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[jLove 2020] Where is my cache architectural patterns for caching microservices by example

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[jLove 2020] Where is my cache architectural patterns for caching microservices by example

  1. 1. Where is my cache? Architectural patterns for caching microservices Rafał Leszko @RafalLeszko rafalleszko.com Hazelcast
  2. 2. About me ● Integration 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. 3. About Hazelcast ● Distributed Company ● Open Source Software ● 140+ Employees ● Products: ○ Hazelcast IMDG ○ Hazelcast Jet ○ Hazelcast Cloud @Hazelcast www.hazelcast.com
  4. 4. ● Introduction ● Caching Architectural Patterns ○ Embedded ○ Embedded Distributed ○ Client-Server ○ Cloud ○ Sidecar ○ Reverse Proxy ○ Reverse Proxy Sidecar ● Summary Agenda
  5. 5. Service 1 Service 2 v1 Service 2 v2 Service 1 Service 4 v1 Service 4 v2 Service 4 v3 Ruby Microservice World
  6. 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. 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. 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. 9. ● Introduction ✔ ● Caching Architectural Patterns ○ Embedded ○ Embedded Distributed ○ Client-Server ○ Cloud ○ Sidecar ○ Reverse Proxy ○ Reverse Proxy Sidecar ● Summary Agenda
  10. 10. 1. Embedded
  11. 11. Application Load Balancer Cache Application Cache Request Embedded Cache
  12. 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. 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. 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. 15. CacheBuilder.newBuilder() .initialCapacity(300) .expireAfterAccess(Duration.ofMinutes(10)) .maximumSize(1000) .build(); Embedded Cache (Java libraries)
  16. 16. Embedded Cache (Java libraries) CacheBuilder.newBuilder() .initialCapacity(300) .expireAfterAccess(Duration.ofMinutes(10)) .maximumSize(1000) .build();
  17. 17. Caching Application Layer @Service public class BookService { @Cacheable("books") public String getBookNameByIsbn(String isbn) { return findBookInSlowSource(isbn); } }
  18. 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. 19. Application Load Balancer Cache Application Cache Request Embedded Cache
  20. 20. 1*. Embedded Distributed
  21. 21. Application Application Load Balancer Cache Cache Request Hazelcast Cluster Embedded Distributed Cache
  22. 22. @Configuration public class HazelcastConfiguration { @Bean CacheManager cacheManager() { return new HazelcastCacheManager( Hazelcast.newHazelcastInstance()); } } Embedded Distributed Cache (Spring with Hazelcast)
  23. 23. Hazelcast Discovery Plugins
  24. 24. Hazelcast Discovery Plugins
  25. 25. Hazelcast Discovery Plugins
  26. 26. Application Application Load Balancer Cache Cache Request Hazelcast Cluster Embedded Distributed Cache
  27. 27. 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
  28. 28. ● Introduction ✔ ● Caching Architectural Patterns ○ Embedded ✔ ○ Embedded Distributed ✔ ○ Client-Server ○ Cloud ○ Sidecar ○ Reverse Proxy ○ Reverse Proxy Sidecar ● Summary Agenda
  29. 29. 2. Client-Server
  30. 30. Application Load Balancer Application Request Cache Server Client-Server Cache
  31. 31. Application Load Balancer Application Request Cache Server Client-Server Cache
  32. 32. Application Load Balancer Application Request Cache Server Client-Server Cache Separate Management: ● backups ● (auto) scaling ● security Ops Team
  33. 33. Application Load Balancer Application Request Cache Server Client-Server Cache
  34. 34. Application Load Balancer Application Request Cache Server Client-Server Cache
  35. 35. Client-Server Cache
  36. 36. Client-Server Cache
  37. 37. Client-Server Cache $ hz start Starting Hazelcast Cache Server (standalone)
  38. 38. Client-Server Cache Starting Hazelcast Cache Server (Kubernetes) $ helm install hazelcast/hazelcast
  39. 39. Client-Server Cache Hazelcast Client (Kubernetes): @Configuration public class HazelcastClientConfiguration { @Bean CacheManager cacheManager() { return new HazelcastCacheManager(); } } Starting Hazelcast Cache Server (Kubernetes) $ helm install hazelcast/hazelcast
  40. 40. Application Load Balancer Application Request Cache Server Client-Server Cache Ops Team Separate Management: ● backups ● (auto) scaling ● security
  41. 41. 2*. Cloud
  42. 42. Application Load Balancer Application Request Cloud (Cache as a Service)
  43. 43. Application Load Balancer Application Request Cloud (Cache as a Service) Management: ● backups ● (auto) scaling ● security Ops Team
  44. 44. Application Load Balancer Application Request Cloud (Cache as a Service) Management: ● backups ● (auto) scaling ● security Ops Team
  45. 45. Application Load Balancer Application Request Cloud (Cache as a Service)
  46. 46. @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)
  47. 47. 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)
  48. 48. ● Introduction ✔ ● Caching Architectural Patterns ○ Embedded ✔ ○ Embedded Distributed ✔ ○ Client-Server ✔ ○ Cloud ✔ ○ Sidecar ○ Reverse Proxy ○ Reverse Proxy Sidecar ● Summary Agenda
  49. 49. 3. Sidecar
  50. 50. Kubernetes Service (Load Balancer) Request Hazelcast Cluster Kubernetes POD Application Container Cache Container Application Container Cache Container Kubernetes POD Sidecar Cache
  51. 51. 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
  52. 52. @Configuration public class HazelcastSidecarConfiguration { @Bean CacheManager cacheManager() { ClientConfig clientConfig = new ClientConfig(); clientConfig.getNetworkConfig() .addAddress("localhost:5701"); return new HazelcastCacheManager(HazelcastClient .newHazelcastClient(clientConfig)); } } Sidecar Cache
  53. 53. Sidecar Cache apiVersion: apps/v1 kind: Deployment ... spec: template: spec: containers: - name: application image: leszko/application - name: hazelcast image: hazelcast/hazelcast
  54. 54. 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
  55. 55. ● Introduction ✔ ● Caching Architectural Patterns ○ Embedded ✔ ○ Embedded Distributed ✔ ○ Client-Server ✔ ○ Cloud ✔ ○ Sidecar ✔ ○ Reverse Proxy ○ Reverse Proxy Sidecar ● Summary Agenda
  56. 56. 4. Reverse Proxy
  57. 57. Application Load Balancer Cache Application Request Reverse Proxy Cache
  58. 58. Reverse Proxy Cache http { ... proxy_cache_path /data/nginx/cache keys_zone=one:10m; ... }
  59. 59. ● Only for HTTP ● Not distributed ● No High Availability ● Data stored on the disk NGINX Reverse Proxy Cache Issues
  60. 60. 4*. Reverse Proxy Sidecar
  61. 61. 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
  62. 62. Good
  63. 63. Reverse Proxy Sidecar Cache Service 1 Service 2 v1 Service 2 v2 Service 1 Service 4 v1 Service 4 v2 Service 4 v3 Ruby
  64. 64. Reverse Proxy Sidecar Cache Service 1 Service 2 v1 Service 2 v2 Service 1 Service 4 v1 Service 4 v2 Service 4 v3 Ruby
  65. 65. Bad
  66. 66. Reverse Proxy Cache @CacheEvict(value = "someValue", allEntries = true) public void evictAllCacheValues() {} Application Cache:
  67. 67. 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; } }
  68. 68. 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)
  69. 69. ● Introduction ✔ ● Caching Architectural Patterns ○ Embedded ✔ ○ Embedded Distributed ✔ ○ Client-Server ✔ ○ Cloud ✔ ○ Sidecar ✔ ○ Reverse Proxy ✔ ○ Reverse Proxy Sidecar ✔ ● Summary Agenda
  70. 70. Summary
  71. 71. application-aware?
  72. 72. application-aware? containers? no
  73. 73. application-aware? containers? Reverse Proxy no no
  74. 74. application-aware? containers? Reverse Proxy Reverse Proxy Sidecar no yes no
  75. 75. application-aware? containers? Reverse Proxy Reverse Proxy Sidecar lot of data? security restrictions? yes no yes no
  76. 76. application-aware? containers? Reverse Proxy Reverse Proxy Sidecar lot of data? security restrictions? language-agnostic? containers? yes no yes nono
  77. 77. application-aware? containers? Reverse Proxy Reverse Proxy Sidecar lot of data? security restrictions? language-agnostic? containers? Embedded (Distributed) yes no yes no no no
  78. 78. 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
  79. 79. 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
  80. 80. 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
  81. 81. 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
  82. 82. Resources ● Code for this talk: https://github.com/leszko/caching-patterns ● Hazelcast Sidecar Container Pattern: https://hazelcast.com/blog/hazelcast-sidecar-container-pattern/ ● Hazelcast Reverse Proxy Sidecar Caching Prototype: https://github.com/leszko/caching-injector ● NGINX HTTP Reverse Proxy Caching: https://www.nginx.com/resources/videos/best-practices-for-caching/
  83. 83. Thank You! Rafał Leszko @RafalLeszko rafalleszko.com

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