Camel Desing Patterns Learned Through Blood, Sweat, and Tears
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Goes over the most commnonly used design patterns with Apache Camel. Based on Camel Design Patterns book
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Camel Desing Patterns Learned Through Blood, Sweat, and Tears
- 1. Apache Camel Design Patterns Learned Through Blood, Sweat, and Tears June 2016 Bilgin Ibryam @bibryam
- 2. Apache Camel Design Patterns Learned Through Blood, Sweat, and Tears2 Bilgin Ibryam ● Senior Middleware Architect at Red Hat UK ● Apache Camel Committer and PMC member ● Apache OFBiz Committer and PMC member ● Author of Camel Design Patterns (new) ● Author of Apache Camel Message Routing ● Twitter: @bibryam ● Email: bibryam@gmail.com ● Blog: http://ofbizian.com ● LinkedIn: http://www.linkedin.com/in/bibryam
- 3. Apache Camel Design Patterns Learned Through Blood, Sweat, and Tears3 Apache Camel Project Status It has all necessary ingredients for a successful open source project. ● Community: 52 committers, 903 users ● Support by large vendors (Red Hat) ● Connectors (256), DataFormats (40) ● Enterprise Integration Patterns++ ● Domain Specific Language ● Ecosystem: Karaf, ActiveMQ, CXF, Fabric, Hawtio, Spring and others ● Monolith, SOA, Microservices, Serverless Source https://www.openhub.net/p/camel/ Stats Date: 06/06/2016
- 4. Apache Camel Design Patterns Learned Through Blood, Sweat, and Tears4 Application Integration with Camel What do you need to know to create great Camel applications?
- 5. Apache Camel Design Patterns Learned Through Blood, Sweat, and Tears5 Happy Path Scenarios How Pipes and Filters Pattern looks like in Camel?
- 6. Apache Camel Design Patterns Learned Through Blood, Sweat, and Tears6 VETRO What is a typical processing flow for a Camel route? ● Validate: validation, schematron, MSV, Jing, bean validation components ● Enrich: enrich and pollEnrich EIPs, custom beans ● Transform: Data formats, auto type conversion, templating components ● Route: Message routing EIPs ● Operate: this is the essence of the processing flow
- 7. Apache Camel Design Patterns Learned Through Blood, Sweat, and Tears7 Edge Component Let's start with a simple Camel route that consumes files
- 8. Apache Camel Design Patterns Learned Through Blood, Sweat, and Tears8 Edge Component How to expose the same business functionality to multiple consumers?
- 9. Apache Camel Design Patterns Learned Through Blood, Sweat, and Tears9 Edge Component Encapsulate endpoint-specific details and prevent them from leaking into the business logic of an integration flow.
- 10. Apache Camel Design Patterns Learned Through Blood, Sweat, and Tears10 Read vs Write Operations How to evolve Read and Write operations independently?
- 11. Apache Camel Design Patterns Learned Through Blood, Sweat, and Tears11 CQRS This decouples read from write operations to allow them to evolve independently.
- 12. Apache Camel Design Patterns Learned Through Blood, Sweat, and Tears12 Unhappy Path Scenarios Happy paths are the easy ones. More work is required for designing and implementing the unhappy paths. ● Data Integrity Pattern ● Saga Pattern ● Retry Pattern ● Idempotent Filter Pattern ● Circuit Breaker Pattern ● Error Channels Pattern ● Throttling Pattern
- 13. Apache Camel Design Patterns Learned Through Blood, Sweat, and Tears13 Data Integrity How hard can it be to copy files from one location to another? Download Data Integrity Chapter: http://bit.ly/came-design-patterns-sample
- 14. Apache Camel Design Patterns Learned Through Blood, Sweat, and Tears14 Data Integrity Transactional systems Local transaction manager Global transaction manager
- 15. Apache Camel Design Patterns Learned Through Blood, Sweat, and Tears15 Saga How to avoid distributed transactions and ensure data consistency?
- 16. Apache Camel Design Patterns Learned Through Blood, Sweat, and Tears16 Saga Ensures that each step of the business process has a compensating action to undo the work completed in the case of partial failures.
- 17. Apache Camel Design Patterns Learned Through Blood, Sweat, and Tears17 Retry To enable applications handle anticipated transient failures by transparently retrying a failed operation with expectation it to be successful. ● Which failures to retry? ● How often to retry? ● Idempotency ● Monitoring ● Timeouts and SLAs
- 18. Apache Camel Design Patterns Learned Through Blood, Sweat, and Tears18 Retry Camel RedeliveryPolicy ● The most well known retry mechanism in Camel ● Retries only the failing endpoint ● Fully in-memory ● Thread blocking behavior by default ● Can be asynchronous ● Good for small number of quick retries (in milliseconds)
- 19. Apache Camel Design Patterns Learned Through Blood, Sweat, and Tears19 Retry ActiveMQ consumer RedeliveryPolicy ● Retries the message from the beginning of the Camel route ● Not used very often, but enabled by default ● Fully in-memory ● Thread blocking by default ● Good for small number of quick retries (in milliseconds)
- 20. Apache Camel Design Patterns Learned Through Blood, Sweat, and Tears20 Retry ActiveMQ Broker Redelivery ● ActiveMQ specific and requires custom logic ● It will consume the message again from a queue ● Persisted at the broker rather than application memory ● Can be clustered and use fail over, load balancing, etc ● Good for long persisted retries (in minutes or hours)
- 21. Apache Camel Design Patterns Learned Through Blood, Sweat, and Tears21 Circuit Breaker How to guard a system by cascading failures and slow responses from other systems?
- 22. Apache Camel Design Patterns Learned Through Blood, Sweat, and Tears22 Circuit Breaker Improves the stability and the resilience of a system by guarding integration points from cascading failures and slow responses. Closed state Open state
- 23. Apache Camel Design Patterns Learned Through Blood, Sweat, and Tears23 Circuit Breaker Improves the stability and the resilience of a system by guarding integration points from cascading failures and slow responses.
- 24. Apache Camel Design Patterns Learned Through Blood, Sweat, and Tears24 Circuit Breaker Two Circuit Breaker Implementations in Camel 2.18
- 25. Apache Camel Design Patterns Learned Through Blood, Sweat, and Tears25 Bulkhead How to enforce resource partitioning and damage containment in order to preserve partial functionality in the case of a failure?
- 26. Apache Camel Design Patterns Learned Through Blood, Sweat, and Tears26 Bulkhead Enforces resource partitioning and damage containment in order to preserve partial functionality in the case of a failure. ● Multi-threaded EIPs: Delayer, Multicast, Recipient List, Splitter, Threads, Throttler, Wire Tap, Polling Consumer, ProducerTemplate, and OnCompletion. ● Async Error Handler ● Circuit Breaker EIP Possible Camel bulkhead points:
- 27. Apache Camel Design Patterns Learned Through Blood, Sweat, and Tears27 Scalability Scenarios Vertical scaling (performance tuning) ● Endpoints: messaging client buffers, DB client batching, template caching choices ● Concurrent consumers option: Seda, VM, JMS, RabbitMQ, Disruptor, AWS-SQS ● Data types choice: affects content based router, splitter, filter, aggregator ● Multithreading: parallel processing EIPs, threads DSL construct, Seda component, asynchronous redelivery/retry ● Micro optimizations: log tuning, camel sampler EIP, disable JMX, disable message history, disable original message record ● Startup/Shutdown: Use lazyLoadTypeConverters for a faster application startup, or configure the shutdownStrategy for a faster shutdown ● Tune: JVM options, networking and operating system Camel performance tuning blog post: http://bit.ly/camel-tuning Camel performance tuning blog post: http://bit.ly/camel-tuning
- 28. Apache Camel Design Patterns Learned Through Blood, Sweat, and Tears28 Horizontal Scaling Service Instance Pattern for accommodating increasing workloads.
- 29. Apache Camel Design Patterns Learned Through Blood, Sweat, and Tears29 Service Instance Areas to consider before horizontally scaling a Camel application. ● Service state: load balancer, circuit breaker, resequencer, sampler, throttler, idempotent consumer and aggregator are stateful EIPs! ● Request dispatcher: Messaging, HTTP, file (what about locking?) ● Message ordering: exclusive consumer, message groups, consumer priority, message priority, virtual topics ● Singleton service requirements: for batch jobs, and concurrent polling ● Other resource contention and coupling considerations
- 30. Apache Camel Design Patterns Learned Through Blood, Sweat, and Tears30 What did we cover so far?
- 31. Apache Camel Design Patterns Learned Through Blood, Sweat, and Tears31 How patterns are changing? What is happening in the IT industry today? ● Canonical Data Model ● Edge Component ● Reusable Route ● Runtime Reconfiguration ● Singleton Service ● Batch jobs in JVM ● Bounded Context ● Standalone services ● Favor code duplication ● Less configuration, more redeployment ● Container managed singleton ● Container scheduling ● Circuit Breaker, Bulkhead, Health checks..
- 32. Apache Camel Design Patterns Learned Through Blood, Sweat, and Tears32 Win a print copy of Camel Design Patterns When was the first commit to Apache Camel project done?
- 33. Apache Camel Design Patterns Learned Through Blood, Sweat, and Tears33 Win a print copy of Camel Design Patterns When was the first commit to Apache Camel project done?
- 34. More Information Learn more about Apache Camel: http://camel.apache.org Check out Camel Design Patterns: https://leanpub.com/camel-design-patterns Develop Apache Camel based integrations using Red Hat JBoss Fuse: red.ht/FuseDev