While a microservices architecture is more scalable than a monolith, it has a direct hit on performance. To cope with that, one performance improvement is to set up a cache. It can be configured for database access, for REST calls or just to store session state across a cluster of server nodes. In this demo-based talk, I’ll show how Hazelcast In-Memory Data Grid can help you in each one of those areas and how to configure it. Hint: it’s much easier than one would expect.

1. @nicolas_frankel
3 performance improvements in your
microservices architecture
Nicolas Fränkel

2. @nicolas_frankel
Me, myself and I
 Former developer, team lead, architect,
blah-blah
 Developer Advocate
 Used to Enterprise stacks

3. @nicolas_frankel
Hazelcast
HAZELCAST IMDG is an operational,
in-memory, distributed computing
platform that manages data using
in-memory storage and performs
execution for breakthrough
and scale.
HAZELCAST JET is the ultra
fast, application embeddable,
3rd generation stream
processing engine for low
latency batch and stream
processing.

4. @nicolas_frankel
Microservices: a tentative definition
1. Componentization via Services
2. Smart endpoints and dumb pipes
3. Decentralized Governance
4. Decentralized Data Management
5. Infrastructure Automation
6. Design for failure
7. Evolutionary Design
8. Organized around Business Capabilities
9. Products not Projects
https://martinfowler.com/articles/microservices.html

5. @nicolas_frankel
A benefit: scalability
https://martinfowler.com/articles/microservices.html

6. @nicolas_frankel
Do you spot the difference?

7. @nicolas_frankel
Distributed systems
« You have to be in a really unusual spot to see in-process
function calls turn into a performance hot spot these days, but
remote calls are slow. If your service calls half-a-dozen
remote services, each which calls another half-a-dozen remote
services, these response times add up to some horrible
latency characteristics. »
-- https://martinfowler.com/articles/microservice-trade-offs.html

8. @nicolas_frankel
Fallacies of distributed computing
 The network is reliable
 Latency is zero
 Bandwidth is infinite
 The network is secure
 Topology doesn't change
 There is one administrator
 Transport cost is zero
 The network is homogeneous
https://yourlogicalfallacyis.com/

9. @nicolas_frankel
More like that…

10. @nicolas_frankel
No, like that!

11. @nicolas_frankel
Caching to the rescue
Fast vs. up-to-date

12. @nicolas_frankel

13. @nicolas_frankel
Caching?
Let’s use a hash map!
 Unbounded
 No eviction strategy
 No TTL
 etc.

14. @nicolas_frankel
In-Memory Data Grid
 A distributed object store
 Think distributed data structure

15. @nicolas_frankel
Caching use-cases in microservices
 Database access
 HTTP call
 Session data

16. @nicolas_frankel
Hibernate
 Object-Relational Mapping framework
 Quite widespread
 JPA implementation

17. @nicolas_frankel
Hibernate
 Level 1 cache
• Implemented by default
• Related to the Session object
 Level 2 cache
• Optional
• Multiple integrations available

18. @nicolas_frankel
Read-through
 The cache doesn’t contain the key
1. Load from the database
2. Put it in the cache
 The cache contains the key
1. Return it

19. @nicolas_frankel
Write-through
Create or update the cached value

20. @nicolas_frankel

21. @nicolas_frankel
Even faster alternative
 The code only interacts with Hazelcast
 Registered listeners allow to write to the
database
 Async
• No guarantee

22. @nicolas_frankel
HTTP and cache
 Could be implemented manually
 But there’s a Java API for that!

23. @nicolas_frankel
JCache
 Specification
 Multiple implementations
 Integrated with Spring

24. @nicolas_frankel
E-commerce architecture
 Catalog service
 Stock service
 Pricing service
 Cart service
 Recommendation service
 Payment service
 etc.

25. @nicolas_frankel

26. @nicolas_frankel
Session data in cluster nodes

27. @nicolas_frankel
Standards?

28. @nicolas_frankel
Hazelcast to the rescue!
1. Filter-based
2. Spring Session integration
3. Direct Tomcat integration
• Per-node configuration
• Or through Spring Boot embedded
4. Direct Jetty integration

29. @nicolas_frankel

30. @nicolas_frankel
Takeaways
 Scalability and performance are not the same
 Caching helps performance
• The cost is stale data
 Hazelcast IMDG provides several integration-points for caching
across different areas
• Database access
• HTTP call
• Session data

31. @nicolas_frankel
Thanks for your attention!
 https://blog.frankel.ch/
 @nicolas_frankel
 https://hazelcast.org/
 https://bit.ly/micro-perf