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Tesmon Platform == Postman + Cypress + RestAssured + Database + More

Hacker News

Tesmon Platform == Postman + Cypress + RestAssured + Database + More

I'm Nagaraj, the founder of Tesmon. Having been both a developer and an engineering leader, from big tech companies to startups, I've personally encountered the challenges of integration testing. It's often so cumbersome that we resort to manual testing. The world of testing is fragmented across multiple frameworks and platforms like Postman, RestAssured, pytest, Selenium, Cypress, Testim, and various custom in-house code using open source frameworks. Building and maintaining this testing infrastructure is not only time-consuming but can be a real pain. Our mission is to revolutionize testing into an assertion-free, near zero effort process by leveraging AI/ML. Current challenges? - Environment Differences: Tests often fail across different environments—local, staging, production—due to setup discrepancies and versioning issues between environments. - Complex Negative Testing: Difficult to manage sequences like receiving an HTTP 200 followed by a 407 error for the same resource. - Frequent Updates: Tests require extensive updates with each application change, including writing assertions for all critical fields in large response bodies. - Unreliable Self-Healing: Self-healing tests frequently fail to correct issues automatically, necessitating manual intervention. - Scalability Issues: No-code/low-code UI tests struggle to scale, becoming a significant time drain as the test suite grows. - Trade-offs Between Automation and Deadlines: Testing automation is often deprioritized due to urgent deadlines, leading to increased manual testing and the risk of regressions. - Resource Limitations: Restricted access to essential databases and services due to compliance requirements, including the need to set up VPN access and manage Jenkins hosted in public clouds because of private subnet restrictions. - Isolation Challenges: Testing everything from only the frontend or backend is often impractical, highlighting the need for integrated testing solutions. - Effort in Framework Construction: Building a testing framework requires significant effort, especially when dealing with modularization and managing different testing environments. How does testing code differ from product code? Testing usually involves sending requests and checking responses, a process that doesn't need to run continuously like microservices or batch jobs. This makes it perfect for AI/ML automation, as the predictable nature of testing tasks allows for efficient learning and optimization without the complexity of continuous monitoring. Traditional programming adds unnecessary complexity to testing, which Tesmon simplifies. Unit tests vs integration tests? We cannot ship code without thorough integration testing, whether automated or manual. This step is critical for identifying significant issues that might not be caught by unit testing alone. Unit tests are primarily used for testing common code and libraries, ensuring that each individual component functions correctly in isolation. Tesmon's Approach: We've completely rethought testing with the Tesmon Platform: - Interactive Local Testing: Directly interact with your APIs, databases, caches, Kafka, and more through Tesmon Desktop, which autonomously creates tests. - Single-Click Test Updates: Tesmon adapts to changes in your system and can integrate updates with just a click. - Extended Lifecycle with Tesmon Cloud: From local development through staging to production, Tesmon covers it all. - Unified Frontend and Backend Testing: Execute comprehensive testing across both frontend and backend within a single test. - Zero Assertions: Utilize AI/ML models to ensure testing requires no manual assertions. Get Started Now. Download Tesmon Desktop today on Mac/Windows and transform your testing. https://tesmon.io/desktop

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Indie HackersFits the IH revenue-focused audience · Strong signals: started, vpn, including · Missing: supports, reddit linkedin, podcasting
97%97% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: mac, model, models · Missing: agents, macos, agent
92%92% predicted probability of success on Product Hunt, 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
61%61% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Strong signals: personal · Missing: mobile apps, ios, entrepreneurs
44%44% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform, host, efficient · Missing: plus, intuitive, reviews
39%39% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue
12%12% 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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