Real-world load conditions under heavy user stress scenarios
Spawn up virtual users from different geographical regions to connect to your mobile API endpoints
Send real HTTP/S and WebSocket requests
Create custom playbooks to test scenarios that run commands of your choice
Identify bottlenecks in your systems
Understand how your application behaves when thousands of users access it simultaneously
Reveal configuration between development and production environments
Measure response times, connection rates, and resource-utilization levels to reveal your server's performance thresholds
Supports a wide range of web, mobile, and legacy applications
HTTP/2, GWT, HTML5, WebSocket, adaptive bitrate streaming, APIs, IoT, and many more
Conduct load test globally through a single access point
Generate load from 150+ locations around the globe and from multiple cloud providers on real devices
Code level Diagnostics
Out-of-the-box integration with leading APM solutions such as New Relic, Dynatrace, AppDynamics, or CA APM
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Flexible pricing model
Choose from an on-demand and pay-as-you-go pricing model
A large multinational consulting firm has developed an enterprise mobile contextual assistant mobile app that services their users worldwide. Using HeadSpin's load tests, they are able to spin up globally distributed virtual users, send WebSocket requests to their backend, and collect KPI metrics on their scenarios.
Figure 1 shows a KPI degradation discovered through HeadSpin's load tests where the firm's server would intermediately stop responding to requests when there were 500 active users. The area between the vertical red dotted lines in Figure 1 indicate the regions of the load tests' session where the firm's API servers stopped servicing WebSocket requests and returned back "Status 500 Internal Server Error." The first region highlights a degradation that created a downtime of 12 minutes and the second region showcases another outage downtime of approximately 1 minute. The insights derived through HeadSpin's load tests helped the firm identify the root cause: a cache buffer overflow that occurred on the backend WebSocket server.
Figure 1