frootai/frootai/fai-azure-event-hubs-setup
Claude Code and agent skill by frootai/frootai
- community
Checking that the SKILL.md file is still in the repository.
Configure Azure Event Hubs for real-time data ingestion with stream processing, auto-scaling, Managed Identity auth, and consumer groups — enabling AI workload telemetry at millions of events/second.
Install
npx vskill@latest install frootai/frootai/fai-azure-event-hubs-setupSKILL.md
FAI Azure Event Hubs
Sets up Event Hubs namespaces with topics (hubs), consumer groups for parallel processing, auto-scaling, and Managed Identity access. Ingests traces, metrics, model outputs, and custom events from distributed AI services. Prevents Kafka SPOF and manual queue management.
When to Invoke
| Signal | Example | |
|---|---|---|
| High-volume telemetry source | Millions of requests/sec from AKS cluster | |
| Multiple consumers need same data | Metrics pipeline + machine learning pipeline both need events | |
| Manual queue scaling | Message queue grows faster than infrastructure | |
| No stream processing pipeline | Events arrive but are not aggregated or transformed |
Workflow
Step 1 — Create Event Hubs Namespace
Step 2 — Create Consumer Groups
Step 3 — Send Events via Python
Step 4 — Stream Processing with Azure Stream Analytics
Step 5 — Consumer Group Monitoring
Event Hub Scaling Reference
| Metric | Standard (1 TU) | Standard (10 TU) | Premium | |
|---|---|---|---|---|
| Max ingress MB/s | 1 MB/s | 10 MB/s | 100 MB/s | |
| Max partitions | 32 | 32 | 100 | |
| Consumer groups | 20 | 20 | 1000 | |
| Retention days | 1-7 | 1-7 | 1-90 |
Consumer Group Lag Monitoring
WAF Alignment
| Pillar | Contribution | |
|---|---|---|
| Performance Efficiency | Event Hubs handles 3M+ events/sec; partitioning enables parallel consumer scaling | |
| Reliability | Consumer group offset tracking prevents duplicate/missed message processing | |
| Operational Excellence | Archive to Blob Storage enables forensics; auto-scaling handles burst traffic |
Compatible Solution Plays
- Play 20 — Real-Time Analytics (event ingestion)
- Play 17 — AI Observability (metrics collection)
- Play 05 — IT Ticket Resolution (ticket event stream)
Notes
- Partition count (Step 1,
partitionCount=32) must match expected throughput; higher = more parallel consumers - Consumer group lag indicates processing speed; lag > message retention duration loses events
- Capture feature (Step 1,
captureDescription) auto-archives to Storage; useful for replay/forensics - Starting position
@latestskips backlog; use@earliestfor catch-up processing
Security
- Security scanPassed, 95 of 100Pattern checks on the skill's files.
- Model reviewPassed
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingskills/fai-azure-event-hubs-setup/SKILL.md
Popularity
- Repository stars
- 7
- 7-day trend score
- 10
Stars and forks are for the whole GitHub repository, not this skill alone. Not refreshed yet.
Works with
Any agent vskill installs to: 56 targets in all. These 39 have a page on this site.
- Claude Code
- Cursor
- GitHub Copilot
- Windsurf
- Codex
- Gemini CLI
- Cline
- Amp
- Roo Code
- Goose
- Continue
- Kilo Code
- Junie
- Trae
- OpenHands
- Qwen Code
- AI Agent
- Tabnine Chat
- Sourcegraph Cody
- Amazon Q
- Firebase Genkit
- Sweep
- Devin
- Phind
- Mentat
- Claude Desktop
- Aider
- GPT Pilot
- Plandex
- bolt.new
- v0
- Replit Agent
- Anse
- TypingMind
- BetterChatGPT
- LibreChat
- Warp AI
- Pieces
- Fig AI
Embed badge
[](https://verified-skill.com/skills/frootai/frootai/fai-azure-event-hubs-setup)