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Rookout Agile Flame Graphs GA

March 24, 2021

Rookout's Agile Flame Graphs aims to provide developers with a fully visualized understanding of how their code is impacting other applications and services. It empowers developers to instantly analyze the performance impact of individual lines of code, by bringing distributed tracing data into the debugging workflow.

“Until today, developers were blind to the performance of this code in production environments, due to the significant performance overhead of profiling tools,” said Liran Haimovitch, CTO and Co-Founder of Rookout. “Agile Flame Graphs allows software engineers to select a section of code and instantly visualize the latency between functions and individual lines of code, within and across distributed systems.”

Traditional code profiling tools that collect data from every line of code or function within an application lead to a massive amount of noise and performance overhead that prevents developers from using them in production environments. A study published by the Cambridge Judge Business School found that 620 million developer hours a year are wasted on debugging software failures, at a cost of roughly $61 billion annually. The report also notes software engineers spend on average 13 hours to fix a single software failure. Rookout’s Agile Flame Graphs collect only the most useful data across applications, such as CPU consumption and latency between microservices, then visualizes it in an easily accessible manner.

“Nobody profiles code anymore because traditional tools have too much overhead to use in production and local environments don’t match the reality of scale,” said Patrick Lightbody, Co-founder of Reclaim.ai, Former SVP of Product at New Relic. “Rookout's Agile Flame Graphs give us the ability to instantly collect ad-hoc performance metrics from any line of code which is critical when dealing with live incidents.”

Arnal Dayaratna, Research Director for Software Development at IDC said, "Typically, remote debugging requires sifting through voluminous amounts of log files or attempting to replicate the issue in question in another environment (preproduction, staging, etc.)...Both approaches are also very time-consuming, leading to prolonged mean time to resolution (MTTR) as well as to developers' "wasting" time on nonproductive activities (determining the root cause) rather than fixing the code issue or developing new features."

Jason Bloomberg, President at Intellyx added, "A single line of code may not only affect multiple microservices running across the Kubernetes landscape, but each microservice may depend upon other microservices or other software components – again dynamically. The connection between individual lines of code and the behavior of all software running in production is thus tenuous at best. The only way to keep the entire effort from running off the rails is to rigorously follow cloud-native principles while leveraging tools that support those principles [...] An understandability tool like Rookout brings information about the running software in production to developers, providing visibility into how individual lines of code impact the behavior of running software, without impacting that software."

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