Supporting everything from mobile apps with thousands of concurrent users to global deployments processing millions of requests daily, Anypoint Platform has been put to test. In this session, MuleSoft experts will talk through case studies from our most demanding deployments and provide a best practice approach to designing and delivering application to meet the non-functional requirements (e.g. SLAs) of your application.

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Building Performant, Reliable and
Scalable Integrations
Rupesh Ramachandran
Wai Ip

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Non-Functional Requirements
• A Contract?
• Requirements?
• When are they defined?

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Performance
• Response Time
• Throughput
• Capacity

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• Throughput
• Concurrency
• Message Size
Scalability

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Reliability
• Uptime
• Zero downtime
upgrades
• Disaster Recovery
Data Service
• Zero Message Loss
• Message Recovery

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Trade-offs

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Best Practices

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1) Take it seriously, plan for it.
• First class non-functional requirements
• Define early
• Be Quantitative
• Consider Growth Scenarios

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2) Make it a reality
• Define
• Prioritize
• Model
• Measure

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3) Measure/Tune iteratively
• Measure
• Generate load
• Compare with baseline, SLA
• Identify hot spots
• Tune and profile

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4) Remember the big picture
• Runtime Engine
• JVM
• Operating System
• File System
• Network
• Downstream Systems

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Performance

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• Asynchronous vs Synchronous
• Real-time vs Batch
• On-Premises vs Cloud
• Caching
Design and Deployment Options

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Performance Case Study:
Mule runtime deployed as API Gateway

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Infrastructure 32-core Amazon EC2 RedHat Linux
Throughput 7600tps
Latency Transaction: 5ms
Gateway: 2 ms
API Gateway performance

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Scalability

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Scalability: Best Practices
• Scale Up, Scale Out
• Stateful vs Stateless
• Synchronous
• Asynchronous

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Case Study: Scale-Up

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Reliability

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Reliability: Best Practices
• Degrees of reliability
- At least once
- Once and only once {XA}
• Reliable transactions
- JMS, JDBC, VM-Endpiont
- Multi-resource transactions
- Business vs Infrastructure Exceptions

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Reliable Acquisition Pattern

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Out of the Box Reliability
• Transactional Scope
• Retry Mechanisms
• Until Successful
• First Successful
• Persistent Queues
• HA Clustering
• In-Memory
Replication

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On-Prem versus Cloud
• Anypoint Fabric
• Redundant Platform
• Intelligent Healing
• Zero Downtime Updates
• Data Center Redundancy
On-Prem
• In-memory data grid
• HA Clustering
CloudHub

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Reliability and Scalability Case Study:
Mule runtime deployed as a PaaS

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Customer PaaS performance
6,000+ Mule VMs deployed to test
500+ Mule VMs deployed in production
200+ Service consumers in production
200+ Service providers in production
600+ Service contracts in production
9.5 million messages per day
850,000 messages per hour peak

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Managing and
Monitoring SLA’s

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Out of the box API management

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Want More?

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Mule 3.5 & 3.6: Performance Tuning Guides
Mule 3.6 https://www.mulesoft.com/lp/whitepaper/soa/performance-tuning-guide-mule-36x
Mule 3.5 https://www.mulesoft.com/lp/whitepaper/soa/performance-tuning-guide

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