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Aims to observe the cascading effect of interdependent containers in a Kubernetes. This repo is the Backend containing Rest APIs of this system.

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Garuda

Garuda aims to observe the cascading effect of interdependent containers in a Kubernetes.
This repo is the Backend containing Rest APIs of this system.

Abstract

Big organizations such as Google and Facebook have thousands of microservices, databases, filesystems, and many other interdependent systems running in a synchronized manner. In such a complex system, if one of the systems crashes, it becomes very difficult to identify the other affected systems that might crash as a domino effect. Suppose Service A is dependent on Database D, Service B is also dependent on D. In this scenario, if D crashes, then both services A and B will also crash. If we somehow know that crashing D would result in crashing both A and B, we could take some precautionary measures before taking any action that might crash D. In the real world, there are thousands of interdependent systems and it is almost impossible to spontaneously identify all the affected systems. We propose a solution that would identify the cascading effect of any system going down and alert the user beforehand, which would enable the user to take appropriate actions and minimize the repercussions. In this paper, we present a solution that keeps track of the cascading effect of failing services in the Kubernetes cluster and alerts users beforehand.

System Architecture

System Architecture

Cascading Effect Observation

Network Diagram with no failing service

No Failure

Network Diagram with failing service and their cascading effect

No Failure

Tech Stack

  • FastAPI - Python
  • Postgres
  • D3.js
  • Kubernetes
  • Docker
  • Prometheus

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Aims to observe the cascading effect of interdependent containers in a Kubernetes. This repo is the Backend containing Rest APIs of this system.

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