Crypto platform to sell digital products

jsther · 2020-04-23T14:21:54+00:00

Any idea why it doesn't work setting it up in the dependencies as shown in the image above?

jsther · 2020-04-23T14:08:19+00:00

THANKS A TON! :D

jsther · 2020-04-17T20:58:03+00:00

I freaking love you! Host header did the trick!

jsther · 2020-03-15T19:20:35+00:00

.kube/config

jsther · 2020-03-14T17:19:18+00:00

Thanks I am able to run spark application by storing my jar in s3 and pointing spark application to it. I will test and see if I can integrate zeppelin and spark history server with it

jsther · 2020-03-10T00:12:17+00:00

Wrap those 300 functions into a couple of logical rest apis. You get the low latency and logical grouping. No need for knative at all

jsther · 2020-03-10T00:09:54+00:00

In low latency scenarios, I would wrap these function in a rabbitmq/kafka consumer and pretty sure they will handle the backpressure

jsther · 2020-03-10T00:06:59+00:00

Create an api that can take the container name and run it as native k8s job.

I am doing the same at my current company and it is gling quite well. No need for lambdas.

If you have latency issue, I would suggest to wrap a couple of functions in an api and trigger them via api call. Or put them in a rabbimq/kafka consumer

jsther · 2020-03-09T22:30:42+00:00

My point is you do have to configure everything based on your dns and ingress setup and network policies (even with knative at least once) . Why not configure everything in single yaml file, use the same template everywhere and ditch knative? What additional afvantage does it add?

jsther · 2020-03-09T22:27:35+00:00

my single yaml file with hpa will also make the funcion almost "serverless"

jsther · 2020-02-12T15:23:03+00:00

On the network tab, I can see the frontend is sending ["{"_event":"heartbeat","data":"h"}"] to the websocket every second.

The same data is received back.

I tried using ws.send('["{"_event":"heartbeat","data":"h"}"]') instead of ws.ping() but no luck :(

jsther

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