ Reduce load ● Resilience ○ High availability ○ Lower downtime

6. Service 1 Service 2 v1 Service 2 v2 Service 1 Service 4 v1 Service 4 v2 Service 4 v3 Ruby Microservice World

7. Service 1 Service 2 v1 Service 2 v2 Service 1 Service 4 v1 Service 4 v2 Service 4 v3 Ruby Microservice World cache cache cache cache

8. Service 1 Service 2 v1 Service 2 v2 Service 1 Service 4 v1 Service 4 v2 Service 4 v3 Ruby Microservice World cache cache cache

9. Service 1 Service 2 v1 Service 2 v2 Service 1 Service 4 v1 Service 4 v2 Service 4 v3 Ruby Microservice World cache cache cache

10. ● Introduction ✔ ● Caching Architectural Patterns ○ Embedded ○ Embedded Distributed ○ Client-Server ○ Cloud ○ Sidecar ○ Reverse Proxy ○ Reverse Proxy Sidecar ● Summary Agenda

11. 1. Embedded

12. Application Load Balancer Cache Application Cache Request Embedded Cache

13. private ConcurrentHashMap<String, String> cache = new ConcurrentHashMap<>(); private String processRequest(String request) { if (cache.contains(request)) { return cache.get(request); } String response = process(request); cache.put(request, response); return response; } Embedded Cache (Pure Java implementation)

14. private ConcurrentHashMap<String, String> cache = new ConcurrentHashMap<>(); private String processRequest(String request) { if (cache.contains(request)) { return cache.get(request); } String response = process(request); cache.put(request, response); return response; } Embedded Cache (Pure Java implementation)

15. ● No Eviction Policies ● No Max Size Limit (OutOfMemoryError) ● No Statistics ● No built-in Cache Loaders ● No Expiration Time ● No Notification Mechanism Java Collection is not a Cache!

16. CacheBuilder.newBuilder() .initialCapacity(300) .expireAfterAccess(Duration.ofMinutes(10)) .maximumSize(1000) .build(); Embedded Cache (Java libraries)

17. Embedded Cache (Java libraries) CacheBuilder.newBuilder() .initialCapacity(300) .expireAfterAccess(Duration.ofMinutes(10)) .maximumSize(1000) .build();

18. Caching Application Layer @Service public class BookService { @Cacheable("books") public String getBookNameByIsbn(String isbn) { return findBookInSlowSource(isbn); } }

19. Caching Application Layer @Service public class BookService { @Cacheable("books") public String getBookNameByIsbn(String isbn) { return findBookInSlowSource(isbn); } } Be Careful, Spring uses ConcurrentHashMap by default!

20. Application Load Balancer Cache Application Cache Request Embedded Cache

21. 1*. Embedded Distributed

22. Application Application Load Balancer Cache Cache Request Hazelcast Cluster Embedded Distributed Cache

23. @Configuration public class HazelcastConfiguration { @Bean CacheManager cacheManager() { return new HazelcastCacheManager( Hazelcast.newHazelcastInstance()); } } Embedded Distributed Cache (Spring with Hazelcast)

24. DEMO

25. Hazelcast Discovery Plugins

28. Application Application Load Balancer Cache Cache Request Hazelcast Cluster Embedded Distributed Cache

29. Embedded Cache Pros Cons ● Simple configuration / deployment ● Low-latency data access ● No separate Ops Team needed ● Not flexible management (scaling, backup) ● Limited to JVM-based applications ● Data collocated with applications

30. ● Introduction ✔ ● Caching Architectural Patterns ○ Embedded ✔ ○ Embedded Distributed ✔ ○ Client-Server ○ Cloud ○ Sidecar ○ Reverse Proxy ○ Reverse Proxy Sidecar ● Summary Agenda

31. 2. Client-Server

32. Application Load Balancer Application Request Cache Server Client-Server Cache

34. Application Load Balancer Application Request Cache Server Client-Server Cache Separate Management: ● backups ● (auto) scaling ● security Ops Team

37. Client-Server Cache

38. Client-Server Cache

39. Client-Server Cache $ ./start.sh Starting Hazelcast Cache Server (standalone)

40. Client-Server Cache Starting Hazelcast Cache Server (Kubernetes) $ helm install hazelcast/hazelcast

41. Client-Server Cache Hazelcast Client (Kubernetes): @Configuration public class HazelcastClientConfiguration { @Bean CacheManager cacheManager() { ClientConfig clientConfig = new ClientConfig(); clientConfig.getNetworkConfig().getKubernetesConfig() .setEnabled(true); return new HazelcastCacheManager(HazelcastClient .newHazelcastClient(clientConfig)); } } Starting Hazelcast Cache Server (Kubernetes) $ helm install hazelcast/hazelcast

42. Application Load Balancer Application Request Cache Server Client-Server Cache Ops Team Separate Management: ● backups ● (auto) scaling ● security

43. 2*. Cloud

44. Application Load Balancer Application Request Cloud (Cache as a Service)

45. Application Load Balancer Application Request Cloud (Cache as a Service) Management: ● backups ● (auto) scaling ● security Ops Team

46. Application Load Balancer Application Request Cloud (Cache as a Service) Management: ● backups ● (auto) scaling ● security Ops Team

47. Application Load Balancer Application Request Cloud (Cache as a Service)

48. @Configuration public class HazelcastCloudConfiguration { @Bean CacheManager cacheManager() { ClientConfig clientConfig = new ClientConfig(); clientConfig.getNetworkConfig().getCloudConfig() .setEnabled(true) .setDiscoveryToken("KSXFDTi5HXPJGR0wRAjLgKe45tvEEhd"); clientConfig.setGroupConfig( new GroupConfig("test-cluster", "b2f984b5dd3314")); return new HazelcastCacheManager( HazelcastClient.newHazelcastClient(clientConfig)); } } Cloud (Cache as a Service)

49. DEMO cloud.hazelcast.com

50. Client-Server (Cloud) Cache Pros ● Data separate from applications ● Separate management (scaling, backup) ● Programming-language agnostic Cons ● Separate Ops effort ● Higher latency ● Server network requires adjustment (same region, same VPC)

51. ● Introduction ✔ ● Caching Architectural Patterns ○ Embedded ✔ ○ Embedded Distributed ✔ ○ Client-Server ✔ ○ Cloud ✔ ○ Sidecar ○ Reverse Proxy ○ Reverse Proxy Sidecar ● Summary Agenda

52. 3. Sidecar

53. Kubernetes Service (Load Balancer) Request Hazelcast Cluster Kubernetes POD Application Container Cache Container Application Container Cache Container Kubernetes POD Sidecar Cache

54. Sidecar Cache Similar to Embedded: ● the same physical machine ● the same resource pool ● scales up and down together ● no discovery needed (always localhost) Similar to Client-Server: ● different programming language ● uses cache client to connect ● clear isolation between app and cache

55. @Configuration public class HazelcastSidecarConfiguration { @Bean CacheManager cacheManager() { ClientConfig clientConfig = new ClientConfig(); clientConfig.getNetworkConfig() .addAddress("localhost:5701"); return new HazelcastCacheManager(HazelcastClient .newHazelcastClient(clientConfig)); } } Sidecar Cache

56. Sidecar Cache apiVersion: apps/v1 kind: Deployment ... spec: template: spec: containers: - name: application image: leszko/application - name: hazelcast image: hazelcast/hazelcast

57. Sidecar Cache Pros Cons ● Simple configuration ● Programming-language agnostic ● Low latency ● Some isolation of data and applications ● Limited to container-based environments ● Not flexible management (scaling, backup) ● Data collocated with application PODs

58. ● Introduction ✔ ● Caching Architectural Patterns ○ Embedded ✔ ○ Embedded Distributed ✔ ○ Client-Server ✔ ○ Cloud ✔ ○ Sidecar ✔ ○ Reverse Proxy ○ Reverse Proxy Sidecar ● Summary Agenda

59. 4. Reverse Proxy

60. Application Load Balancer Cache Application Request Reverse Proxy Cache

61. Reverse Proxy Cache http { ... proxy_cache_path /data/nginx/cache keys_zone=one:10m; ... }

62. ● Only for HTTP ● Not distributed ● No High Availability ● Data stored on the disk NGINX Reverse Proxy Cache Issues

63. NGINX Reverse Proxy Cache Issues ● Only for HTTP ● Not distributed ● No High Availability ● Data stored on the disk

64. 4*. Reverse Proxy Sidecar

65. Kubernetes Service (Load Balancer) Request Hazelcast Cluster Kubernetes POD Application Container Reverse Proxy Cache Container Application Container Reverse Proxy Cache Container Kubernetes POD Reverse Proxy Sidecar Cache

66. Good

67. Reverse Proxy Sidecar Cache Service 1 Service 2 v1 Service 2 v2 Service 1 Service 4 v1 Service 4 v2 Service 4 v3 Ruby

69. Reverse Proxy Sidecar Cache apiVersion: apps/v1 kind: Deployment ... spec: template: spec: initContainers: - name: init-networking image: leszko/init-networking containers: - name: caching-proxy image: leszko/caching-proxy - name: application image: leszko/application

70. Reverse Proxy Cache Container Application Container eth0 :80 Reverse Proxy Sidecar Cache :80 Pod :8000 lo :80

71. Reverse Proxy Sidecar Cache #!/bin/bash # Forward TCP traffic on port 80 to port 8000 on the eth0 interface. iptables -t nat -A PREROUTING -p tcp -i eth0 --dport 80 -j REDIRECT --to-port 8000

73. Reverse Proxy Sidecar Cache (Istio)

74. Bad

75. Reverse Proxy Cache @CacheEvict(value = "someValue", allEntries = true) public void evictAllCacheValues() {} Application Cache:

76. Reverse Proxy Cache @CacheEvict(value = "someValue", allEntries = true) public void evictAllCacheValues() {} Application Cache: Proxy Cache: http { ... location / { add_header Cache-Control public; expires 86400; etag on; } }

77. Reverse Proxy (Sidecar) Cache Pros Cons ● Configuration-based (no need to change applications) ● Programming-language agnostic ● Consistent with containers and microservice world ● Difficult cache invalidation ● No mature solutions yet ● Protocol-based (e.g. works only with HTTP)

78. ● Introduction ✔ ● Caching Architectural Patterns ○ Embedded ✔ ○ Embedded Distributed ✔ ○ Client-Server ✔ ○ Cloud ✔ ○ Sidecar ✔ ○ Reverse Proxy ✔ ○ Reverse Proxy Sidecar ✔ ● Summary Agenda

79. Summary

80. application-aware?

81. application-aware? containers? no

82. application-aware? containers? Reverse Proxy no no

83. application-aware? containers? Reverse Proxy Reverse Proxy Sidecar no yes no

84. application-aware? containers? Reverse Proxy Reverse Proxy Sidecar lot of data? security restrictions? yes no yes no

85. application-aware? containers? Reverse Proxy Reverse Proxy Sidecar lot of data? security restrictions? language-agnostic? containers? yes no yes nono

86. application-aware? containers? Reverse Proxy Reverse Proxy Sidecar lot of data? security restrictions? language-agnostic? containers? Embedded (Distributed) yes no yes no no no

87. application-aware? containers? Reverse Proxy Reverse Proxy Sidecar lot of data? security restrictions? language-agnostic? containers? Embedded (Distributed) Sidecar yes no yes yes no no no

88. application-aware? containers? Reverse Proxy Reverse Proxy Sidecar lot of data? security restrictions? language-agnostic? containers? Embedded (Distributed) Sidecar cloud? yes no yes yes yes no no no

89. application-aware? containers? Reverse Proxy Reverse Proxy Sidecar lot of data? security restrictions? language-agnostic? containers? Embedded (Distributed) Sidecar cloud? Client-Server yes no yes yes yes no nono no

90. application-aware? containers? Reverse Proxy Reverse Proxy Sidecar lot of data? security restrictions? language-agnostic? containers? Embedded (Distributed) Sidecar cloud? Client-ServerCloud yes no yes yes yes yes no nono no

91. Resources ● Hazelcast Sidecar Container Pattern: https://hazelcast.com/blog/hazelcast-sidecar-container-pattern/ ● Hazelcast Reverse Proxy Sidecar Caching Prototype: https://github.com/leszko/caching-injector ● Caching Best Practices: https://vladmihalcea.com/caching-best-practices/ ● NGINX HTTP Reverse Proxy Caching: https://www.nginx.com/resources/videos/best-practices-for-caching/

92. Thank You! Rafał Leszko @RafalLeszko rafalleszko.com