Learn to test continuously even when dependent systems are unavailable.
Keep Your Testing Continuous When Systems Aren’t
Modern development moves fast, but testing often doesn’t. Dependencies on third-party services, unstable environments, and limited test data can slow teams down and create costly bottlenecks.
In this on-demand demo, you’ll see how BlazeMeter Service Virtualization helps you keep testing continuous—no matter the constraints.
Eliminate testing delays by simulating dependent systems with realistic virtual services.
•
Accelerate delivery by removing environment constraints and testing earlier in the SDLC.
•
Create scalable, dynamic mocks and integrate seamlessly into your CI/CD pipelines.
•
Enable continuous testing—even when critical services aren’t available.
Customer Reduced Modeled LLM Token Cost by Over $1M With BlazeMeter Service Virtualization
Before BlazeMeter
•
Every test run invoked live OpenAI services across their AI-powered applications.
•
Token usage scaled rapidly across the enterprise AI workloads.
•
Enterprise-scale testing was constrained by token cost and live service availability.
•
High-scale performance and regression cycles incurred recurring, unpredictable charges.
After BlazeMeter
•
BlazeMeter Service Virtualization replaced every live LLM call with a simulated, API-layer response.
•
Teams tested at enterprise volumes across three workloads. Azure OpenAI models including GPT-4 were fully virtualized.
•
Token consumption during testing dropped to near zero. Test cadence increased without cost penalty.
•
Performance and regression testing scaled without dependency on live AI service availability or rate limits.
Whether you're struggling with environment limitations, costly third-party dependencies, or delayed test cycles, this session will show you how to unlock faster feedback loops and more resilient releases.
