as90

This trend has no stopping it seems. Every dev tool startups are getting funded.

Some of these startups are simple clones of existing proprietary services offered by AWS and other providers. (Like Cognito / Auth0)

Why VCs are betting on this market? What is the opportunity to build a huge business here for a new startup, beating reputed players like AWS, Auth0 etc? What is the conviction of VCs here that these new startups will build a $100M business?

I'm confused.

Also, despite getting a lot of pessimistic comments on the future of such startups here in HN, they seem to raise further rounds (Series A, B) and even building a stable business.

I feel like VCs are better at spotting something huge in this space, than the actual users (I mean developers) who feel pessimistic. Lol.

Which one do you prefer?

If you're gonna use some third party service (either closed hosted, or self hosted) to build application logic workflows, what will be your preference? To write the workflow in their DSL spec and decoupled from your source code?, or will you be more interested if you can run your own native code as workflows?

I have built several apps, but I always use MYSQL search queries to build the search features. I have never felt the need to use Elasticsearch. Can someone enlighten me about the use cases where Elasticsearch becomes irreplaceable? Or is it just nice to have?

I'm trying to identify the bottleneck in my rabbitmq consumer written in Node.JS. The consumer performs 2 simple MYSQL SELECT queries using TypeORM, and then finally perform an API request using Axios.

My Setup -- This consumer, the rabbitmq server, and the MYSQL server, everything is in docker containers inside a t3.large EC2 instance.

The tables are very small, (less than 2000 rows)

The issue -

* This consumer is able to process only around 200 jobs per second. If I push 1000 jobs into the queue, it takes atleast 5 seconds to complete the 1000th job.

* Observations --- * I monitored the typeorm find() function execution time in node. It degrades when the number of jobs in queue increase. For example, if I have only 1 job in queue, it takes around 10ms to complete the query. But when the queue has 1000 jobs, in the 1000th job the execution time of the same function is above 1000ms.

* So to check if the MYSQL server itself is slowing the queries, I fetched the performance metrics of queries from the MYSQL server, but it shows a consistent query speed of around 2-3ms. Max query execution time recorded is around 40ms.

* Consumer docker containers CPU usage is near 100% when it process 1000 jobs.

* If I set the rabbitmq prefetch count to 10 or 20, the consumer behaves normally, and the find() function execution time is also stable. And the overall job completion time also comes down. But if I add more workers with same prefetch count, the same problem again happens. (find() function execution starts to degrade)

Any idea where is the real bottleneck here? Is it the consumer that is not able to perform the job under high load? Why? Is it because of MYSQL connection initiation? (I even increased max_connections in MYSQL server but not much difference). Can anyone help?

I'm a tech + product co-founder who just raised our seed round. Ours is a pure hi-tech product and I envisioned the product and built it. I have no professional experience as a CEO, but I think only I can lead the "product" in the right direction. Should I be the CEO? or Is it really important to hire a "management guru" as the CEO?