Architectural Patterns That Limit Application Scalability & Performance Optimization

Note - Currently working on this blog

Client & Server Pattern

Master & Worker Pattern

Partition For Parallelism 

Common Approach To Improve Throughput

Performance Optimization Concepts

Latency = time delay between starting an activity and when the results are  available /  detectable

Throughput = ratio of number of tasks completed in a unit of time.

Performance (perceived speed / responsiveness) = number of requests made and acknowledged in a unit of time.

Throughput and Performance are often confused!  (sometimes they are the same)

Example:

Average Throughput = 10 tasks / sec

Average Latency = 1000ms (1sec / 10)

Performance = unknown

NOTE - 

To improve performance = reduce latencies (between request and response)

To improve throughput = increase capacity (or reduce total latency)

Only Execute Mandatory Tasks

Increase CPU speed (scale up)

Optimize Algorithm

Exploit Parallelism (Scale Out)

Optimize Large Latencies

Best of all world - Do them all

Reduce Use Of XML

Use Case - Oracle Coherence In Compute Grid