Performance testing that finds breaking points before your users do
QAble runs load, stress, spike, and soak tests to validate how your system behaves under realistic and peak traffic conditions, identifying bottlenecks, capacity limits, and degradation patterns before they become production incidents.
What load and performance testing covers:
Engineering teams that rely on QAble
What load and performance testing covers
Performance testing answers a different question than functional testing: not whether the feature works for one user, but how the system behaves when thousands use it concurrently.
Load testing
Validates system behaviour under expected and peak user loads, confirming response times, throughput, and resource usage remain within acceptable targets as concurrent users scale.
Stress and spike testing
Identifies the system breaking point by pushing beyond normal capacity, and validates recovery from sudden sharp traffic spikes without catastrophic failure or unacceptable degradation.
Soak testing and profiling
Runs the system under sustained load for extended periods to surface memory leaks, connection exhaustion, and gradual degradation that only become visible after hours of operation.
Run performance tests when:
Why performance problems are invisible until they are catastrophic
Functional testing confirms that features work correctly for one user. Performance testing answers a different question: what happens when a thousand users use it at the same time?
Performance signals that commonly escape testing
response times degrading silently as user numbers grow
Silentdatabase connection exhaustion under concurrent load
Capacitymemory leaks that only appear after extended operation
Memorythird-party API timeouts causing cascading system failures
Dependenciesinfrastructure that holds under test conditions but fails at real scale
ScaleThe QAble solution
QAble designs performance test scenarios that reflect your actual traffic patterns, not artificial benchmarks. Every engagement delivers correlated application and infrastructure data with prioritised optimisation recommendations.
Load test coverage
Expected and peak traffic validated across all endpoints.
Bottleneck resolution
Root cause pinpointed, not just symptoms reported.
Real-time monitoring
Grafana dashboards live during every test run.
Realistic load profiles
Modelled from your actual traffic analytics and patterns.
Performance testing coverage areas
Six performance testing disciplines, from load and stress to soak testing and infrastructure profiling, selected and combined depending on your system's risk profile and launch timeline.
Load testing
Validates system behaviour under expected and peak user loads, confirming response times, throughput, and resource usage remain within acceptable limits.
Stress testing
Pushes the system beyond normal capacity to identify the breaking point, and validates that failures are graceful rather than catastrophic.
Spike testing
Simulates sudden, sharp increases in traffic, validating whether the system can absorb traffic spikes without failures or unacceptable degradation.
Soak testing
Runs the system under sustained moderate load for an extended period, surfacing memory leaks, connection leaks, and gradual degradation.
API performance testing
Validates individual endpoint response times and throughput, identifying slow endpoints that become bottlenecks under concurrent load.
Infrastructure and database profiling
Correlates application performance data with infrastructure and database metrics, pinpointing whether bottlenecks are in code, queries, or infrastructure.
Performance testing methodology
A five-stage process that takes a performance engagement from target definition to actionable bottleneck analysis, with documented artefacts at every stage.
Baseline and goal definition
Defining acceptable response time, throughput, and concurrency targets based on business requirements and traffic projections.
Load profile design
Modelling realistic user behaviour, traffic patterns, and data volumes based on production analytics or expected launch traffic.
Test script development
Building k6 or JMeter scripts that accurately simulate the designed load profiles across target endpoints and user flows.
Execution and monitoring
Running load, stress, spike, and soak tests with real-time monitoring of application and infrastructure metrics via Grafana.
Analysis and recommendations
Identifying bottlenecks from correlated application and infrastructure data, then delivering prioritised optimisation recommendations.
Tooling and instrumentation we run performance testing on
Performance testing becomes engineering evidence when the tooling makes load, latency, and infrastructure metrics as visible as a green build already is.
k6
Script-based load and performance testing
Apache JMeter
Load testing for web and APIs
Grafana
Real-time performance dashboards
InfluxDB
Time-series metrics storage
Gatling
High-concurrency load simulation
Prometheus
Infrastructure metrics monitoring
What you receive
Structured performance findings with clear bottleneck analysis and actionable optimisation recommendations, so engineering teams have the data to act, not just a report to file.
Performance baseline
Test execution report
Bottleneck analysis
Optimisation recommendations
Performance bottlenecks a structured programme surfaces
These are the performance failure patterns QAble consistently identifies across engagements, each one quietly converting into a production incident if left untested.
Slow response under load
Response times that are acceptable with single users but degrade to 10x or more under concurrent load, invisible until production traffic arrives.
Database connection exhaustion
Connection pool limits reached under concurrent load, causing request queuing or failures that only appear at scale.
Memory leaks
Gradual memory growth that causes performance degradation or crashes after extended operation, only surfaced by soak testing.
Cascading third-party failures
Slow or failed third-party API calls blocking application threads and degrading overall response time across the system.
Inadequate auto-scaling
Infrastructure that does not scale fast enough to absorb traffic spikes, causing failures during peak periods and launch events.
Missing caching layers
Repeated expensive database queries or computations that could be cached, causing avoidable load that compounds at scale.
Ways to work with QAble
Three engagement shapes covering a performance baseline, a full test project, and continuous performance QA across releases.
1 to 2 weeks
Performance baseline
Establish current response time, throughput, and concurrency benchmarks for your application with bottleneck identification and optimisation recommendations.
Deliverables
Best for
3 to 5 weeks
Full performance test project
Load, stress, spike, and soak testing with real-time monitoring, bottleneck analysis, and optimisation guidance: a complete performance validation engagement.
Deliverables
Best for
Ongoing
Continuous performance QA
Regular performance regression testing integrated into your release cycle to catch degradation early and track capacity trends as the product scales.
Deliverables
Best for
Why choose QAble
QAble brings disciplined performance testing methodology: realistic load profiles, correlated infrastructure data, and actionable recommendations that engineering teams can act on the same day.
QAble performance testing expertise
Frequently asked questions
Common questions from engineering and platform teams evaluating a load and performance testing engagement.
What is the difference between load testing and stress testing?
Load testing validates system behaviour under expected and peak traffic, confirming that the system meets performance targets at normal operating conditions. Stress testing pushes the system beyond capacity to identify the breaking point and validate that failures are handled gracefully rather than catastrophically.
Do you test in production or staging environments?
QAble recommends testing in a production-equivalent staging environment to avoid impacting live users. For organisations that need production performance data, we can design carefully scoped synthetic traffic injection during low-traffic periods, but this requires explicit coordination and approval.
How do you model realistic load profiles?
QAble analyses your application's traffic analytics, user behaviour data, and business projections to design load profiles that reflect actual usage patterns, including peak hours, user journey distribution, and concurrent session volumes. We do not use generic benchmark scenarios.
Can you identify specific slow database queries?
Yes. Performance bottlenecks frequently originate in database queries rather than application code. QAble correlates application response time data with database metrics to identify slow queries, missing indexes, and connection pool issues, providing specific query-level recommendations.
How does performance testing integrate with our CI/CD pipeline?
Performance regression tests can be integrated as pipeline stages, running a scoped load profile on every release candidate to catch degradation before it reaches production. Thresholds are defined upfront and the pipeline fails if response time or error rate targets are breached.
How quickly can a performance testing engagement begin?
Most performance engagements begin within one week of scope agreement. The first few days define targets, model load profiles, and establish the monitoring stack; active test execution begins in the second week. For urgent pre-launch windows, the engagement can be compressed around the highest-risk scenarios first.
Performance testing built around your real traffic patterns
QAble runs load, stress, spike, and soak tests designed around your actual user behaviour, delivering bottleneck analysis and optimisation recommendations that engineering teams can act on immediately.
Performance testing built around your real traffic patterns
QAble runs load, stress, spike, and soak tests designed around your actual user behaviour, delivering bottleneck analysis and optimisation recommendations that engineering teams can act on immediately.
Talk to QA Advisor
Direct access to QAble's performance testing engineers.
Response within 24 hours