What is Load Testing and Stress Testing?
Introduction
負載測試 simulates realistic user traffic to validate how systems perform under expected conditions. It answers critical questions like: Can our application handle 10,000 concurrent users during a product launch? By gradually increasing virtual users (e.g., ramping from 100 to 10,000 over 30 minutes), engineers measure response times, error rates, and resource consumption. This reveals bottlenecks before users experience slowdowns—such as a database struggling with high read volumes or APIs timing out under load.
壓力測試, conversely, deliberately pushes systems past their breaking points. Its goal isn’t stability but resilience. Engineers overload infrastructure (e.g., 200% beyond capacity) to force failures like server crashes, memory leaks, or data corruption. The focus shifts to recovery: Can the system self-heal? Does data remain consistent after a crash? For example, an e-commerce platform might simulate payment processing during server failures to ensure orders aren’t lost.
Testing Approach
Load Testing Workflow
- Scenario Design: Replicate real user behavior. For a video streaming service, this might include:
- 60% of users browsing content
- 30% starting streams
- 10% updating payment details
- Tool Configuration: Using Apache JMeter, engineers create “Thread Groups” to define virtual users and “HTTP Request” samplers to simulate actions. Ramp-up periods ensure traffic increases gradually.
- Execution & Monitoring: As load scales, tools track:
- Response Time: Does the checkout page load within 2 seconds at peak?
- Throughput: How many transactions per second can the database handle?
- Error Rates: Are 5xx errors spiking at 5,000 users?
- Optimization: Identify weak spots—like unoptimized SQL queries—and retest.
Stress Testing Workflow
- Failure Injection: Tools like k6 or Gatling bombard systems with unnatural traffic (e.g., 50,000 users in 60 seconds). Chaos engineering tools (Chaos Monkey) may randomly terminate cloud servers.
- Breaking Point Analysis: Engineers monitor:
- Resource Exhaustion: When does CPU hit 100%?
- Cascading Failures: Does a crashed auth service take down the entire app?
- Data Integrity: After a database crash, do user balances remain accurate?
- Recovery Validation: Systems should auto-restart failed components or activate backup servers within minutes.
Common Tools for Load Testing and Stress Testing
When to Use Load Testing and Stress Testing
- Load Testing Is Essential For:
- New feature launches (e.g., “Will our servers handle AI image generation requests?”)
- Infrastructure upgrades (validating if a new database cluster improves throughput)
- Marketing campaigns (preparing for Black Friday traffic spikes)
- Stress Testing Uncovers:
- Hidden memory leaks after 12+ hours of sustained load
- Third-party API failures cascading to core services
- Data corruption during sudden power losses
For more information of our methodologies, please visit https://cassolution.com/what-is-load-testing-and-stress-testing/
