tanveergill

6 ms·

1. 1.▲
   Show HN: Traycer – AI-Powered Code Analysis in Real Time for VSCode(marketplace.visualstudio.com)

   10 points by tanveergill 2y ago|0 comments
2. 2.▲
   by tanveergill 3y ago

   I agree that queues can cause problems especially when misconfigured. But some amount of queuing is necessary, to absorb short spikes in demand vs capacity. Also, queues can be helpful to re-order requests based on criticality which won&#x2
3. 3.▲
   by tanveergill 3y ago

   I am in the same school of thought as you, fair queuing is the most optimal solution while capacity is constrained. This is the approach we took in Aperture, an open-source load management system. Read more about our Scheduler which impleme
4. 4.▲
   by tanveergill 3y ago

   Aperture ( https://github.com/fluxninja/aperture ) takes a slightly opinionated take on queue size. Instead of defining queue sizes, you put a timeout on each request which is the amount of time the request is willing to
5. 5.▲
   by tanveergill 3y ago

   I agree that fair queueing is a good solution to this problem! A request scheduler based on weighted fair queuing is also central to Aperture, an open-source load management system my team has been building for the last 2 years. Priorities
6. 6.▲
   by tanveergill 3y ago

   We have been building a platform called Aperture in the open-source trying to solve this very problem. Our approach is to let the developer decide how long they want to wait in the queue using a timeout parameter. If timeout is hit, they ma
7. 7.▲
   Monitoring Microservices in Kubernetes(blog.netsil.com)

   3 points by tanveergill 10y ago|0 comments