Engineering · Performance

Performance engineering that you can measure

Sub-100ms APIs, 95+ Lighthouse scores, and Core Web Vitals in the green — baked into every layer and proven with numbers, not promises.

What we optimize

Where the time actually goes

We profile before we touch anything. Then we fix the layers that matter — in the order that moves the metric.

01

Front-end load.

Code splitting and lazy loading. Image optimization in WebP and AVIF. Critical CSS, font-loading strategy, JavaScript bundle reduction, and resource hints — preload, prefetch, preconnect.

02

API response time.

A sub-100ms p95 target. Query optimization and indexing, N+1 elimination, multi-layer caching with Redis and the CDN, plus rate limiting and throttling that hold under burst.

03

The database.

Execution-plan analysis, index design and maintenance, connection pooling, read replicas and sharding, query caching, and materialized views where they earn their keep.

04

Caching architecture.

CDN, app, and database layers with deliberate invalidation. Redis, Memcached, Varnish. Edge caching, regional optimization, and cache warming so the first visitor isn't the slow one.

05

Core Web Vitals.

Real User Monitoring and synthetic checks. LCP, CLS, and TBT tracked against budgets, with CI gates and A/B tests so a regression never reaches production unnoticed.

Targets we hit

The numbers we ship against

<100ms
API response (p95)
95+
Lighthouse score
<2.5s
Largest Contentful Paint
<0.1
Cumulative Layout Shift
How we work

Measure the baseline. Find the real bottleneck. Fix the 20% of changes that deliver 80% of the gain. Prove it, then guard it in CI.

Lighthouse, WebPageTest, and distributed tracing tell us where time is actually spent — database, network, or JavaScript. The same discipline runs under the behavioral-health platform we operate: Cadence answers live intake conversations on infrastructure tuned exactly this way.

Performance starts at the metal → Cloud Infrastructure
Profiling
DevTools · WPT
Chrome DevTools, WebPageTest, Lighthouse CI, bundle analysis
Database
EXPLAIN · indexes
execution-plan analysis, pgBadger, Percona, query analyzers
Caching
Redis · CDN · Varnish
multi-layer caching with deliberate invalidation strategy
Load testing
k6 · Artillery
JMeter and Gatling for sustained, real-world traffic shapes
FAQ

Questions engineering leads ask

How fast can you make our API?

We target sub-100ms p95 response times. That comes from query optimization, eliminating N+1 patterns, indexing, connection pooling, and multi-layer caching with Redis and a CDN. We measure the baseline first, then prove the improvement.

Do you fix Core Web Vitals?

Yes. We tune LCP under 2.5s, CLS under 0.1, and TBT under 200ms — through code splitting, image optimization, critical CSS, and font-loading strategy. Real User Monitoring confirms the gains in production, not just in the lab.

How do you prevent performance from regressing later?

Performance budgets enforced in CI/CD block regressions before they ship, and real user monitoring alerts us when metrics degrade in production. Performance engineering is continuous, not a one-time pass.

Get started

Make it fast — and prove it stayed fast.

We'll audit your current performance and hand you a roadmap with measurable targets, not vague promises.

Call 833-MAANTIS