degrade | Keep track of service error rates using redis | Runtime Evironment library

If your main concern is to run the code in the thread other than "main", but you don't necessarily need a coroutine context, then you can create a Handler running on your background thread and then pass it to setCallback() method.

Also, please note that coroutines are very lightweight. You can run thousands or even millions of coroutines concurrently and nothing bad really happens. I'm not sure about creating a coroutine from outside of the coroutine context - it may involve some latency. I suggest testing the performance first, if you did not do it yet.

The issue is resolved.

The application was extremely chatty and even with server_idle_timeout set as low as 5 seconds, the connections were not getting recycled on the Postgres side.

The issue we had was that server_lifetime was accidentally commented when we thought it was active and once we changed that, we could clearly see that Postgres connections were getting recycled every 2 minutes (based on our settings).

The increased memory of each connection over time especially for long-lived connections was only taking into consideration private memory and not shared memory. What we observed was the longer the connection was alive, the more memory it consumed. We tried setting things like DISCARD ALL for reset_query and it had no impact on memory consumption. Based on my research online, we were not the only to ones to face this challenge with pooling connections.

Thanks for the comments and the help. Our solution in the end was to leverage server_lifetime in pgBouncer to control the number of long-lived connections on Postgres.

-Mayan

The accepted answer in this question should work here as well.. I just tried it by stopping a service and then giving that service's name in the script.. it started it. Every driver would have a corresponding service entry and sc commands would work on a driver service as well. Adapting this to inject fault or bypass conditions should be doable.. reproduced from the answer of the highlighted question:

By default Jboss handles appends logs in multiple files (standalone.logs,server.logs) you can deactivate the log handler using the CLI :

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Signed division is accomplished with the IDIV instruction. Per Agner Fog's instruction tables, on the Haswell architecture, the reciprocal throughput of IDIV for 32 bit registers is 8-11, while for 64 bit registers its 24-81. That is, it takes roughly between 2x and 10x longer to do 64 bit integer division when using 64 bit registers than it takes for 32 bit registers. The numbers vary by architecture, and have a wide range even for Haswell specifically, but an 8x loss in performance seems reasonable. It's not the increment (INC has fixed and absurdly fast speed; it can be dispatched four times per clock cycle apparently), it's your test to limit the amount of output you're performing that uses % 100000000 with larger operand sizes.

Perhaps try replacing it with masking to print based on a large power of 2 instead of a power of 10 (AND is ridiculously cheap and not tied to register size), e.g:

The ASP.NET Core authentication and authorization middleware are not in the right order: app.UseAuthentication() MUST be called before app.UseAuthorization().

Your example data is significantly different to the "nba" examples you have used in this and previous questions. This is why you are having so much trouble. Here are three ways to visualize your actual data:

1.) Tidyverse geom_tile() method: