What is Tricentis NeoLoad?
It simplifies and scales performance testing for everything, from APIs and microservices to end-to-end application testing. It is designed for the complexities of modern enterprises. It is purpose-built to be flexible and fast, working with complementary testing solutions and toolchains, to enable continuous performance testing.
Tricentis NeoLoad is a tool in the Load and Performance Testing category of a tech stack.
Tricentis NeoLoad Integrations
GitHub, Slack, GitLab, Jenkins, and GitLab CI are some of the popular tools that integrate with Tricentis NeoLoad. Here's a list of all 8 tools that integrate with Tricentis NeoLoad.
Tricentis NeoLoad's Features
- Continuous performance testing
- Supports native testing of packaged applications, all protocols, virtualization, and web, mobile, microservices, and APIs
- Integrates with the entire tech stack from legacy systems to the DevOps toolchain
- Saas-based platform
- Cloud-agnostic and integrated with all cloud development tools
- Optimizes cloud infrastructure dynamically
- Automated approach within any CI pipeline
- Fits into existing developer and QA approaches with a Python CLI and REST API
Tricentis NeoLoad Alternatives & Comparisons
What are some alternatives to Tricentis NeoLoad?
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It is open source software, a 100% pure Java application designed to load test functional behavior and measure performance. It was originally designed for testing Web Applications but has since expanded to other test functions.
Gatling is a highly capable load testing tool. It is designed for ease of use, maintainability and high performance. Out of the box, Gatling comes with excellent support of the HTTP protocol that makes it a tool of choice for load testing any HTTP server. As the core engine is actually protocol agnostic, it is perfectly possible to implement support for other protocols. For example, Gatling currently also ships JMS support.
Locust is an easy-to-use, distributed, user load testing tool. Intended for load testing web sites (or other systems) and figuring out how many concurrent users a system can handle.
AWS Device Farm
Run tests across a large selection of physical devices in parallel from various manufacturers with varying hardware, OS versions and form factors.
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