Test on live data
without the risk.
Deploy a shadow flow that taps into your production pipeline. It processes real events with your new logic but doesn't write to your sinks. Compare outputs, validate fixes, then promote to production — zero downtime, zero risk.
It handles failures
so you don't have to.
Built-in circuit breaker, global rate limiting, and dead letter queue. When Steam's API rate-limits you, Tsunagi backs off automatically. When ClickHouse is at 95% disk, it throttles ingestion. Failed events go to the Error Hub — fix, replay, done.
| Feature | What it does |
|---|---|
| | Auto-stop a flow if error rate exceeds threshold, retry after cooldown |
| | Global rate limiting shared across workers — no API bans |
| | Quarantine failed events with full payload and context |
| | Re-process any failed event after fixing the pipeline |
| | Start or stop 50 workers in one click |
Monitor data schema changes
in your pipelines.
The schema_monitor processor detects when fields are added or removed from your data, helping you track format stability and governance.
Hash-Based Detection
Calculates hash of payload keys, compares with stored schema to detect added or removed fields.
Alert vs Strict Mode
Alert mode logs changes and continues processing. Strict mode blocks events when schema changes detected.
Conditional Alerting
Use conditional sinks to send alerts only when schema changes detected. Slack, Discord, or custom webhooks.
Schema Governance
Track data format stability over time. Store schema history in database for governance and compliance.
Monitor, alert, govern
Place the schema_monitor processor after sources or before sinks to track data format changes and maintain governance.
AI directly in your pipeline.
One line of YAML.
Enrich events with AI directly in your pipeline. Sentiment, translation, summarization, classification — one line of YAML.
How it works
Built-in controls
Providers
Anthropic, OpenAI, Ollama (self-hosted)
Template engine
{{.field}} injects event data into prompts
Budget enforcement
Circuit breaker if daily_budget_usd exceeded
Cost tracking
Per-flow, per-event token usage and USD cost
Fallback
Default value if LLM fails
Retry + backoff
Built into the Go processor
Gaming-native connectors.
Not generic social media scrapers.
Steam
Discord
Twitch
YouTube
Google Play
App Store
X
Bluesky
RSS
SQL Source
S3 Source
Kafka
Webhook
More coming
A desktop that understands
your data pipelines.
Multi-instance. Native. Dark mode by default. Built for the team that ships at 2am.
Flows
Tools
| id | content | ai_sentiment | ai_summary | timestamp |
|---|---|---|---|---|
| sr_001 | Best update yet, love the new maps | positive | Player praises new maps | 2m ago |
| sr_002 | Servers are lagging after patch | negative | Reports performance issues | 5m ago |
| sr_003 | How do I unlock ranked mode? | neutral | Asks about ranked unlock | 12m ago |
Multi-instance
Prod, Staging, Dev — one click to switch
Live Dashboard
TPS, active flows, success rates in real-time
Event Genealogy
Trace any event through the entire pipeline
Error Hub
Click, replay, resolve — without leaving the app
Liveboards
Build dashboards with KPI cards, data tables, and ECharts visualizations. Drag, resize, save.
Templates
Start from 20+ pre-built blueprints. Source-only templates for the Data Forge.
Playground
Test your processors against mock JSON. See the output instantly. No deploy needed.
Analytics built into
your pipeline.
No BI tool needed. Query your live data directly where it flows — DuckDB handles the rest.
The old way
Steampipe, Powerpipe, and friends.
Live data
Query events as they flow through the pipeline
DuckDB-native
Embedded analytics engine, no external database
Zero setup
Works out of the box with your existing flows
Write a SQL query,
Tsunagi generates the pipeline.
Run it in sandbox, promote to production in one click.
SQL-to-Pipeline
Write your query, get a complete data pipeline
Sandbox Testing
Test with live data before promoting
One-Click Deploy
Promote to production instantly