Architectural patterns for caching microservices

1. Architectural patterns for caching microservices Rafał Leszko @RafalLeszko rafalleszko.com Hazelcast

2. About me ● Cloud-Native Team Lead 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. Service 1 Service 2 v1 Service 2 v2 Service 1 Service 4 v1 Service 4 v2 Service 4 v3 Ruby Microservice World

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

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

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

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

10. 1. Embedded

11. Application Load Balancer Cache Application Cache Request Embedded Cache

12. 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)

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. ● 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!

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

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

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

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

19. Application Load Balancer Cache Application Cache Request Embedded Cache

20. 1*. Embedded Distributed

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

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

23. DEMO

24. Hazelcast Discovery Plugins

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

28. 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

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

30. 2. Client-Server

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

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

36. Client-Server Cache

37. Client-Server Cache

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

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

40. Client-Server Cache Hazelcast Client (Kubernetes): @Configuration public class HazelcastClientConfiguration { @Bean CacheManager cacheManager() { return new HazelcastCacheManager(HazelcastClient .newHazelcastClient()); } } Starting Hazelcast Cache Server (Kubernetes) $ helm install hazelcast/hazelcast

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

42. 2*. Cloud

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

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

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)

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

48. DEMO cloud.hazelcast.com

49. 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)

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

51. 3. Sidecar

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

53. 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

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

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

56. 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

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

58. 4. Reverse Proxy

59. Application Load Balancer Cache Application Request Reverse Proxy Cache

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

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

62. 4*. Reverse Proxy Sidecar

63. 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

64. Good

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

67. 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

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

70. Bad

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

72. 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; } }

73. 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)

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

75. Summary

76. application-aware?

77. application-aware? containers? no

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

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

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

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

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

83. 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

84. 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

85. 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 no no no

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

87. 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/

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

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