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We’re exhibiting at KUBECON, Nov 7-9! Stop by booth #M27, or schedule a personalized 1:1 demo
Turn user behavior into realistic local development environments. Provision API, database, and message queue mocks in minutes. Because staging doesn’t always have what you need.
Your databases and APIs never have the right scenarios.
Speedscale can synthetically build more data for dev and test – or let our advanced rules engine model it after PII redacted user traffic.
“With the exponential increase of microservices and capability focused development, a platform like Speedscale is the only way to certify and confidently deploy these features to our customers at scale and speed.”
“Speedscale is a game changing capability that enables large architectural upgrades with quality. Traffic replay is high coverage and fast.”
“Just on the first run of a regression traffic replay we found a defect in how our APIs were returning IDs. That demonstrated how quick to value the use of Speedscale could be.”
Whether it’s our Kubernetes operator or Postman import — spinning up dev environments with realistic scenarios is quick and automated, in any cloud or even your laptop.
Whether you’re looking to understand behavior under 2x or 10x production load, Speedscale can stress your systems based on real traffic patterns, every commit.
Multiply or loop sanitized user traffic and find your throughput, latency, and breaking point.
Jeff Kwan
Principal Software Engineer
“Speedscale gave us clear insight on the upper load limit of our software. Whereas with K6, it was more binary, like a PASS/FAIL grade. Speedscale took it one step further to help us understand, based on transactions per second, exactly where our breakpoints were. We felt more confident in where our service could be.”
Observe user behavior and choose which backends and scenarios to replicate. Then debug and troubleshoot your next build. Fix, and repeat.
Speedscale observes and redacts PII from your API calls via sidecar, Postman collection or logs
Speedscale then detects auth tokens, dates, and data patterns that need to be replaced to simulate production
Run your code changes against realistic production environments and data so you can build better, faster.
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