Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Akka-stream throughput checking Flow [feature-request] #17614

Closed
l15k4 opened this issue May 29, 2015 · 1 comment
Closed

Akka-stream throughput checking Flow [feature-request] #17614

l15k4 opened this issue May 29, 2015 · 1 comment
Labels
help wanted Issues that the core team will likely not have time to work on t:stream

Comments

@l15k4
Copy link

l15k4 commented May 29, 2015

Hey,

I think a lot of people would appreciate a Flow that would seamlessly help dealing with strange throughput decreases/issues. Either in form of logging & profiling capabilities or throwing exceptions that would reveal the culprit.

Imagine having a stream of 10 components using 5 different remote services and the stream suddenly looses 50% of original throughput, there is almost no way of targeting this problem right now which leads to a whole day of troubleshooting because you don't know whether it is caused by the services, by akka version upgrade or by a new feature you added. It's madness unless you are an akka-stream guru :-)

Based on these 2 discussions :

stream-idling-on-suddenly-slowed-down-services

profiling-options

@ktoso ktoso added t:stream 1 - triaged Tickets that are safe to pick up for contributing in terms of likeliness of being accepted labels May 29, 2015
@drewhk drewhk added the help wanted Issues that the core team will likely not have time to work on label Jul 27, 2015
@drewhk drewhk added this to the http-1.x milestone Jul 27, 2015
@rkuhn rkuhn modified the milestones: streams-1.x, http-1.x Oct 13, 2015
@drewhk drewhk modified the milestones: streams-2.0, streams-backlog Dec 8, 2015
@rkuhn rkuhn removed the 1 - triaged Tickets that are safe to pick up for contributing in terms of likeliness of being accepted label Mar 9, 2016
@rkuhn
Copy link
Contributor

rkuhn commented Mar 23, 2016

Within a stream we can at best create combinators that measure throughput and allow reactions to the measured values, but in a back-pressured system this will not tell you where the problem lies—it could even be downstream. This concern will need to addressed by external holistic monitoring tools.

@rkuhn rkuhn closed this as completed Mar 23, 2016
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
help wanted Issues that the core team will likely not have time to work on t:stream
Projects
None yet
Development

No branches or pull requests

4 participants