Date post: | 03-Dec-2014 |
Category: |
Software |
Upload: | ryan-hoegg |
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Building Performant, Reliable, Scalable Integrations with Mule ESB
Ryan Hoegg, Integration Architect, ConfluexRupesh Ramachandran, Solutions Architect, MuleSoft
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Service Level Agreement
First Class Requirements
Precision Matters
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Reliability SLAs
AvailabilityUptimeTime to Recovery
Message LossMaximum GuaranteeDetectionRecovery
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Scalability SLAs
CapacityPeakSustained(Degraded)
Message VolumeMessage Size
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Performance SLAs
Response Time ThroughputConcurrencySustainability
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Performance Tuning: Big picture
Mule ESBJVMOperating SystemFile SystemNetworkDownstream Systems
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Performance: Best Practices
Asynchronous vs SynchronousReal-time vs BatchStateful vs Stateless (web scale)On-Premise vs iPaaS
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Performance: Manage SLA’s
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Performance: Case Study
Use Case: API GatewayXML to JSON transformsMixed Payload Sizes
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Performance: Case Study
Test Case Mule ESB 3.5 EE as API Gateway
Infrastructure Amazon EC2 with 10GbE network
Throughput ~8000tps
Latency ~5ms
Scale Linear scale out, to 6 boxes*
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Performance Characteristics: Mule ESB 3.5 EE
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Making SLAs a Reality
PrioritizeModelMeasure
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Tuning: Focusing on What Matters
ObserveIdentify hot spotGenerate loadCompare with SLA
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Tuning: Improve Scalability
Scale Up, Scale OutSEDAStore and ForwardMessage Oriented Middleware
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Case Study: Gaming Platform
Public Beta Launch“Code Complete”Players are unforgiving
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Case Study: Gaming Platform
1. Catalog Services, Estimate Load
2. Prioritize
3. Isolate Mule and Instrument
4. Generate Load
5. Observe
6. Tune
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Case Study: Gaming Platform
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Case Study: Gaming Platform
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Tuning: Improve Reliability
Reliable Acquisition PatternTransactionsRetryDelegate
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Case Study: Retail
Business Critical Integration“Code Complete”Losing Purchase Orders
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Case Study: Retail
1. Determine failure modes
2. Decide how to respond
3. Induce and observe
4. Apply reliability patterns
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Case Study: Retail
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Questions?Please visit Confluex and
MuleSoft experts in the Expo Hall
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