Emergent
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socketify.py
EmergentI used Emergent to build and prepare a website intended for a live launch. The concept of the platform is promising and the early build experience suggested it could be a very useful tool. However, over several days I encountered repeated technical and deployment problems that ultimately prevented the site from going live.
During development I experienced:
Deployments reporting as successful while requested changes did not appear on the live site
Inconsistent behaviour between preview and production environments
Multiple requests needing to be repeated before partial fixes were applied
Credits being consumed while trying to resolve issues that appeared to be platform-related rather than user error
A major concern was the level of customer support during this period. Responses were often delayed, acknowledgements did not translate into timely resolution, and there were gaps in communication while the work was effectively at a standstill.
Most recently, the build engine itself indicated it was unable to resolve one of the problems, leaving no clear path to complete deployment despite continued attempts.
In preparation for launch, I had already invested in supporting services such as voice generation through 11 Labs and a Canva subscription to create promotional materials linked to the build. These were arranged specifically for rollout, so the inability to achieve a stable deployment resulted in additional wasted expense beyond the platform itself.
As someone trying to move from development to an operational launch, this created a significant setback in both time and cost despite sustained effort to work through the issues.
The overall idea behind the platform is strong, but in my experience the reliability of deployment, consistency of updates reaching production, and speed of support response were not yet dependable enough for a live environment.
โข Slow or inconsistent customer support responses when issues arise. โข Acknowledgement of problems does not always lead to timely resolution. โข Deployment process can report success even when changes have not actually gone live. โข Repeated troubleshooting cycles may consume credits without resolving the underlying issue. โข Communication gaps during fault resolution can leave projects at a standstill. โข Limited transparency on what is happening behind the build/deployment pipeline when errors occur. โข Platform can feel difficult to rely on for time-sensitive or production launches.
Based on our record, socketify.py seems to be more popular. It has been mentiond 2 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
These "benchmarks" are useless, they're not testing anything real world except the performance of uWebsockets. There are copy errors all over the place. And then an advertisement: https://github.com/cirospaciari/socketify.py#briefcase-comme... Is this a professional framework that produces proper, real-world benchmarks and... - Source: Hacker News / over 3 years ago
After starting the project called socketify.py at https://github.com/cirospaciari/socketify.py, I got pretty good results and reviews, but many people asked if socketify.py could be used to create a WSGI and ASGI server. WSGI and ASGI have a lot of overhead, that's is why I choose not to use them in the first place, but adding an ASGI and WSGI server allows a lot of code already written to run faster! Source: over 3 years ago
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