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Building Performant, Reliable and Scalable Integrations

Rupesh RamachandranWai 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: 5msGateway: 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 production200+ Service consumers in production200+ Service providers in production600+ Service contracts in production9.5 million messages per day850,000 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-36xMule 3.5 https://www.mulesoft.com/lp/whitepaper/soa/performance-tuning-guide

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