Subscription billing API
- Challenge
- Invoice list p95 latency 1.2s at 8,000 customers.
- Simplileap solution
- PostgreSQL index tuning, ORM prefetch, materialized views.
- Outcome
- p95 1.2s → 180ms; RDS CPU peak down 37 points.
// Scale
Backend Performance Tuning
Frontend optimisation is limited by your server response time. We profile and tune backend performance, API latency, TTFB, database query performance, and throughput, ensuring your frontend optimisations are not bottlenecked by slow servers.
// Key benefits
What makes this service valuable
Profiling-driven changes
We profile your application under realistic load before changing a line of code, identifying actual bottlenecks rather than optimising what appears slow intuitively.
Database query optimisation
N+1 queries, missing indexes, lock contention, and connection pool exhaustion are common culprits. We diagnose and resolve the database performance issues causing the largest latency improvements.
Throughput and concurrency
Connection pooling, async processing, queue architecture, and horizontal scaling configurations that maximise throughput under concurrent load.
// Details
Server response times that do not limit your frontend
Backend performance profiling surfaces the 20% of code responsible for 80% of latency. Premature optimisation wastes time; profiling-driven optimisation targets the exact bottlenecks with measurable impact.
We use APM tools (Datadog, New Relic, Pyroscope) and database query analysis (pg_stat_statements, EXPLAIN ANALYZE) to build a complete picture before implementing changes.
// What this includes
- APM-based latency profiling
- Database query analysis (EXPLAIN ANALYZE)
- N+1 query identification and resolution
- Index analysis and implementation
- Connection pool configuration
- Caching strategy implementation
- Load testing and throughput measurement
// Deliverables
What you receive
Every engagement produces clear, documented deliverables. Here is exactly what is included in our backend performance tuning service.
- 01Performance profiling report
- 02Database query analysis and optimisation
- 03Caching implementation
- 04Before/after latency and throughput benchmarks
- 05Performance monitoring configuration
// In practice
How backend performance tuning engagements run
Profiling uses py-spy, async-profiler, or Datadog APM flame graphs to find hot paths — often N+1 ORM queries or missing DB indexes. pg_stat_statements or slow query logs drive index additions; connection pool sizes match actual concurrency, not defaults. p95 API latency and TTFB are baselined before/after each change with load tests at expected RPS.
// Stack & frameworks
Stack we use for this
Measurement
- Lighthouse CI
- CrUX field data
- WebPageTest filmstrip
- RUM dashboards
Tuning
- Redis object cache
- CDN edge rules
- Image pipeline
- Query plan review
Governance
- Performance budgets
- Regression alerts
- Release checklists
- Executive reporting
// Delivery
Simplileap execution framework
01
Architecture mapping
Dependencies, API contracts, compliance constraints, and performance budgets documented before sprint one.
02
Secure sprints
Two-week increments with GitHub access, demo recordings, and QA checkpoints, client visibility at every stage.
03
QA & handover
Automated tests on critical paths, security review, runbooks, and knowledge transfer to your team.
// Proof
Real deployments from Bangalore
// Engagement models
How teams engage us
Currency
| Package | Ideal for | Investment | Includes |
|---|---|---|---|
| Managed services AMC | Post-launch platforms | ₹25K – ₹1.5L / month |
|
| DevOps transformation | Engineering teams | Project + retainer |
|
| SLO-backed operations | Revenue-critical apps | Scoped within AMC range |
|
// Company and service positioning
Company and Service positioning is reviewed for production delivery standards by Harsha Parthasarathy (Co-Founder, Strategy & Operations 24+ years IT veteran, IBM, Global Delivery, Program Management) and Keshav Sharma (Co-Founder, Engineering and Lead Architect, Full-stack engineering, product delivery and technical standards).
CIN
AAU-8582
Startup India
DIPP83124
Founded
November 2020
Office
Residency Rd, Bengaluru, India
// FAQ
Common questions about backend performance tuning
What is a realistic target for API response time?+
P50 under 100ms and P99 under 500ms are reasonable targets for most API operations. Read-heavy endpoints with proper caching can achieve P50 under 20ms. Write-heavy endpoints with database operations typically target P50 under 200ms.
Ready to get started with backend performance tuning?
Share your requirements with our team. We respond within one business day with a clear plan from discovery to delivery.