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ContainIQ finds defects faster with traffic-based service mocks


ContainIQ is a Kubernetes-native monitoring and tracing platform that makes it easy for teams to monitor and observe Kubernetes events, logs, and core metrics. With ContainIQ, engineering teams get a clear view of cluster health with pre-built dashboards and easy-to-set monitors.

Using Speedscale

ContainIQ runs all infrastructure on Google Cloud (GKE), and was able to get Speedscale installed within a few minutes. After installing the Speedscale operator, ContainIQ began capturing traffic from the primary gateway where service calls come into a cluster.

“Speedscale lets us ship with confidence because we are able to quickly understand if our new code will run well in production.”

Traffic replay with custom configuration

With the change of a single configuration line, the same traffic can be used for both functional and performance validations. This makes it incredibly easy to build out load scenarios for every kind of traffic being collected. Of course when there are problems, ContainIQ needs to drill down with a ton of detail, and Speedscale collects infrastructure metrics and logs from the application and attaches all data to the test report.

Shipping new code with confidence

Thanks to the integration with Speedscale and the ContainIQ environment, ContainIQ can quickly understand the impact of each change. This allows ContainIQ to ship new functionality faster and prevents bad code being sent to customers. As ContainIQ continues to build out product integrations, the company plans to use service mocks to mock out third-party dependencies for things like Alert Notifications.

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CNCF & Cimpress: Leverage User Traffic to Automate Load Testing this Holiday Season

Integration with CI

The best way to make sure new code is validated is to ensure that it runs as code is checked in. ContainIQ uses GitHub Actions for Continuous Integration, and has integrated Speedscale as a standard checkpoint on every Pull Request. As part of the peer review, ContainIQ can easily see how the new code behaves under common workload requirements, without having to stand up an entire environment and write a bunch of tests.

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