How My Day Looks Like as Indie Developer Owning Localz SaaS?
Assuming: FastAPI + React (+ RN) self-hosted on EC2 (later EKS), Workers + Nginx/Traefik + Redis self-hosted, Managed: Postgres, Object Storage, CDN, Kafka, Elasticsearch/OpenSearch, SaaS: Clerk, Stripe, OpenAI, Anthropic, Sentry, SendGrid, Twilio, FCM/APNs. Scale: 500 sellers / 10k buyers / 50k listings.
Your real job description
You are NOT "just coding". You are simultaneously:
- CTO → architecture + reliability
- CEO → product direction + sellers + customers
- CFO → cloud bills + runway
- Dev → features + bug fixes
- DevOps → deployments + infra
- AIOps → model costs + prompt quality
- SecOps → auth, secrets, permissions
Your week must be structured or you drown.
Daily Routine (2–4 hours/day minimum)
Morning (20–30 min)
1. System health check — Open:
- Sentry → errors
- Grafana / managed observability → latency + CPU + memory
- Kafka consumer lag
- Postgres connections
- Stripe dashboard (failed payments)
- Clerk dashboard (signups)
Ask: Did anything break overnight? Any spikes? Any stuck workers?
If yes → fix FIRST. No feature work until system is green.
2. Money glance (5 min)
- Cloud bill
- OpenAI/Anthropic spend
- Stripe revenue
Track every day: Revenue yesterday / Infra cost yesterday / AI cost yesterday
Midday (1–2 hours)
Feature or bug work — Only ONE focus at a time:
- Seller onboarding friction
- Buyer UX
- Payments flow
- Search quality
- AI usefulness
Ship something small DAILY.
Seller support — At 500 sellers, expect 2–5 tickets/day. Answer emails, fix broken profiles, help listings appear, debug payment issues. This is product discovery disguised as support.
Evening (30–60 min)
Infrastructure hygiene — Rotate between:
- Backups check
- Redis memory
- DB slow queries
- Kafka topic growth
- Object storage size
- CDN cache hit rate
Weekly Routine
Monday – Product Direction
Decide: What is this week's ONE improvement? (faster listing creation, better mobile UX, AI auto-description, seller analytics) No multitasking.
Tuesday – Infra
Review: CPU trends, Postgres IOPS, Kafka partitions, Worker throughput. Adjust: Instance sizes, Redis limits, Batch sizes. Prevent fires before they start.
Wednesday – Growth
Work on: Seller acquisition, SEO, Landing page, Email campaigns. No code unless growth is blocked by product.
Thursday – Tech Debt
Clean: messy endpoints, missing indexes, untyped models, bad prompts, brittle workflows. This is why systems survive.
Friday – Finance + Strategy
Calculate:
- MRR
- Burn rate
- Runway
- Cost per seller
- Cost per buyer
Decide: Can I afford new features? Do I need price changes? Can I scale infra?
Monthly Routine
Infrastructure Review — Capacity planning:
- DB growth
- Kafka retention
- Storage growth
- AI token usage
- Forecast next 3 months
Security pass — Rotate: API keys, DB credentials, Clerk secrets. Audit: IAM roles, public endpoints, bucket permissions.
Cost optimization — Downsize: unused disks, over-provisioned VMs, Kafka retention, OpenAI temperature/token limits.
Annual Routine
Architecture evolution — Decide: Move to EKS? Split services? Introduce BFF? Add vector DB?
Business model — Revisit: Seller pricing, Transaction fees, AI usage monetization, Premium tiers.
Legal / Compliance — Update: Privacy policy, Terms, Payment agreements.
Mental model that keeps you sane
Your system has ONLY 5 pillars:
- Runtime — EC2 / EKS
- State — Postgres / Mongo / Object storage / Kafka
- Interfaces — React / RN / FastAPI / Webhooks
- External brains — Clerk / Stripe / OpenAI / Anthropic
- Observability — Metrics / Logs / Errors
Everything fits here.
Reality check
At your scale (500 sellers / 10k buyers), you will spend:
- ~40% ops
- ~30% product
- ~20% support
- ~10% growth
NOT coding all day. If you code all day → startup dies.
Final mentor advice
Your technical foundation is already strong. Your success depends on learning:
- operational discipline
- cost awareness
- product prioritization
- ruthless simplicity
Not more frameworks.