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Pprof Alternatives
Similar projects and alternatives to pprof
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InfluxDB
Build time-series-based applications quickly and at scale.. InfluxDB is the Time Series Platform where developers build real-time applications for analytics, IoT and cloud-native services. Easy to start, it is available in the cloud or on-premises.
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parca
Continuous profiling for analysis of CPU and memory usage, down to the line number and throughout time. Saving infrastructure cost, improving performance, and increasing reliability.
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SonarLint
Clean code begins in your IDE with SonarLint. Up your coding game and discover issues early. SonarLint is a free plugin that helps you find & fix bugs and security issues from the moment you start writing code. Install from your favorite IDE marketplace today.
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minitrace
Simple C/C++ library for producing JSON traces suitable for Chrome's built-in trace viewer (about:tracing).
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tokio
A runtime for writing reliable asynchronous applications with Rust. Provides I/O, networking, scheduling, timers, ...
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fluent-bit
Fast and Lightweight Logs and Metrics processor for Linux, BSD, OSX and Windows
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flamegraph
Easy flamegraphs for Rust projects and everything else, without Perl or pipes <3 (by flamegraph-rs)
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
pprof reviews and mentions
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Why So Slow? Using Profilers to Pinpoint the Reasons of Performance Degradation
Because we couldn't identify the issue using the results we got from Callgrind, we reached for another profiler, gperftools. It's a sampling profiler and therefor it has a smaller impact on the application's performance in exchange for less accurate call statistics. After filtering out the unimportant parts and visualizing the rest with pprof, it was evident that something strange was happening with the send function. It took only 71 milliseconds with the previous implementation and more than 900 milliseconds with the new implementation of our Bolt server. It was very suspicious, but based on Callgrind, its cost was almost the same as before. We were confused as the two results seemed to conflict with each other.
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Improving the performance of your code starting with Go
github.com - google/pprof
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A Generic Approach to Troubleshooting
The application performances in a specific code path (e.g. gdb, pprof, …).
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Does rust have a visual analysis tool for memory and performance like pprof of golang?
pprof is https://github.com/google/pprof, it's a very useful tool in golang , and really really really convenient
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Tokio Console
Go also has pretty good out of the box profiling (pprof[0]) and third-party runtime debugging (delv[1]) that can be used both remotely and local.
These tools also have decent editor integration and can be use hand in hand:
https://blog.jetbrains.com/go/2019/04/03/profiling-go-applic...
https://blog.jetbrains.com/go/2020/03/03/how-to-find-gorouti...
Go has pprof (https://github.com/google/pprof), which I've heard good things about --- and, the pprof data model was one of the influences I looked at when designing the Tokio console's wire format. But, I'm not sure if pprof has any similar UIs to the one we've implemented for the Tokio console; and I haven't actually used it all that much.
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Cats and Clouds – There Are No Pillars in Observability with Yoshi Yamaguchi
And what we do in Google Cloud is that we still use the pprof. But it's a kind of forked version of the pprof because the visualization part is totally different. So we give that tool as the Cloud Profiler. So that is the product name. And then, the difference between the pprof and a Cloud Profiler is that Cloud Profiler provides the agent library for each famous programming language such as Java, Python, Node.js, and Go. And then what you need to do is to just write 5 to 10 lines of code in a new application. That launches the profile agent in your application as a subsidiary thread of the main thread. And then, that thread periodically collects the profile data of the application and then sends that data back to Google Cloud and the Cloud Profiler.
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Is there a way I can visualize all the function calls made while running the project(C++) in a graphical way?
gprftools (https://github.com/gperftools/gperftools) can be easily plugged in using LD_PRELOAD and signal, and has nice go implemented visualization tool https://github.com/google/pprof.
Would pprof's visualizations (especially the tree graph) work for you?
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google/pprof is an open source project licensed under Apache License 2.0 which is an OSI approved license.