I did that, and it's still just some board room speak about cost reduction, novel data enrichment and not what actual it actually does. What do I use this for?
I get that you want to sell this to executives, but the people that point executives to products to buy are the developers like me, and if don't understand what it does, I can't see executives finding your product.
Just give examples of what on-the-ground problems is solves, converts kafka messages to s3 objects or what?
Lack of novel data enrichment is not a problem that I have, but I could do with something that streams k8s pod logs to kafka or s3 or whatever. Does this solve that?
Yes, streaming k8s pod logs to Kafka and/or S3 is a great example of when you could use Vector.
The "collect, transform, and route all your logs, metrics, and traces" bit is our most succinct explanation of what Vector does, but I'll admit it's still not as clear as we'd like. To expand it slightly, Vector is a tool to collect observability data (logs, metrics, etc) from wherever it's generated, optionally process that data in-flight, and then forward it to whatever upstream system you'd like to consume it. It does this by providing a variety of different components that you configure into whatever pipeline you need. In your example, you could use our new k8s source and plug it into our Kafka sink, our S3 sink, or both.
I get that you want to sell this to executives, but the people that point executives to products to buy are the developers like me, and if don't understand what it does, I can't see executives finding your product.
Just give examples of what on-the-ground problems is solves, converts kafka messages to s3 objects or what?
Lack of novel data enrichment is not a problem that I have, but I could do with something that streams k8s pod logs to kafka or s3 or whatever. Does this solve that?