nilabja-bhattacharya / cloudprober

An active monitoring software to detect failures before your customers do.

NOTE: Cloudprober's active development moved from google/cloudprober to cloudprober/cloudprober in Nov, 2021. We lost a bunch of Github stars (1400) in the process. See the about page to learn more about the history of Cloudprober.

Cloudprober is a monitoring software that makes it super-easy to monitor availability and performance of various components of your system. Cloudprober employs the "active" monitoring model. It runs probes against (or on) your components to verify that they are working as expected. For example, it can run a probe to verify that your frontends can reach your backends. Similarly it can run a probe to verify that your in-Cloud VMs can actually reach your on-premise systems. This kind of monitoring makes it possible to monitor your systems' interfaces regardless of the implementation and helps you quickly pin down what's broken in your system.

Features

• Out of the box, config based, integration with many popular monitoring systems:

  • Prometheus/Grafana
  • DataDog
  • PostgreSQL
  • AWS CloudWatch
  • StackDriver / Google Cloud Monitoring

• Multiple options for checks:

  • Efficient, highly scalable, built-in probes: HTTP, PING, TCP, DNS, gRPC, UDP.
  • Run custom checks through the "external" probe type.

• Automated targets discovery to make Cloud deployments as painless as possible:

  • Kubernetes resources.
  • GCP instances, forwarding rules, and pub/sub messages.
  • File based targets.

• Deployment friendly:

  • Written entirely in Go, and compiles into a static binary.
  • Deploy as a standalone binary, or through docker containers.
  • Continuous, automated target discovery, to ensure that most infrastructure changes don't require re-deployment.

• Low footprint. Cloudprober takes advantage of the Go's concurrency paradigms, and makes most of the available processing power.

• Configurable metrics:

  • Configurable metrics labels, based on the resource labels.
  • Latency histograms for percentile calculations.

• Extensible architecture. Cloudprober can be easily extended along most of the dimensions. Adding support for other Cloud targets, monitoring systems and even a new probe type, is straight-forward and fairly easy.

Getting Started

Visit Getting Started page to get started with Cloudprober.

Feedback

We'd love to hear your feedback. If you're using Cloudprober, would you please mind sharing how you use it by adding a comment here. It will be a great help in planning Cloudprober's future progression.

Join Cloudprober Slack or Github discussions for questions and discussion about Cloudprober.