PostWire — Autonomous Streaming Incident Commander

🎬 INSPIRATION

Movie releases are no longer just entertainment events — they can create massive, unpredictable traffic spikes for streaming platforms.

A highly anticipated movie can suddenly bring millions of viewers online, causing increased buffering, playback failures, regional degradation, and infrastructure pressure. During such incidents, SRE teams often have to jump between multiple dashboards, correlate different signals, and manually determine what is actually going wrong.

We wanted to build something that could act like an AI incident commander for a streaming platform — one that understands the context of a movie release, investigates viewer experience, analyzes infrastructure telemetry, and recommends what should be done next.

That idea became PostWire.

💡 WHAT POSTWIRE DOES

PostWire is an autonomous AI-powered streaming release incident commander.

It correlates three major sources of information:

🎬 Movie release context 📺 Viewer Quality of Experience (QoE) 📊 Grafana infrastructure telemetry

Instead of simply displaying metrics, PostWire uses AI to reason over the available evidence and investigate an incident.

The workflow is:

Movie Release ↓ Viewer QoE + Regional Signals ↓ Grafana Telemetry through MCP ↓ AI Investigation ↓ Incident Classification ↓ Root Cause Analysis ↓ Recommended Remediation ↓ Action Simulation

🤖 AUTONOMOUS AI INVESTIGATION

The core of PostWire is an AI incident commander built using Google Gemini and Google ADK.

The agent can determine which information is relevant to an investigation, query available MCP tools, analyze telemetry, correlate signals, and produce an investigation report.

For example, if a major movie release causes a sudden increase in traffic and buffering in one region, PostWire can correlate the regional QoE degradation with infrastructure telemetry instead of treating each signal independently.

The result is an evidence-driven incident assessment rather than a simple alert.

📊 REGIONAL QoE INTELLIGENCE

Streaming problems are not always global.

A service may be healthy in most regions while viewers in one geographic area experience severe degradation.

PostWire provides regional breakdowns to help identify:

• Regional degradation • Device-specific problems • Traffic spikes • Playback failures • Buffering increases • Infrastructure pressure

This helps narrow down the scope of an incident quickly.

📡 GRAFANA + MCP

One of the key technical challenges was making the AI useful with operational telemetry.

We integrated Grafana telemetry through MCP, allowing the incident commander to access relevant monitoring information as part of its investigation.

This creates a bridge between observability infrastructure and AI reasoning:

Grafana Telemetry ↓ MCP ↓ AI Incident Commander ↓ Evidence-based Investigation

🧠 WHY AGENTIC AI?

A traditional monitoring system might tell an engineer:

"Buffering increased by 40%."

PostWire aims to go further.

The agent can ask:

• Where is the degradation happening? • Is it correlated with the movie release? • Which regions are affected? • Are specific devices affected? • What telemetry supports the hypothesis? • What is the most likely cause? • What action should be considered?

This makes PostWire an agentic investigation system rather than just another monitoring dashboard.

🛠️ HOW WE BUILT IT

Frontend: React, TypeScript, Vite, Tailwind CSS

Backend: Python, FastAPI, Pydantic, Uvicorn

AI: Google Gemini, Google ADK

Observability: Grafana Cloud, Grafana MCP

Deployment: Render

The frontend and backend are deployed separately on Render.

⚙️ KEY FEATURES

Autonomous Investigation

PostWire investigates predefined streaming incident scenarios using an AI reasoning workflow.

Regional Breakdown

The system analyzes viewer QoE across regions to identify geographic hotspots.

Telemetry Correlation

Grafana telemetry can be queried through MCP and incorporated into the investigation.

Incident Classification

The AI produces an incident assessment based on the evidence it discovers.

Action Simulation

Potential remediation actions can be simulated before being considered for execution.

🚧 CHALLENGES WE FACED

One of the biggest challenges was connecting AI reasoning with operational telemetry.

It is easy to build an AI chatbot that generates explanations, but we wanted PostWire's investigation to be grounded in actual telemetry and structured evidence.

We therefore had to design:

• MCP-based telemetry access • Structured API endpoints • Scenario-based investigations • Regional QoE models • AI investigation workflows • Action simulation • A frontend capable of presenting the investigation clearly

Another challenge was making the system useful without overwhelming the user with raw telemetry.

The goal was to transform complex operational signals into an understandable incident narrative.

📚 WHAT WE LEARNED

Building PostWire taught us how different engineering disciplines can work together in an agentic system.

We learned about:

• Building production-style FastAPI services • React and TypeScript frontend development • Google Gemini and Google ADK • MCP-based tool integration • Observability with Grafana • AI-assisted incident investigation • Designing APIs for agentic workflows • Deploying full-stack applications on Render

Most importantly, we learned that an AI agent becomes significantly more useful when it can observe real signals, reason over evidence, and take structured actions rather than simply generate text.

🚀 FUTURE SCOPE

PostWire can be extended into a fully autonomous SRE platform with:

• Real-time streaming telemetry • Predictive incident detection • Automated remediation • Automated rollback • Slack and Teams incident notifications • Historical incident learning • Multi-agent investigations • Continuous SRE feedback loops

Our long-term vision is for PostWire to evolve from an incident investigation assistant into an autonomous reliability layer for streaming platforms.

🌐 TRY POSTWIRE

Live Demo: https://postwire-frontend.onrender.com/

Backend API: https://postwire-kzex.onrender.com/

Swagger API Documentation: https://postwire-kzex.onrender.com/docs

GitHub: https://github.com/prathampoojari13/PostWire