Step CI – open-source lightweight alternative to Pingdom and Checkly

Hacker News

In our last post, we showed that there is an easy way to generate automated tests for Rest APIs from your specification. Since the last release, we have added some new features: - Generate tests from your API spec in the CLI - Run tests against gRPC APIs automatically - Get request and response information when your tests fail - Generate fake data and use it in the requests - Bring your own test data (from .csv) - More intuitive CLI interface We built this because we wanted a simple, developer-friendly way to automate API testing without relying on cloud solutions. You can integrate it with Docker, GitHub Actions and Node. Your tests can have multiple steps, with shared context between them. Lastly, you can use it as a library and in combination with other testing tools like Jest, Ava, Mocha (and soon Insomnia). If you want to step out of locked-in cloud solutions, give our tool a try.

Visit product View on Hacker NewsNov 4, 2022

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Product HuntOn track for Day 1 leaderboard · Strong signals: dock, new, context · Missing: mac, agents, macos

94%94% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

67%67% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

48%48% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoMay struggle as an AppSumo deal · Strong signals: intuitive, friendly, interface · Missing: plus, platform, reviews

47%47% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal

35%35% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

13%13% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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