Open source speed reading software
Branczyk said that the company will eventually offer additional enterprise-grade features, such as automatic recommendations to address infrastructure configuration and code. The commercial hosted Polar Signals product launched in beta back in February, and there it shall remain until next year. “We have prepared lots of pre-baked deployment options and tutorials to make this as easy as possible - users can then choose to run the storage themselves, or purchase the hosted version from us.” The Parca agent is deployed into each Kubernetes cluster node, with the workloads automatically profiled with “super-low overhead,” Branczyk added. “We have taken special care that Parca and Polar Signals integrate particularly well with those environments,” Branczyk told VentureBeat. Polar Signals has been designed from the get-go to play nicely with all the usual observability tools, such as Jaeger and Prometheus, the latter now being the “defacto standard” for monitoring any Kubernetes environment. It packs a bunch of features out of the box, including capabilities for collecting, storing, and making profiles available for query over time - this includes CPU profiling to determine the amount of time a CPU needs to execute a specific piece of code. Parca is the backbone of Polar Signals, and as an open source project, it’s designed to bring the power of continuous profiling to developers from all businesses. Backboneįounded in 2020 by Frederic Branczyk, a former Red Hat senior principal engineer and prominent figure in the Prometheus and Kubernetes open source ecosystems, Polar Signals is designed for large-scale infrastructure, which means it’s gunning for the enterprise segment in a sizable way. And newcomer Polar Signals has officially thrown its hat into the ring today with the launch of a new continuous profiling open source project called Parca, which is available on GitHub now.Īdditionally, Polar Signals today announced it has raised $4 million in seed funding from Alphabet’s venture capital arm GV and Lightspeed.
Open source speed reading software software#
There are several notable players in the space, such as software monitoring giant Datadog, while Andreessen Horowitz-backed Optimyze, which develops the closed source Prodfiler, does something similar.
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Google was one of the early champions of the practice, detailing it in a 2010 white paper titled, Google-Wide Profiling: A Continuous Profiling Infrastructure for Data Centers.
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So continuous profiling is basically optimizing codebases to save on cloud costs.
![open source speed reading software open source speed reading software](https://s3.studylib.net/store/data/006742017_1-b37a2b5e191f09f05fe9967f8e1a07af-768x994.png)
A common use case is in helping companies reduce their cloud bill, given that most of the major cloud platform providers charge on a consumption basis: the more consumption, the higher the cost.
Open source speed reading software code#
Continuous profiling, specifically, is all about monitoring the resources that an application is using, such as CPU or memory, giving engineers deeper insights into what code - down to the line number - is consuming the most resources.