ego
pyroscope
ego | pyroscope | |
---|---|---|
1 | 56 | |
56 | 7,382 | |
- | - | |
4.0 | 9.6 | |
4 months ago | about 1 year ago | |
OCaml | Go | |
GNU General Public License v3.0 only | GNU Affero General Public License v3.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
ego
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Ask HN: What are some 'cool' but obscure data structures you know about?
Shameless plug, I also maintain an OCaml implementation of egraphs (named ego) at https://github.com/verse-lab/ego
While the most popular implementation at the moment seems to be egg in Rust, I find that OCaml serves as a much more ergonomic environment for quickly prototyping out uses of egraphs in practice. As a bonus, ego also shares the same logical interface as egg itself, so once you've finalised your designs, you shouldn't have much trouble porting them to egg if you need the performance gains.
pyroscope
- Grafana Phlare, open source database for continuous profiling at scale
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The pros and cons of eBPF profiling in K8s
What do you mean? pyroscope.io was slow for you? or the blog?
- Go garbage collector doesn't release memory
- Pyroscope - Continuous profiling platform
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Ask HN: What are some 'cool' but obscure data structures you know about?
Tries (or prefix trees).
We use them a lot at Pyroscope for compressing strings that have common prefixes. They are also used in databases (e.g indexes in Mongo) or file formats (e.g debug symbols in macOS/iOS Mach-O format are compressed using tries).
We have an article with some animations that go into details about tries in case anyone's interested [0].
[0] https://github.com/pyroscope-io/pyroscope/blob/main/docs/sto...
- How to add dynamic tags/labels to Java profiles (example)
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Question: How do you handle oversized heap analysis?
You could use continuous profiling with Pyroscope which uses async-profiler under the hood, but with the added functionality that you can add relevant tags to your VMs (example).
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JFR (Java Flight Recorder) Parser written in Go
Java Flight Recorder (JFR) is a format for collecting diagnostic and profiling data from Java applications. A while back someone created an issue for Pyroscope , an open source continuous profiler written in Go, to support ingesting profiles in JFR format, but there were no existing parsers that were also written in Go.
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flamegraph.com - a new website for uploading, analyzing, and sharing pprof profiles
This cloud version is actually a slimmed-down version of Pyroscope which is open source and so you can run it locally.
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We created flamegraph.com - A website for uploading, analyzing, and sharing flamegraphs
At Pyroscope (open source continuous profiling) we use flamegraphs extensively to visualize and analyze profiling data. However, one of the worst parts about using flamegraphs for analysis is that they are kind of annoying to share.
What are some alternatives?
PSI - Private Set Intersection Cardinality protocol based on ECDH and Bloom Filters
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.
sdsl-lite - Succinct Data Structure Library 2.0
profefe - Continuous profiling for long-term postmortem analysis
us - An alternative interface to Sia
barrier - Open-source KVM software
RVS_Generic_Swift_Toolbox - A Collection Of Various Swift Tools, Like Extensions and Utilities
Grafana - The open and composable observability and data visualization platform. Visualize metrics, logs, and traces from multiple sources like Prometheus, Loki, Elasticsearch, InfluxDB, Postgres and many more.
Folly - An open-source C++ library developed and used at Facebook.
SheetJS js-xlsx - 📗 SheetJS Spreadsheet Data Toolkit -- New home https://git.sheetjs.com/SheetJS/sheetjs
multiversion-concurrency-control - Implementation of multiversion concurrency control, Raft, Left Right concurrency Hashmaps and a multi consumer multi producer Ringbuffer, concurrent and parallel load-balanced loops, parallel actors implementation in Main.java, Actor2.java and a parallel interpreter
Oat++ - 🌱Light and powerful C++ web framework for highly scalable and resource-efficient web application. It's zero-dependency and easy-portable.