Application performance at scale — when the code that worked at 100 users doesn't work at 10,000.
Scaling an application isn't about adding servers. It's about identifying the specific bottlenecks: N+1 queries, missing database indexes, synchronous operations that should be async, and cache strategies that reduce database load.
Application that worked at early user scale is now slow or failing under real load — need performance engineering and scale-ready architecture
The specific bottlenecks that appear at scale:
N+1 query problem: Loading a list of records, then for each record making a separate database query. 100 records = 101 queries. 10,000 records = 10,001 queries. Fix: joins or batch loading with Drizzle's with clause.
Missing indexes: A table with 1,000 rows is fast without indexes. A table with 1,000,000 rows without indexes causes full table scans. Every column used in a WHERE, JOIN, or ORDER BY needs an index. Postgres EXPLAIN ANALYZE reveals sequential scans.
Synchronous operations that should be async: Sending email in the request handler means the user waits for the email provider to respond before seeing success. Move to a background job (BullMQ, Inngest, Trigger.dev).
No caching: Database queries that return the same result for every user should be cached. Next.js unstable_cache, Redis, or Vercel's data cache. Even a 60-second cache TTL dramatically reduces database load.
Connection pool exhaustion: Too many simultaneous database connections from serverless functions. Pgbouncer (via Neon or Supabase) pools connections at the database level.
Performance audit with identified bottlenecks fixed — measurable improvement in response times, database query performance, and application throughput
Performance audit
identify top 5 bottlenecks
Query optimization
indexes, joins, batch loading
Background job
implementation for async operations
Caching layer
for frequently read data
Load testing
validation of improvements
One honest number to start.
Fixed-scope, fixed-price. The number below is the starting point — final scope is built from your brief.
Performance audit with identified bottlenecks fixed — measurable improvement in response times, database query performance, and application throughput
Three steps, every time.
The same repeatable engagement on every project. No surprises, no mystery, no billable ambiguity.
Brief & discovery.
We send you questions, then get on a call. Output: a written scope with every step, feature, and integration listed.
Build & ship.
Fixed schedule, weekly reviews. No scope creep unless you change the scope — and if you do, we reprice it transparently.
Warranty & retainer.
30-day warranty on every launch. Most clients stay on a monthly retainer for ongoing features and maintenance.
Why Fixed-Price Matters Here
Performance work has a defined scope: audit + top 5 fixes. Fixed-price.
Questions, answered.
Application-specific, but: fixing N+1 queries and adding missing indexes typically produces 5-20x improvement in slow endpoint response times. Caching further reduces database load by 60-80% for read-heavy applications.
Tell Ryel about your project.
Describe what you’re building and what outcome you need. You’ll have a written, fixed-price scope within the week.