Use case

System Load Analysis Demo

This demo showcases how to analyze and visualize high CPU utilization across components within a large call graph, using PuppyGraph's powerful query capabilities. By querying historical records related to components with a CPU load ratio above 0.9, users can swiftly identify patterns of heavy usage and the associated component and invocation information. Additionally, the application of the PageRank algorithm ranks the importance of each component, providing insights into which components are critical within the network and might need optimization or monitoring to prevent system overloads. This practical approach helps in proactive system maintenance and optimization in complex environments.

Tech stack

PuppyGraph
Apache Iceberg
Docker

Queries in natural language

  • Query historical records and related components with a CPU load ratio greater than 0.9
  • Query historical records of components with CPU usage exceeding 90%, as well as corresponding component and invocation info
  • Rank the importance of each component using the PageRank algorithm

Want to try it yourself?

We've open-sourced the sample dataset, graph schema, and graph queries on GitHub, so you can recreate this demo in your own environment.

Visit GitHub Repository

Downloads

Sample dataset

Download

Schema JSON file

Download

Query groovy file

Download

Get started with PuppyGraph!

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Dev Edition

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Enterprise Edition

Developer

$0
/month
  • Forever free
  • Single node
  • Designed for proving your ideas
  • Available via Docker install

Enterprise

$
Based on the Memory and CPU of the server that runs PuppyGraph.
  • 30 day free trial with full features
  • Everything in Developer + Enterprise features
  • Designed for production
  • Available via AWS AMI & Docker install
* No payment required

Developer Edition

  • Forever free
  • Single noded
  • Designed for proving your ideas
  • Available via Docker install

Enterprise Edition

  • 30-day free trial with full features
  • Everything in developer edition & enterprise features
  • Designed for production
  • Available via AWS AMI & Docker install
* No payment required