Pragmatic Scalability: Under the Hood of Artifactory HA

Application scalability is hard. Application scalability done right is even harder.

While some might try to write a distributed clustering framework from scratch, a Pragmatic Developer, from another hand, most likely will leverage mature open source framework, like Hazelcast, that takes care of all the hassle. In this session, you will learn how the pragmatic developers of JFrog benefited from using battle-tested clustering capabilities of Hazelcast while building Artifactory High Availability feature.

Transcript

1. Pragmatic Scalability Under the hood of Artifactory HA
2. whoiam Senõr Solutions Architect @Hazelcast @gAmUssA on the internetz
3. What’s Artifactory HA
5. Artifactory HA Challenges • Concurrent and Distributed access to binaries • Repository Cache • Job Notifications • Connectivity / Node Discovery
6. Artifactory HA (powered by Hazelcast) • Distributed Lock (ILock) • Distributed Map (IMap) • Distributed Topic • Membership Listener • Discovery SPI
7. What’s Hazelcast 01001 10101 01010 In Memory Data Computing In Memory Data Messaging + + In Memory Data Storage
8. Distribute Concurrency Control
10. Concurrent and Distributed Access to the Binaries
11. ILock • Extends java.util.concurrent.locks.Lock • Is re-entrant • The ILock has 1 synchronous backup • Owner member goes down, lock is released • ILock is fair and grants lock in order of request • ILock can return a Condition.
12. ILock HazelcastInstance hz = Hazelcast.newHazelcastInstance(); // Acquire the lock outside the try-catch block. // We may fail to get the lock but the finally unlock will // still run if we acquire inside try-catch ILock myLock = hz.getLock("myLock"); try { // Doing my protected stuff here. // No other distributed member can execute this code. } finally { myLock.unlock(); } }
13. ILock HazelcastInstance hz = Hazelcast.newHazelcastInstance(); // Acquire the lock outside the try-catch block. // We may fail to get the lock but the finally unlock will // still run if we acquire inside try-catch ILock myLock = hz.getLock("myLock"); try { // Doing my protected stuff here. // No other distributed member can execute this code. } finally { myLock.unlock(); } }
14. demo
15. Distributed Cache
19. CACHES
21. Green Primary Green Backup Green Shard
22. Hazelcast Deployment Options Great for early stages of rapid application development and iteration and for OEM. Necessary for scale-up or scale-out deployments – decouples upgrading of clients and cluster Embedded Mode Hazelcast Node 1 Applications Java API Client-Server Mode Hazelcast Node 3 Java API Applications .Net API Applications C++ API Applications Hazelcast Node 2 Hazelcast Node 1 Hazelcast Node 2 Applications Java API Hazelcast Node 3 Applications Java API
23. demo
24. Messaging and Notifications
27. © 2016 Hazelcast Inc. 27 Connectivity and Discovery
28. Membership Listener public interface MembershipListener extends EventListener { void memberAdded(MembershipEvent me); void memberRemoved(MembershipEvent me); void memberAttributeChanged(MemberAttributeEvent mae); }
29. Any Cloud, Anytime – Discovery SPI Cloud & Cloud Discovery Plugins Deployment Options YARN Apache jClouds PaaS Environment Integrations
31. demo
33. How we can make things even better • Distributed Executor Service for distributed jobs • Entry Processor for atomic data changes • Discovery SPI for Cloud and custom topologies