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Rocketship – Open-source E2E testing that's self-hostable

Hacker News

Rocketship – Open-source E2E testing that's self-hostable

Hey HN. My name's Matteo and I'm currently a SWE @ Twilio. 1 day at stand-up the question came up if there was an open source solution to something like https://www.runscope.com . I found it super interesting that there was no artillery.io-like YAML/DSL solution out there. So I built one. Why i think this is cool: 1. Companies today run a ton of microservices for event-driven systems. Asserting on the ingress/egress out of a system might not be covered fully by HTTP. I've setup a plugin interface so that I can implement assertions on stuff like file buckets, DBs, queues, etc. in the future. 2. I didn't want to reinvent the wheel. Temporal provides all of the test orchestration, scheduling, persistence, etc. I could ever need. Simply put: A test = A workflow and A step = An activity inside of temporal. 3. In the future your AI agent friend could run these tests against your system to make sure there aren't any regressions. You can try it out the local version here: https://docs.rocketship.sh/quickstart I think there's a ton of potential for this project and I would really appreciate any advice, stars, or better-yet both.

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Product HuntOn track for Day 1 leaderboard · Strong signals: agent, activity, open · Missing: mac, agents, macos
81%81% 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
73%73% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: open source, ide, io · Missing: https docs, excited, just released
64%64% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal
50%50% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: host, interface · Missing: plus, platform, intuitive
32%32% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
20%20% 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.

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