Speedscale
Load testing tools
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- Information technology and software
- Energy and utilities
- Healthcare and life sciences
What is Speedscale
Speedscale is a performance and load testing tool that generates realistic traffic for APIs and microservices by capturing, replaying, and scaling production-like requests. It is used by engineering teams to validate service behavior and performance in CI/CD pipelines and pre-production environments. The product emphasizes traffic replay, service virtualization/mocking, and Kubernetes-native deployment patterns to test distributed systems without hand-authoring large test scripts.
Production-traffic replay approach
Speedscale can capture real API traffic and replay it at higher volumes to create load tests that reflect actual request shapes and sequences. This reduces reliance on manually scripted scenarios when compared with tools that primarily start from synthetic test plans. It is particularly useful for microservices where many endpoints and payload variations exist. The approach can improve coverage of edge cases that appear in real usage.
Microservices and Kubernetes fit
The product is designed for distributed services and commonly deploys alongside workloads in containerized environments. It supports testing patterns such as replaying traffic to a specific service while mocking upstream/downstream dependencies. This helps teams isolate performance characteristics of a single service in a larger system. It aligns with modern platform engineering workflows where tests run close to the cluster.
CI/CD-oriented automation
Speedscale is built to run tests as part of automated pipelines rather than only as a desktop-driven workflow. Captured traffic and test configurations can be versioned and reused across environments. This supports regression performance testing on each release and can shorten feedback loops. It also reduces the operational overhead of repeatedly building new test data sets.
Best for API workloads
Speedscale’s core model centers on API and service-to-service traffic capture and replay. Teams whose primary need is browser-based, end-user performance testing may find the fit less direct than tools focused on full UI journeys. For mixed stacks, organizations may need additional tooling for front-end performance validation. This can increase overall testing complexity.
Traffic capture governance needs
Capturing production-like traffic can introduce data handling requirements, especially when payloads include sensitive information. Teams typically need processes for redaction, sampling, retention, and access control. These governance steps can add setup time compared with purely synthetic test generation. The operational model may require coordination with security and compliance stakeholders.
Learning curve for replay modeling
Replay-based testing requires understanding how to parameterize, filter, and scale captured traffic without creating unrealistic amplification effects. Service virtualization and dependency mocking also add concepts that some teams may not already use. As a result, initial adoption can take longer than straightforward script-and-run approaches. Success often depends on establishing repeatable capture and replay practices.
Plan & Pricing
| Plan | Price | Key features & notes |
|---|---|---|
| Proxymock | $0 | Unlimited local mocking; Basic traffic recording; Community support; Desktop CLI tool; Local dev environment setup. Data stored locally (local-only). |
| Team | Contact Sales (Free trial available) | Everything in Free; Advanced traffic replay (local + cloud); CI/CD pipeline integration; Priority email support; Team collaboration and dashboard. Billing is usage-based (charged on data ingested, GB/month). |
| Enterprise | Custom | Everything in Team; Dedicated support and onboarding; Custom integrations; Advanced security features; SLA guarantees; Cloud dedicated tenant. Custom pricing — contact sales. |
