The document discusses various architectural patterns for caching microservices, including embedded caching, embedded distributed caching, client-server caching, cloud caching, sidecar caching, reverse proxy caching, and reverse proxy sidecar caching. It provides examples and pros and cons of each pattern. The presentation concludes with a summary of when each pattern may be best suited based on factors like whether the application is aware of the cache, if it uses containers, the data volume, security restrictions, language agnostic needs, and cloud usage.

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

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. 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. 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

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. 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

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

26. Hazelcast Discovery Plugins

27. 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

33. 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

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

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

37. Client-Server Cache

38. Client-Server Cache

39. Client-Server Cache
$ hz start
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() {
return new HazelcastCacheManager();
}
}
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.setClusterName("test-cluster");
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

67. Good

68. 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
Service 1
Service 2
v1
Service 2
v2
Service 1
Service 4
v1
Service 4
v2
Service 4
v3
Ruby

70. 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

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

72. 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
Service 1
Service 2
v1
Service 2
v2
Service 1
Service 4
v1
Service 4
v2
Service 4
v3
Ruby

75. Reverse Proxy Sidecar Cache (Istio)

76. Reverse Proxy Sidecar Cache (Istio)

77. Bad

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

80. 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;
}
}

81. 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)

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

83. Summary

84. application-aware?

85. application-aware?
containers?
no

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

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

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

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

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

91. 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

92. 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

93. 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

94. 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

95. 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/

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