2. Distributed Tracing Of Microservices
Neil Stevenson, Solution Architect, Hazelcast

3. Talk Outline
Microservices are generally perceived as a better application style than monolithic code, and certainly this is a style that sits nicely within Cloud Foundry.
However, it’s not all good news. One of the drawbacks to such decomposition is it can be very difficult to identify bottlenecks.
In this presentation, Neil will show how it’s easy this can solved for Spring Boot users. A few beans and dependencies can activate tracing, and with Hazelcast as a service, trace information can be centrally captured from to a fault-tolerant scalable in-memory repository. Trace analysis can then be distributed across multiple service instances, without the performance bottleneck of a unclustered disk based resource.

4. Talk Outline 1 – Microservices 2 – Zipkin 3 – Hazelcast
Misbehaving microservices
2 – Zipkin
3 – Hazelcast
4 – Demo, a solution !

5. 1 - Microservices Q: What is a microservice ?
A: Not the entire application in one deployment unit
(my definition)
=> does one or a few functions for an application
=> ideally some sort of logical grouping to functions performed
=> ideally data separation, isolated domain models
=> may call other microservices
=> may be clustered
=> in CF terms an “app” or a “service”

6. 1 - Microservices – the demo app
Credit Cards -
A simple domain
1 => users have credit limits, how much they can spend
2 => transactions are permanent, record of money spent
3 => authorisations are transient and expiring, money you might spend
Available credit is derived => (1 – (2 + 3))

7. 1 - Microservices – the demo app
Credit Cards -
A web front end and REST/JSON microservices, all Spring Boot
1 => list users
2 => user first name and last name
3 => available credit for a user
4 => transactions list for a user
5 => authorisations list for a user
Microservice 3 calls microservices 4 and 5

8. 2 - Zipkin
What is it ?
An implementation of Open Tracing’s open standard for distributed tracing
Part of the Open Tracing project
Grew out from Google’s “Dapper” project
Large scale distributed system tracing

9. 2 - Zipkin Key concept : Spans & Traces
A request to Application #1 might invoke calls to Application #2 and Application #3.
Application #1 may appear slow if Application #2 takes a while
Zipkin adds HTTP Headers so we can correlate the call to Application #2 as originating from a parent call to Application #1

10. 2 - Zipkin Key concept : Spans & Traces
A request to Application #1 might invoke calls to Application #2 and Application #3.
Span is overall, Trace is the particular call

11. 2 - Zipkin Architecture Separable… Zipkin User Interface Server
App
Storage
traces

12. 2 - Zipkin Architecture Storage => If only there was another….
zipkin.storage.type
=> Cassandra
=> MySql
=> In-Memory in JVM
=> not for Prod
=> If only there was another….
User Interface
Server
App
Storage
traces

13. 2 - Zipkin How to configure it ?
Set spring.application.name for Spring Boot
Add
<dependency>
<groupId>org.springframework.cloud</groupId>
<artifactId>spring-cloud-starter-zipkin</artifactId>
</dependency>

14. 3 - Hazelcast Hazelcast is a software company based in Palo Alto
Silver member of the Cloud Foundry Foundation
Two free open-source software products, with optional commercial enhancements

15. In-Memory Data Grid
Java storage, but connectors for .NET, Node.js, etc
Production grade, widely used
Spring Boot supports for auto-configuration
Many many features, but for today
Provides java.util.concurrent.ConcurrentMap
=> sharded across multiple JVMs, scalable
=> backed up across multiple JVMs, robust
=> with querying and indexes
=> with optional (commercial) monitoring
=> with wrapper for Spring

16. 3 - - In-Memory Data Grid Java cluster Key-Value Map Split across JVMs
Duplicated

17. 3 - - In-Memory Data Grid Java cluster Java & non-Java clients
Clojure community effort, perhaps GoLang next

18. 4 - Demo Several moving parts Some in and some out of CF
=> Zipkin server
=> Hazelcast storage JVMs
=> 1 web application, 1 instance of this
=> 5 microservices, 1 instance of each
=> one is misbehaving
Some in and some out of CF
=> The usual legacy jumble
=> HTTP to the rescue
Not a greenfield, a brownfield!

19. 4 - Demo Zipkin Server Traces MS 1 WEB APP MS 2 Hazelcast Server3 MS 5
Trans
Trans

20. 4 - Demo

21. 5 - Summary Add: Set: Track: A Zipkin server
”spring-cloud-starter-zipkin” to your dependencies
“spring.application.name” to YML
=> and Spring Boot does the REST
Set:
“zipkin.storage.type=hazelcast”
Track:
“ for updates, such as Zipkin2

22. The End Today neil@hazelcast.com
The basis
Current version of Zipkin 2.2.1
Demo using , still evolving