Polly VS BenchmarkDotNet

In our applications, we should wrap all requests to remote services in code that implements a retry policy that follows one of the strategies I listed earlier. If you are a .NET developer like myself, you may be familiar with the Polly library. Golang has a library called Retry, and there are numerous third-party libraries for Python and Java.

Another question that rises is, would it be better to use some HttpClient package to handle the requests, like Refit in combination with Polly. But then again, it seems Refit also uses the HttpClient factory, which was a bad thing according to the previous?

D'Oh! Sorry, not PolySharp. I meant Polly. Too many similarly-named libraries!

Everywhere I've worked with AGs, we've worked with the application team to add retry logic to help make things a bit more seamless to end users. There are libraries out there that can make this pretty easy - Polly is one that I've used a few times, but there are others.

Fallacy 1: The network is reliable. If system 2 works perfectly well, but is not accessible for service 1 due to network issues, service 2 is still unavailable. This is why timeouts, service breakers and retry policies exist. A great tool for .NET to handle common network issues is Polly, but even when using a tool like this, the network is still not completely reliable.

I see. Then I don't have any better idea right now, but I do want to suggest that if your script is mostly API calls and you want to be able to deal with failures then take a look at the polly library: https://github.com/App-vNext/Polly

Runs in containers nicely, has good integration with Kafka, RabbitMQ, gRPC, etc. for Microservices communication. Implements resiliency patterns you'd want in Microservices via Polly. Has a decent Dependency Injection framework built in by default.

It's in no way hidden. But I use Polly all the time.

Depending if the sender or the reciever is down, you can also try Polly http://www.thepollyproject.org/

Let’s look at the first example you see, when you open up BenchmarkDotnet’s website, or Github page.

Or use BenchmarkDotNet which, among other things to get an accurate benchmark, does JIT warmup outside of measurement.

( https://github.com/dotnet/BenchmarkDotNet ).

You can also do proper statistically correct benchmarking by using - https://github.com/dotnet/BenchmarkDotNet. This will run warmup the jit, gauge the overheads, and run your function many times to give you proper data.

take a look at: https://benchmarkdotnet.org/

Yes, weak references are slower than direct calls. How much slower? Heck if I know offhand. But it's usually pretty easy to set up something with Benchmark .NET and find out if it hurts your use case.

For this purpose we are going to use our beloved BenchmarkDotNet tool.

To quantify and compare the performance of the object mapping strategies discussed earlier, we can employ BenchmarkDotNet.

BenchmarkDotNet is a popular open-source library that, as stated in the repo's README.md, helps us to transform methods into benchmarks, track their performance, and share reproducible measurement experiments. Using BenchmarkDotNet feels similar to writing unit tests. It's very important to note that the library only works with console apps. Finally, we can visualize the results in the terminal where the benchmark ran or in user-friendly formats such as markdown, HTML and CSV. We will explore examples of there formats later in the article.

However, obviously this prevents parallelism within the lock, so this only makes sense if you do some other expensive operation in the parallel loop and the string builder is only a small part of it. Performance wise, it may be better to concatenate the results together after the parallel operation, instead of locking inside the loop. You'll have to benchmark it to know for sure.

We’re of course going to be using BenchmarkDotNet for our benchmarks, and you can find all of the code for these over at GitHub. To start, we need an entry point hook for our single Benchmark class that will be defining the permutations of scenarios that we’d like to run. This will be relatively basic as follows: