Slow, fragile or expensive. Usually measurable.
Performance, cost and reliability work on systems that are already in production and have to stay that way. We start by measuring what is actually happening, because the part everyone blames and the part causing the problem are rarely the same part.
What you leave with
- Where the instability or the cost is most likely coming from
- The measurements to take first, before anyone rewrites anything
- Quick fixes worth making this month, and what can wait
With a senior architect, not a salesperson. Sixty minutes, no cost, no obligation.
It is slower than it was, and nobody can say why.
Systems rarely fail outright. They get slower every quarter, the cloud bill grows faster than the business does, and a release everybody used to do on a Tuesday now happens on a Friday night with three people watching. None of that shows up as a fault, which is exactly why it goes unfixed for years.
Slow at the worst time
Fine at ten in the morning, unusable at month end. The pattern is real and measurable, and it is almost never the thing everybody blames.
A bill nobody can explain
Cloud spend that nobody can attribute to a customer, a feature or a team, which means nobody can say which part of it is waste.
Releases people are afraid of
When deploying is frightening, the rate of change drops, and the fear is usually well founded: there is nothing that would catch a mistake before customers do.
Measure first. A rewrite is the last resort, not the first.
Find the real bottleneck
Tracing, profiling and query analysis on the system as it actually runs, under the load that actually hurts. The answer is often one query, one lock or one chatty call, not the architecture.
Cost, attributed
What each part of the estate costs, tagged so it can be read by team or by product. Then the reductions that do not change behaviour: right-sizing, storage tiers, idle resources and the instances nobody remembers switching on.
Reliability you can see
What is actually failing, how often, and who finds out first. Alerting on the things a customer would notice rather than on every graph that moved.
A release that is boring
Automated checks, a repeatable deploy and a way back. The goal is that shipping on a Wednesday afternoon stops being a decision anyone has to make.
Short, measured, and you keep the evidence.
Baseline
We measure before we touch anything: response times where they matter, error rates, spend by component. Without a baseline, nobody can tell afterwards whether the work was worth it.
Shortlist
The three changes with the strongest ratio of effect to risk, written down with what each is expected to buy you. You choose which ones happen.
Fix and prove
The work, then the same measurements again beside the baseline. If a change did not do what we said it would, that is in the report too.
Hand over
The dashboards, the alerts and the runbook stay with your team, along with the list of what we did not do and why it can wait.
What we stabilise and optimise
Systems already in production that are slow, fragile or expensive.
Performance
Profiling, query and cache tuning, and load testing against realistic traffic, so changes are measured rather than guessed.
Reliability
Monitoring, alerting and runbooks; retries and timeouts designed rather than inherited; a plan for the failures that will happen.
Cloud cost
Right-sizing, reserved capacity, storage tiers and architecture changes that reduce the bill without reducing resilience.
Observability
Logs, metrics and traces on Amazon CloudWatch, Azure Monitor, Google Cloud Monitoring, Grafana or Datadog, wired to the questions people actually ask during an incident.
Release safety
CI/CD, automated tests and rollback, so a deployment is no longer the riskiest moment of the week.
Technical debt
A ranked list of the debt that is costing you money, and a plan to pay it down alongside normal work.
Sound familiar?
- The system slows down or falls over at the same times every month
- The cloud bill grows faster than the business
- Incidents are found by customers before monitoring
- Releases are rare because each one is risky
- The team spends more time firefighting than building
A small, senior team that stays accountable.
- Architect-led. Every engagement is led by a senior architect who stays accountable for the decisions, from the first hour to the handover.
- Over twenty years of building and integrating software. Enterprise integration, cloud platforms, product delivery and now AI agents, across sectors where systems cannot fail.
- Independent and vendor-neutral. AWS, Azure and Google Cloud, and whatever platforms you already run. We recommend what fits, including doing less.
- Research, applied. The patterns we use are published openly on The Software Lens and applied by our R&D Wing, so you can read the reasoning before you hire us.
- We run what we recommend. We build our own product, Nexcubator, on the same architecture we design for clients.
- You own everything. Your repository, your cloud account and your documentation from the first week. Based in Ireland, working across the EU and beyond.
Questions we get asked
Will you tell us to rewrite everything?▼
Not unless the numbers say so, and they usually do not. Most of what we find is a small number of specific problems: a missing index, a call made in a loop, an instance sized for a load that never arrived. A rewrite is the most expensive answer to a question that has not been asked properly yet.
How much can we expect to save on cloud spend?▼
We do not put a number on it before looking, because it depends entirely on what is running and why. What we can say up front is that the first step is attribution: until spend can be read by team, product or customer, any saving is a guess and any increase is invisible.
Our system is old and the people who built it have left. Is that a problem?▼
It is the usual situation. We work from the running system rather than from documentation that may no longer be true: traces, logs, queries and the code as it is deployed. What we learn gets written down as we go, which is often worth as much as the fixes.
How long does this take?▼
The measurement phase is typically one to two weeks, and you get a report at the end of it whether or not you continue. The work that follows is scoped from what the measurements found, so you are deciding with numbers in front of you rather than at the start.
One free hour. No pitch, no obligation.
Bring the problem you are stuck on: an integration that keeps breaking, a cloud bill nobody can explain, an AI project that is all demo and no product, or a platform you are about to invest in. You will leave with a straight answer and a written summary, whether or not you ever work with us.
- Architecture and integration review
- AI feasibility: what will actually work, and what will not
- AWS, Azure and Google Cloud cost and design
- Business process audit and ISO readiness
- Technical due diligence before you invest or acquire