Performance testing and Capacity planning

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Performance Testing

Performance testing helps you understand how your system behaves under various loads. Here’s how to do it step-by-step:

Step 1: Define Performance Metrics and Objectives

  • Example: You want your website to handle up to 1000 users with an average response time of less than 200 milliseconds.

Step 2: Choose Performance Testing Tools

  • Example Tools: JMeter, Apache Bench (ab), Gatling, Locust.

Step 3: Create Test Plans

  • Example: You want to test how your website performs when 500 users access it simultaneously.

Step 4: Set Up Test Environment

  • Example: Set up a test server that mirrors your production server.

Step 5: Execute Performance Tests

  • Baseline Test: Run a simple test to get initial performance data.
ab -n 100 -c 10

-n 100: Number of requests to perform.

-c 10: Number of multiple requests to perform at a time.

Load Test: Gradually increase the number of users to see how the system handles increased traffic.

ab -n 1000 -c 100

Stress Test: Push the system to its limits to find the breaking point.

ab -n 10000 -c 1000

Soak Test: Run the test for an extended period to check for stability issues.

ab -n 1000 -c 100 -t 3600
  • -t 3600: Run the test for 3600 seconds (1 hour).

Step 6: Analyze Test Results

  • Example: After running the tests, you analyze the results to find out that the response time increased significantly when the number of users exceeded 800.

Step 7: Optimize and Retest

  • Example: You optimize your code and database queries, then retest to see if performance improves.

Capacity Planning

Capacity planning helps you ensure your system can handle future loads. Here’s how to do it step-by-step:

Step 1: Gather Historical Data

  • Example: Collect data on CPU, memory usage, and user traffic for the past 6 months.

Step 2: Forecast Future Demand

  • Example: You notice that user traffic increases by 10% each month. You use this trend to predict future resource needs.

Step 3: Define Capacity Requirements

  • Example: Based on the forecast, you estimate that in 6 months, you will need 50% more CPU and memory to handle the increased load.

Step 4: Plan for Scalability

  • Example: Decide to add more servers (horizontal scaling) rather than upgrading existing ones (vertical scaling).

Step 5: Implement Capacity Planning Tools

  • Example Tools: AWS Trusted Advisor, Azure Advisor, Google Cloud Recommender.

Step 6: Conduct Capacity Tests

  • Example: Use Locust to simulate the predicted future load.
locust --headless -u 1000 -r 100 --run-time 1h
  • -u 1000: Number of users to simulate.
  • -r 100: Spawn rate (users per second).
  • --run-time 1h: Duration of the test.

Step 7: Create Capacity Plans

  • Example: Document that you need to add 5 more servers in the next 3 months and prepare a budget.

Step 8: Review and Update Regularly

  • Example: Review your capacity plan every quarter and adjust based on the latest usage data and forecasts.
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