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Where is my cache architectural patterns for caching microservices by example
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
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!
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!
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
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)
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)
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
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
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
72.
Reverse Proxy Sidecar Cache
Service 1
Service 2
v1
Service 2
v2
Service 1
Service 4
v1
Service 4
v2
Service 4
v3
Ruby
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)
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