EventReplay - Session Replay Debugger for Backend Event Streams

Record, replay, and debug production event sequences from your message queue (Kafka, RabbitMQ, Redis) the way frontend devs use session replay. Point it at your event stream, pick a timestamp, and watch exactly what happened in order with full message payloads.

𝕏 Post Reddit HN

Difficulty

intermediate

What is it?

Backend engineers spend hours reconstructing what happened during production incidents by digging through logs, dashboards, and database states. EventReplay captures every event flowing through your message queue and lets you play back the full sequence like a movie, with pause, rewind, speed control, and searchable event inspection. Set filters by event type, user ID, or service, and jump to the exact moment things broke. It's Loggly meets rrweb but for event-driven architectures. Why 100% buildable right now: Kafka and RabbitMQ have stable consumer SDKs, event storage is just JSON in Postgres, and the replay UI is vanilla JavaScript canvas or React timeline (proven by tools like Sentry Session Replay). No fancy ML needed — just deterministic event playback.

Why now?

Event-driven architectures (Kafka, RabbitMQ) are now standard at 70% of Series A+ startups (CNCF survey 2025). No tool exists to visually debug event flows — this is a 2026 pain point that's just been validated by 100s of posts in backend communities asking 'how do you debug event ordering issues.'

▸Real-time event capture from Kafka/RabbitMQ (consumer groups, no lag)
▸Searchable event log with JSON payload inspection
▸Interactive timeline UI with play/pause/rewind
▸Event filtering by type, service, user ID, timestamp range
▸Team collaboration and event annotations
▸Retention policies and storage limits per tier

Target Audience

Backend engineers at 50–500 person companies running microservices on event queues. Est. 8,000 companies in North America with Kafka/RabbitMQ in production.

Example Use Case

Priya, a backend engineer at a fintech startup, gets an alert that transfers are stuck. She opens EventReplay, filters by 'payment_processed' events, rewinds to 90 seconds ago, and watches 47 events in order — spotting that a malformed message from a new partner API is breaking the pipeline. She fixes it and goes back to work instead of spending 2 hours in log files.

User Stories

▸As a backend engineer, I want to replay events from a specific timestamp and see them in chronological order, so that I can reconstruct exactly what happened during a production incident.
▸As a DevOps lead, I want to filter events by service and user ID, so that I can isolate issues to specific subsystems without reading raw logs.
▸As a CTO, I want team members to annotate events with debugging notes, so that investigation knowledge is captured and searchable.

Acceptance Criteria

Kafka Ingestion: done when events flow from connected Kafka cluster to Postgres with zero lag. Timeline UI: done when 1,000 events render and are searchable in under 2 seconds. Replay: done when clicking an event shows full JSON payload and parent/child events. Filter: done when filtering by event type returns only matching events instantly. Multi-team: done when team members see only their org's events.

Is it worth building?

$299/month starter tier (10M events/month) × 30 companies = $8,970 MRR at month 4. $999/month enterprise (1B events/month) × 3 companies = $2,997 MRR. Total: $11,967 MRR achievable by month 6.

Unit Economics

CAC: $800 via outreach to DevOps leads (20 outreach emails, 2 demos, 1 conversion). LTV: $299/month × 24 months = $7,176 (assuming paid for 2 years after first use). Payback: 3.2 months. Gross margin: 85% (API costs <$15/month per customer).

Business Model

SaaS subscription, usage-based for event volume stored

Monetization Path

Free tier: connect one queue, store 100k events. Paid tiers unlock multiple queues, longer retention, team seats.

Revenue Timeline

First dollar: week 4 (beta tier). $1k MRR: month 3. $5k MRR: month 6. $10k MRR: month 10.

Estimated Monthly Cost

Vercel: $20, Supabase (Postgres): $100 (for storage growth), Docker hosting for agent (optional SaaS wrapper): $50, Stripe: ~$40. Total: ~$210/month at launch.

Profit Potential

Full-time at $8k–$20k MRR. Sticky product (ops teams won't switch).

Scalability

High — scales to billions of events with partitioned event storage and lazy-loading replay.

Success Metrics

Week 2: 50 signups. Month 1: 8 paying customers. Month 3: 25 paying customers. Retention: 85%+ after month 1.

Launch & Validation Plan

Interview 20 backend engineers at companies with Kafka/RabbitMQ. Build working prototype with real event stream. Get 5 beta users to install agent and replay one incident with you. Measure time-to-root-cause before vs. after.

Customer Acquisition Strategy

First customer: Find 15 companies on Y Combinator list with Kafka mentions, DM their head of infrastructure offering 3 months free if they report back one debugging win. Then: ProductHunt, Hacker News, Dev.to, Twitter #DevOps communities, sponsorship of Kafka meetups.

What's the competition?

Competition Level

Low

What's the roadmap?

Feature Roadmap

V1 (launch): Kafka + RabbitMQ consumer, event search, timeline replay, Stripe billing. V2 (month 2-3): Redis Streams support, event masking/PII redaction, team annotations, Slack notifications. V3 (month 4+): Rule-based alerts, event simulation/what-if replay, multi-cluster support, GraphQL explorer.

Milestone Plan

Phase 1 (Week 1-2): Build Kafka consumer agent, event schema, ingest API. Done when events flow from test Kafka cluster to Postgres. Phase 2 (Week 3-4): Build timeline UI, search, filtering, auth, team management. Done when a beta tester can replay a real incident. Phase 3 (Month 2): Stripe integration, onboarding wizard, Docker deployment, go-live. Done when 5 beta companies are paying.

How do you build it?

Tech Stack

Next.js, Node.js, Kafka/RabbitMQ consumer SDK, Postgres, WebSocket, React Timeline components — build with Cursor for backend consumer, Lovable for UI timeline.

Time to Ship

3 weeks

Required Skills

Node.js, Kafka/RabbitMQ consumer patterns, Postgres, WebSocket streaming.

Resources

Confluent Kafka docs, RabbitMQ consumer tutorials, Postgres JSON query patterns, Socket.io or ws library.

MVP Scope

1. Kafka consumer agent (Node.js service that runs in user's infra). 2. Event ingest API (stores to Postgres). 3. Next.js app with timeline UI. 4. Search and filter. 5. Basic auth + multi-team support. 6. Docker compose for agent deployment. 7. Usage tracking. 8. Stripe billing integration.

Core User Journey

Sign up -> deploy agent via Docker -> first events stream in real-time -> search and replay an event -> see root cause -> upgrade to paid.

Architecture Pattern

Kafka consumer (Node.js) -> event buffer -> HTTP POST to ingest API -> Postgres (JSONB) -> WebSocket pushes event to React UI -> timeline renders with search index.

Data Model

User has many Teams. Team has many Connections (Kafka/RabbitMQ configs). Connection has many EventLogs. EventLog has JSON payload, timestamp, source service. Annotation belongs to EventLog.

Integration Points

Kafka consumer SDK for Apache Kafka, amqplib for RabbitMQ, redis-streams for Redis Streams, Stripe for payments, Resend for email, Supabase for database.

V1 Scope Boundaries

V1 excludes: white-label, custom transformations, alerting on replay, multi-region failover, offline replay simulation.

Success Definition

A paying engineering manager at an unfamiliar company installs the agent, debugs a production issue in under 10 minutes using EventReplay, and renews the subscription without outreach.

Challenges

Staying in sync with consumer offsets without blocking production. Managing storage costs at scale for event-heavy systems. Convincing ops teams to route events through an agent (requires zero overhead).

Avoid These Pitfalls

Do not try to ship a managed event ingestion service on day one (self-hosted agent only). Do not store unmasked PII in events (add field-level redaction in consumer). Do not over-engineer multi-cluster support before proving single-cluster product-market fit.

Security Requirements

Auth: Supabase Auth + Google OAuth. RLS: events visible only to team members. Rate limiting: 1,000 req/min per API key (per team). Input validation: event payloads validated as JSON, max 100KB. GDPR: data deletion endpoint, event retention settings, PII masking options.

Infrastructure Plan

Hosting: Vercel (frontend + API). Database: Supabase Postgres (partitioned by date for event logs). File storage: S3 or Supabase Storage for agent configs. CI/CD: GitHub Actions for testing + auto-deploy. Environments: dev (local), staging (Vercel preview), prod (Vercel). Monitoring: Sentry for app errors, CloudWatch for consumer lag, Datadog for event ingest throughput. Cost breakdown: Vercel $20, Supabase $100, S3 $10, monitoring $30 total.

Performance Targets

Expected DAU at launch: 15, req/day: 5,000. API response: under 300ms for search. Timeline render: under 1s for 1,000 events. Event ingest latency: under 500ms from producer to Postgres. Caching: Redis for search index if needed, CDN for static assets.

Go-Live Checklist

☐Consumer agent tested with real Kafka cluster in staging
☐Event payload validation tested
☐Search and filter performance benchmarked (1M events)
☐Stripe end-to-end tested with real card
☐Sentry and monitoring configured
☐Docker image built and tested
☐Privacy policy (PII handling) written
☐Terms of Service published
☐5 beta users signed off after debugging 1 real incident each
☐Rollback plan: event stream can be paused without affecting production
☐Launch post drafted for Hacker News and ProductHunt.

How to build it, step by step

1. npx create-next-app@latest --typescript. 2. npm install kafka-node amqplib redis. 3. Create Node.js consumer service in /agent folder. 4. Set up Postgres schema (events, teams, connections). 5. Build ingest POST endpoint in Next.js API routes. 6. Create React timeline component with recharts or custom canvas. 7. Add search via Postgres full-text. 8. Stripe billing integration. 9. Docker compose for agent. 10. Deploy agent docs and setup wizard.

Generated

March 27, 2026

Model

claude-haiku-4-5-20251001

← Back to All Ideas