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AtlasCamp 2014: Preparing Your Plugin for JIRA Data Center
The document outlines key concepts for developers regarding Atlassian's Data Center, focusing on clustering, scalability, performance, and high availability. It also discusses best practices for plugin development, including cache management, scheduling tasks, and the use of locks in a clustered environment. Resources and references for further information on these topics are provided.
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AtlasCamp 2014: Preparing Your Plugin for JIRA Data Center
- 1. June 3-5, 2014| Berlin, Germany
- 2. Chris Fuller, SeniorDeveloper, Atlassian Data Center for Developers
- 3. • About DataCenter • Hazards for Plugins • Marketplace • Resources ! Data Center for Developers
- 4. • Clustering • Scaleand Performance • High Availability • Hardware Maintenance • Unexpected outages Data Center: The Reasons
- 5. Data Center: ThePicture Users WAN Index Database JIRA
- 6. Data Center: ThePicture WAN Users . . . Replicated Indexes Multiple JIRA Nodes Database Shared Home Load Balancer
- 7. • What youdon’t know… • Long-lived caches • Scheduled tasks • Locking Plugins: Danger Zone!
- 8. Sharing is Caring Oddsand Ends Locks Scheduled Tasks Caches
- 9. • Expensive Information •I/O costs • CPU costs • Caching is not free • Memory costs • Consistency risks Caches: The Problem ?!
- 10. • Local orclustered • Replication control • By invalidation • By copy • Lazy loading pattern • Statistical reporting Caches: Atlassian Cache 2.0
- 11. • Rolling yourown • HTTP Session as a cache • Unbounded caches • Custom key classes • Enumerating the keys Caches: Asking for Trouble ?!
- 12. • Don’t keepstate! • Atlassian Cache API • Lazy load pattern • Set bounds • Maximum size? • Timeout (30 minutes) • Use simple keys Caches: Best practices
- 13. Sharing is Caring Oddsand Ends Locks Caches Scheduled Tasks
- 14. • Per-node maintenance •Atlassian Scheduler API • SAL PluginScheduler • Backward compatibility • Confluence ! Scheduler: Local 1:00 2:00 3:00 4:00
- 15. • Runs onany one node • Atlassian Scheduler API • Quartz (Deprecated) • Compatibility library Scheduler: Clustered 1:00 2:00 3:00 4:00
- 16. • Atlassian SchedulerAPI • Clustered run-immediately job • Could run twice • Specify initial run time • Unscheduling on disable • Unschedules for whole cluster • Unregister job runner instead Scheduler: Dos and Don’ts
- 17. Sharing is Caring Oddsand Ends Caches Scheduled Tasks Locks
- 18. • synchronized • java.util.concurrent •atlassian-util-concurrent Locks: Local
- 19. • Atlassian Beehive •Cluster-wide • Cheap in single node Locks: Clustered
- 20. • Problems • Expensivein a cluster • Not read/write ! ! • Alternatives • Lock-free SQL ordering • Optimistic locking • Tolerating inconsistency • Transactions Locks: The Details
- 21. Sharing is Caring Caches Locks ScheduledTasks Odds and Ends
- 22. • Application HomeSplit • Local home • Shared home No Place Like Shared Home • Application Home Split • Local home • Shared home • Application Home Split • Local home • Shared home
- 23. Data Center Ready! <plugin-info> <description>${project.description}</description> <version>${project.version}</version> <vendorname="${project.organization.name}" url="${project.organization.url}" /> <param name="atlassian-data-center-compatible">true</param> </plugin-info>
- 24. • JIRA PluginGuide developer.atlassian.com/display/JIRADEV/Plugin+Guide+to+JIRA+High+Availability+and+Clustering • Confluence Plugin Guide developer.atlassian.com/pages/viewpage.action?pageId=2031761 • docs.atlassian.com/atlassian-cache-api • docs.atlassian.com/atlassian-scheduler-api • docs.atlassian.com/beehive-api • bitbucket.org/cfuller Resources
- 25. June 3-5, 2014| Berlin, Germany