I've Reached MVP on My SignalR Hubs Test Client

Hacker News

Hey HN, I've reached MVP on the test client I'm building for SignalR Hubs. Below are the current features Link : http://www.wcfstorm.com/wcf/learn-more-tresi.aspx 1. Create and run load tests for Hubs * run tests with constant load * run tests with increasing load * run tests with burst load to simulate sudden spikes in the load of a hub 2. Invoke Hub methods with zero or more arguments 3. Invoke Hub methods with complex arguments 4. Request Parameter editor with syntax highlighting. 5. Syntax highlighting for the JSON response 6. Export and import hub requests 7. Support for certificates 8. Support for cookies 9. Support for user credentials 10. View the generated javascript proxy 11. Variable trace levels (None, All, Events, StateChanges, Messages) 12. Configurable connection limit 13. Support for web proxy 14. Monitor and track all hub events 15. Monitor and track all hub state changes I've also created a discount code SHOWHNTRESI which will bring the price of the Personal license to just 5 USD. My only request is that if you do use the discount code please send me some feedback about the application. Bugs, any annoyances, feature requests etc. are all welcome. I can be reached at erik.araojo@wcfstorm.com Purchase Tresi : http://www.wcfstorm.com/wcf/tresiproduct.aspx

Visit product View on Hacker NewsFeb 4, 2015

Share card

Actual performance

2points

Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →

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

88%88% 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: user, code · Missing: mac, agents, macos

68%68% predicted probability of success on Product Hunt, 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

42%42% 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, para · Missing: mobile apps, ios, entrepreneurs

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

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

22%22% 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

15%15% 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.

Correct prediction on native model

Similar products

Post MVP,I've Added more features to my REST test client(WcfStorm.REST)34%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Post MVP,I've Added more features to my REST test client(WcfStorm.REST)

Hacker News1

I've built a REST Test client in my spare time56%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

I've built a REST Test client in my spare time

Hacker News11

E2E Test Framework MVP25%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

E2E Test Framework MVP

Hacker News1

MVP done, now what?81%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

MVP done, now what?

Hacker News5

Zipmark, my first MVP.28%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Zipmark, my first MVP.

Hacker News1

Dear Henry... (we launched our first MVP)27%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Dear Henry... (we launched our first MVP)

Hacker News3

HiringPlus51%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Find your next MVP

Indie Hackerscommitment-full-time

What I've Made in 201564%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

What I've Made in 2015

Hacker News10

We've Prelaunched - eFolio.me38%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

We've Prelaunched - eFolio.me

Hacker News2

I've ported scrypt authenticaton to NodeJS.35%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

I've ported scrypt authenticaton to NodeJS.

Hacker News6

Browse all products Analyze your launch