Understanding the Problem
Symptoms of LoadRunner Test Anomalies
The issue manifests as:
- Sudden spikes in response time without a matching spike in server CPU or memory usage
- Frequent connection timeouts or transaction errors under moderate load
- Graphs showing failed transactions even when services are online
- High network wait time (NWTT) in LoadRunner reports, while backend metrics remain stable
Why This Problem Matters in Enterprise Load Testing
In high-stakes environments such as banking, telecom, or SaaS platforms, performance testing serves as the final gate before production deployment. Inaccurate or misleading test results delay releases, misdirect optimization efforts, and may lead to under- or over-provisioning. Moreover, false bottlenecks waste engineering hours in root cause analysis and distract from true performance issues.
Root Causes and Architectural Implications
1. Virtual User (Vuser) Misconfiguration
If Vusers are configured with low pacing or think time, they may bombard the system in unrealistic bursts, simulating load spikes that don’t mirror production behavior. This can cause application queue overflow or rate-limiting—even if CPU and RAM are stable.
2. Lack of Network Virtualization
LoadRunner tests often run in local high-bandwidth environments. Without network virtualization, latency profiles don’t match real-world conditions, leading to abnormal request queuing or race conditions in application code.
3. Improper Correlation and Parameterization
In web protocol scripts, dynamic session IDs, tokens, or cookies must be correlated. Missing correlations result in invalid sessions or failed requests that mimic load-induced failures but are actually script-level issues.
4. Controller and Load Generator Bottlenecks
In distributed test setups, the Load Generator (LG) itself can become a bottleneck due to limited CPU or memory, especially when simulating thousands of users. In such cases, application servers perform well, but results appear degraded.
5. Firewall, DNS, or Proxy Issues
LoadRunner components may use different network paths than end-users. DNS caching issues, deep packet inspection by firewalls, or proxy throttling can introduce artificial delays not seen in backend monitoring tools.
Diagnostics and Reproduction
Analyze LoadRunner Results Breakdown
Use the LoadRunner Analysis tool to break down response times by component:
- Look for high DNS time or connection time
- Check Network Delay Time (NWTT) against server response time
- Compare error logs with application logs
Run Isolated Vuser Script
Run a single Vuser instance in VuGen (Virtual User Generator) with full logging to detect failures:
vuser_init() {
web_set_max_html_param_len("2048");
web_url("home", "URL=http://test-app.com/home", LAST);
return 0;
}
Review the Replay Log and Generation Log for missing correlations or HTTP errors.
Monitor LG System Resources
During a test run, monitor CPU, memory, and network utilization on the Load Generator machines:
top vmstat 1 iftop
Ensure LGs are not becoming the bottleneck themselves.
Enable Network Virtualization
If available, enable network virtualization profiles to simulate real-world conditions such as packet loss, jitter, and latency.
Check Web Application Logs and Server Metrics
Correlate LoadRunner timestamps with logs from application servers, load balancers, and web servers. Look for request queuing, 4xx/5xx response codes, or increased latency under low backend utilization.
Step-by-Step Fixes
1. Tune Vuser Pacing and Think Time
Configure realistic pacing and user behavior to match production:
// Set pacing to 60 seconds between iterations Pacing: Fixed, Every 60 seconds // Insert think times where appropriate lr_think_time(5);
2. Correlate All Dynamic Values
Use VuGen's correlation studio or manual correlation to capture session tokens:
web_reg_save_param_ex("session_id", LAST);
Replace hardcoded values in subsequent requests with the captured parameter.
3. Distribute Load Across Multiple LGs
For high-user tests, use Controller to assign user groups across multiple LGs with staggered ramp-up times.
Example: Ramp 500 users over 10 minutes across 3 LGs.
4. Configure Realistic Network Profiles
Use LoadRunner’s network virtualization features or tools like WANem to simulate latency, jitter, and bandwidth constraints:
Latency: 150ms Bandwidth: 2 Mbps Packet Loss: 1%
5. Avoid Unnecessary Resource Contention
Do not run Controller and LG on the same machine. Avoid using VMs with dynamic resource allocation. Pin CPU/RAM resources for predictable performance.
Architectural Best Practices
1. Model User Behavior Accurately
Collaborate with business analysts to define true user behavior patterns. Avoid unrealistic scripts with 0 think time or unthrottled requests.
2. Tag Transactions and Correlate Logs
Tag each business transaction in the script and correlate with application monitoring logs (e.g., New Relic, Datadog) using unique IDs.
3. Separate Network and Application Bottlenecks
Use built-in breakdowns in LoadRunner Analysis to distinguish between DNS delay, connection time, server response, and rendering time.
4. Use Baseline and Benchmark Runs
Run baseline tests with known-good configurations and compare results to new builds. This helps isolate regressions introduced by code or infra changes.
5. Document and Version Control Scripts
Maintain LoadRunner scripts in Git or similar version control. Include annotations for correlation logic, test data sources, and known behavior quirks.
Conclusion
LoadRunner is a cornerstone of enterprise performance testing, but its value is diminished when false bottlenecks or misleading results derail performance investigations. Many anomalies arise not from the application under test but from misconfigured Vusers, insufficient LG resources, or overlooked script errors. Teams must approach LoadRunner diagnostics holistically—correlating logs, observing system metrics, and validating script behavior under isolated conditions. With structured test modeling, network realism, and script hygiene, LoadRunner can deliver precise and actionable insights into system performance under stress.
FAQs
1. Why does LoadRunner show high response times when server metrics look normal?
This may be due to LG resource limits, network path issues, or script errors causing invalid requests. Always cross-check LoadRunner analysis with application logs and LG monitoring.
2. What causes frequent transaction failures during tests?
Common causes include missing correlations, invalid session tokens, or script logic bugs. Use VuGen with full logging to identify these errors before large test runs.
3. Should I use think time in performance scripts?
Yes. Think time helps simulate realistic user behavior and avoids overloading the system with artificial traffic patterns that do not reflect production usage.
4. Can I use LoadRunner with cloud-based apps?
Yes. Ensure that Load Generators have proper network access to cloud endpoints and configure SSL certificates or headers as needed for secure APIs.
5. How can I simulate network latency in LoadRunner?
Use LoadRunner’s Network Virtualization or third-party tools like WANem to emulate real-world network conditions such as latency, jitter, and packet loss.