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API Performance & Backend Optimisation — New Zealand & Australia

A slow API costs you customers. Smahh identifies exactly what is slowing your backend down and fixes it without rewriting everything from scratch.

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A slow API is a silent business killer

A slow API is a silent business killer. When a user clicks a button and waits three seconds for a response, they assume your product is broken. This friction leads directly to abandoned carts, frustrated employees, and lost revenue. In an era where users expect instant feedback, an underperforming backend is no longer acceptable.

Most development teams struggle to identify the root cause of performance issues. The symptom is slow page loads, but the disease could be a poorly indexed database table, an N+1 query problem in the ORM, a memory leak in the application server, or an architectural bottleneck that only appears under heavy load. Guessing and adding more servers is an expensive band-aid, not a cure.

Furthermore, optimizing a live production backend is risky. Changing database schemas or rewriting critical business logic without introducing new bugs requires deep expertise and robust testing strategies. A botched optimization attempt can easily result in extended downtime or, worse, data corruption.

Smahh takes a scientific approach to performance optimization. We don't guess; we profile. We identify the exact bottlenecks across the entire stack, from the database engine to the API gateway, and deliver targeted fixes that dramatically improve speed and reduce infrastructure costs.

What our api optimisation covers

API profiling and audit

We start by deeply analyzing your existing API. Using tools like New Relic, Datadog, or built-in profilers, we identify exactly which endpoints are slow and precisely where they are spending their time. We deliver a detailed audit report that ranks performance issues by impact and outlines clear, actionable remediation steps.

Database query optimisation

The database is the bottleneck in 90% of slow web applications. We dive into SQL execution plans to identify missing indexes, inefficient joins, and the dreaded N+1 query problem common with modern ORMs. We rewrite queries, optimize schema design, and implement proper connection pooling to ensure your database can handle high concurrency without buckling.

Caching strategy implementation

Not every request needs to hit the database. We design and implement robust caching architectures using Redis or Memcached. We handle the complex challenges of cache invalidation, ensuring your users always see fresh data while significantly reducing the load on your primary data store. This alone can often double an application's throughput.

Async processing and background jobs

Web requests should never wait for slow operations like sending emails, processing images, or calling third-party APIs. We move these tasks out of the critical request path and into asynchronous background job queues using tools like Celery, BullMQ, or AWS SQS. This results in instant API responses while heavy lifting happens reliably in the background.

Connection pooling and infrastructure tuning

A misconfigured server can throttle a perfectly good application. We tune application server settings, implement database connection pooling (like PgBouncer for PostgreSQL), and optimize operating system parameters. This ensures your infrastructure is making the most of its available resources before spending more money on larger instances.

Load testing and capacity planning

We simulate extreme production traffic to find out exactly when and how your system will break. We use tools like Locust or k6 to pound your APIs with concurrent requests, identify the breaking points, and provide data-driven capacity plans so you can scale confidently ahead of major events or marketing launches.

Why work with Smahh

We measure, we don't guess

We rely entirely on data. We instrument your code and profile your database queries before making a single change. This means we fix the actual root cause of the performance issue, rather than wasting time on theoretical optimisations that don't move the needle.

We respect production

Optimising live systems is delicate work. We rigorously test all performance fixes in a staging environment that mirrors production, and we always ensure robust rollback plans are in place before deploying changes. We fix performance without causing downtime.

Cost reduction focus

Our optimisations often pay for themselves. By making your code more efficient, you can serve more users with less compute power. We frequently help clients downgrade their cloud infrastructure, turning performance engineering into a cost-saving exercise.

How we work

Step 01

Initial consultation and access

We discuss your symptoms, set up secure access to your staging environment, and establish baselines.

Step 02

Deep profiling and audit

We instrument the application and database, running load tests to identify the specific bottlenecks.

Step 03

Optimization plan presentation

We deliver a fixed-price proposal outlining exactly what needs to be fixed and the expected impact.

Step 04

Iterative implementation

We implement the fixes in small, safe batches, validating performance improvements at each step.

Step 05

Final load test and handover

We prove the new performance metrics under load and provide updated documentation to your team.

Results we've delivered

3-10xfaster API responses after targeted query optimisation
20-40%average cloud cost reduction from rightsized infrastructure
2-6 weekstypical timeline from initial audit to production fix

* Results vary by starting point and engagement scope.

Frequently asked questions

We can often identify the broad category of the problem (e.g., database locking, CPU bottleneck, network latency) using existing monitoring tools like New Relic, Datadog, or AWS CloudWatch. However, to pinpoint the exact line of code or specific SQL query causing the issue, we require secure access to the codebase and a staging environment.

Very rarely. In almost all cases, 80% of the performance issues are caused by 20% of the code—usually a handful of poorly constructed database queries, missing indexes, or a synchronous loop that should be asynchronous. We focus on these high-impact areas first, delivering massive speed improvements without a costly rewrite.

Yes, this is our standard engagement model for performance work. We are highly experienced in parachuting into complex, legacy codebases (especially Python, Node.js, and PHP), understanding the architecture quickly, and identifying the bottlenecks that the original team may have missed.

It's the most common performance killer in modern web apps using ORMs (Object-Relational Mappers). It happens when the code fetches a list of items (1 query), and then loops through that list to fetch a related piece of data for each item (N queries). So fetching 100 users results in 101 database queries instead of a single joined query. We identify and fix these.

We split the work into two phases. Phase 1 is a fixed-price Performance Audit, where we profile the app and identify the issues. Phase 2 is the Implementation, where we provide a fixed-price quote to actually apply the fixes we found in the audit. This ensures you only pay for outcomes, not open-ended hourly billing.

We take extreme care to ensure this doesn't happen. We rely heavily on your existing automated test suite (or we write targeted tests for the critical paths before modifying them). All changes are verified in a staging environment under load before they ever touch production.

Is your application feeling sluggish?

Let our experts find the bottleneck and speed up your API today.

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