taylanbakircioglu

taylanbakircioglu / flowfish

Public

Centralized multi-cluster Kubernetes observability platform — real-time dependency mapping, impact analysis, change detection, and security monitoring across all your clusters, powered by eBPF

blast-radius change-detection cloud-native dependency-graph dependency-map
16
5
100% credibility
Found Mar 05, 2026 at 16 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

Flowfish is a user-friendly platform that automatically maps app connections, detects changes, simulates impacts, and monitors security across multiple computing environments from one dashboard.

How It Works

1
🔍 Discover Flowfish

You hear about this friendly tool that helps you see how all your apps connect and stay safe across different places.

2
🚀 Get it running

With easy steps, you set up Flowfish on your computer or server so it's ready to watch your apps.

3
🔗 Link your app worlds

You connect all your app environments to Flowfish, bringing everything into one clear view.

4
👀 Watch connections live

Start a quick check and instantly see a colorful map of how your apps talk to each other.

5
⚠️ Spot changes and risks

Flowfish alerts you to any surprises like new links or odd behavior right away.

6
🧪 Test what-ifs safely

Play with ideas like updating an app to preview impacts without any real changes.

🏆 Full app mastery

Now you confidently manage your apps with clear insights, safety checks, and easy reports.

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Star Growth

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AI-Generated Review

What is flowfish?

Flowfish is a Python-based observability platform that centralizes monitoring across multiple Kubernetes clusters, capturing real-time network flows, dependencies, and security events using eBPF—no agents or sidecars needed. It auto-discovers pod communications, including external SaaS APIs and datacenter systems, and delivers interactive graphs, change detection, and impact simulations from a single dashboard. Developers get unified visibility into multi-cluster traffic patterns and risks without refactoring apps.

Why is it gaining traction?

Unlike service meshes requiring sidecar injection or APM tools with high overhead, Flowfish deploys as a lightweight DaemonSet and starts collecting kernel-level data on demand, with smart filters for public/external traffic and 18 graph layouts. The blast radius API hooks into GitHub Actions or Azure DevOps for pre-deploy checks, while change detection blends Kubernetes API polling with eBPF anomalies. Its analysis wizard estimates data volume upfront, making it practical for quick experiments across environments.

Who should use this?

Platform engineers juggling EKS, GKE, and AKS fleets will appreciate the centralized multi-cluster management and one-click health checks. SREs validating deploys via CI/CD workflows benefit from blast radius scoring and rollback plans. Security teams tracking capabilities usage and OOM kills get posture reports without extra tooling.

Verdict

Try it for multi-cluster dependency analysis if you're tired of fragmented tools—docs and screenshots are polished for a 15-star repo. At 1.0% credibility, it's early-stage with solid architecture but needs more production battle tests; spin up the Docker Compose quickstart to evaluate.

(198 words)

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