Scale Engineering

Growth is the goal, until the product starts to strain under it. Pages slow down. Outages arrive at the worst possible moment. Releases get riskier. The cloud bill climbs faster than revenue. A product that worked perfectly for 500 customers starts to struggle at 5,000.

Scale Engineering is how we get your product ready for that growth, before it breaks. Senior engineers improve performance, reliability, release speed and cloud costs on AWS and Google Cloud, and set up your infrastructure as code with Terraform, so it is documented, repeatable and easy to change.

• Faster, more reliable product, measured against industry benchmarks

• Lower cloud bills, by cutting what you pay for but do not use

• Safer, faster releases, with automated pipelines and quick rollback

Signs you need scale engineering

• The product slows down as customers and data grow, especially at busy times

• Outages or errors are becoming more frequent, and customers notice before you do

• Releases are risky: deploying is manual, slow, or something the team is afraid to do on a Friday

• The cloud or AI bill is growing faster than revenue, and nobody can explain exactly why

• Nobody fully understands the infrastructure. It was set up by hand, by someone who may have left

• A big moment is coming: a launch, a marketing push, a new market or a large customer that will multiply your traffic

• Enterprise customers or investors are asking about uptime, security, backups and disaster recovery

What we do

1. Performance

We find what is slowing the product down, from slow database queries and heavy pages to inefficient code and missing caching, and fix it, testing against the traffic you expect next, not just today's.

2. Reliability

Monitoring and alerts so problems are spotted before customers notice, automatic scaling for traffic spikes, backups that are tested by actually restoring them, and a disaster-recovery plan for when something serious goes wrong.

3. DevOps and release pipelines

Automated testing and deployment (known as CI/CD), separate staging and production environments, and one-click rollback, so releases become routine, fast and safe instead of stressful.

4. Cloud cost control

We review what you pay for on AWS and Google Cloud, and on AI services, and cut what is wasted: oversized servers, idle resources, missing discounts, and AI calls that could use a cheaper model or a cache. Then we set up budgets and alerts so costs stay under control.

5. Infrastructure as code

We describe your infrastructure in Terraform, so every server, database and network setting is written down, version-controlled and repeatable. Any engineer can see exactly how it is set up, and environments can be rebuilt in minutes rather than from memory.

6. Security and data at scale

Access controls, secrets management, network security, and database changes such as indexing, read replicas and partitioning, so the product stays secure and fast as data grows.

Technology we scale with

Every product we work on starts from the same modern, proven core. On top of it, we add the layer each industry needs, from billing and AI models to payment rails, health data standards and government security controls.

Our core stack

Built for your industry

We choose technology on five things: what your product needs, your industry's rules, speed and cost, how easy it is to hire for, and room to grow. Everything runs in your own accounts, so you are never locked in to us.

How we work

Step 1 — Assess

We measure where you are today: speed, error rates, uptime, release process, infrastructure and cloud costs, and what is coming next in traffic and customers.

You get: a scale readiness report, a list of risks and quick wins, and a fixed-price plan.

Step 2 — Quick wins

We fix the biggest problems that can be solved fast, such as monitoring gaps, the slowest queries and the most obvious cloud waste, so you see results in the first weeks.

You get: measurable improvements and, usually, a lower monthly bill.

Step 3 — Build the foundation

We set up infrastructure as code, automated release pipelines, autoscaling, backups and disaster recovery, so the product is ready for the growth ahead.

You get: documented, repeatable infrastructure and a release process the team trusts.

Step 4 — Test under load

We simulate the traffic you expect, such as a launch or a peak season, to find the breaking points before customers do.

You get: a load test report and the fixes it led to.

Step 5 — Run and improve

We keep watching performance, reliability and costs each month, and keep improving them as you grow.

You get: a monthly report on speed, uptime, releases and spend.

How we measure success

Every engagement starts with a baseline and ends with numbers you can compare against it, and against recognised industry benchmarks.

Reliability: what uptime really means

We help you choose the right target for your stage, because each extra "nine" costs more to achieve.

Speed, releases and costs

Sources: Google web.dev, Web Vitals; DORA 2024 performance clusters, via Octopus Deploy; Flexera 2025 State of the Cloud Report. Uptime figures are calculated on a 30-day month. Targets in the last column are Supernova's own.

Ways to work with us

Fixed scope and price for projects. Cloud and tool costs are paid directly by you to AWS, Google Cloud and other providers, so you always see exactly what you spend. The assessment fee is credited against the project if you go ahead within 30 days.

Is this for you?

A good fit if you:

• Have a live product with growing users, and it is starting to slow down or break

• Have a big launch, campaign or new market coming that will multiply your traffic

• Are paying more for cloud or AI than you think you should

• Have infrastructure set up by hand that nobody fully understands

• Need to show enterprise customers or investors a credible answer on uptime, security and disaster recovery

Not the right fit if you:

• Have not launched yet. Start with AI-Driven MVP or Web and Mobile, which include a production-ready setup

• Want a large enterprise-wide replatforming of legacy systems

• Need 24/7 on-call support only, without improving what causes the incidents

Frequently asked questions

When should a startup invest in scaling? When the evidence shows a constraint becoming real: slowing pages, more errors, risky releases or a fast-growing bill, or when a known event will multiply traffic. Scaling too early wastes money; too late, and things break just as growth arrives.

Do you only work with AWS and Google Cloud? Those are our main platforms, and we also work with Vercel, Supabase and other modern hosting services. If you are on another provider, we can review your setup and recommend whether to stay or move.

What is Terraform, and why does it matter? Terraform lets us write down your entire infrastructure as code. Every server, database and setting is documented and version-controlled, so it can be rebuilt, copied or changed safely, and you are never dependent on one person's memory of how it was set up.

Can you reduce our cloud bill? Usually, yes. We look for oversized servers, idle resources, missing discounts and expensive AI calls, and agree a savings target with you during the assessment.

Will this disrupt our product or team? No. We make changes in small, tested steps, using staging environments and rollback plans, and coordinate releases with your team.

Do we own the infrastructure? Yes. Everything runs in your own cloud accounts, and you own all the Terraform code, documentation and dashboards.

Scale what works, without breaking it

Growth should be the best thing that happens to your product, not the thing that breaks it. With the right foundations, more customers mean more revenue, not more outages and a bigger bill.

Getting ready to scale? Let's make sure your product is.