Cloud & DevOps
Ship on a Tuesday afternoon without holding your breath
We rebuild the path from commit to production so releases stop being events. Infrastructure as code, pipelines your team can read, monitoring that pages the right person, and a cloud bill you can explain line by line.
A senior engineer replies within 24 hours — not a sales rep.
What usually pushes teams to call us
"We deploy on Friday and nobody sleeps"
Releases are manual, take four hours and need three people awake. So the team batches up two weeks of changes into one deploy, which makes every deploy riskier, which makes everyone batch even harder. The fix is not more process. It is smaller, boring, reversible releases.
"Our cloud bill doubled and nobody knows why"
Nothing is tagged, so finance cannot attribute spend to a team or a product. Meanwhile a staging cluster from a cancelled project is still running, half the instances are oversized because someone guessed once, and data transfer charges nobody predicted are quietly compounding.
"One engineer knows how production actually works"
Infrastructure was built by hand in a console over three years. There is no record of why a security group is the way it is. When that person is on leave, changes stop, and if they resign, you are reverse-engineering your own platform from a running system.
"Users tell us we're down before our alerts do"
You have dashboards, but they show CPU rather than whether checkout works. Alerts fire so often the team mutes the channel. When something does break, an engineer SSHes into a box and greps logs because there is no trace connecting the failed request to the service that dropped it.
How we fix it
We start with the two numbers that predict everything else: how often you can deploy, and how long a change takes to reach production. Then we remove whatever is holding those back — usually manual steps, untested infrastructure and missing feedback, in that order.
Pipelines that make releases unremarkable
Automated build, test and deploy on every merge, with staged rollouts and a rollback that is one command rather than a rehearsed incident. Database migrations get versioned alongside the code so schema changes stop being the scary part of a release.
Infrastructure written down, reviewed and reproducible
Terraform for the cloud footprint, Helm or Kustomize for what runs on it, all in your repository with the same review process as application code. Rebuilding an environment becomes a pipeline run, not a week of archaeology.
Migration in slices, not one weekend
We move workloads incrementally behind a routing layer, starting with something valuable enough to matter and small enough to reverse. Each slice proves the pattern for the next one, and the business keeps trading while the platform underneath it changes.
Observability and spend visibility that answer real questions
Metrics, structured logs and distributed traces wired to alerts based on user-facing symptoms, plus runbooks so a page tells the responder what to do. On the cost side: tagging, rightsizing, commitment planning and a dashboard that shows which team and which feature is spending what.
The stack we build on
Chosen to fit the problem — not because it's what we used last time.
Cloud platforms
- AWS
- Microsoft Azure
- Google Cloud Platform
- DigitalOcean
- Cloudflare
Infrastructure & orchestration
- Terraform
- Kubernetes
- Docker
- Helm
- Ansible
- AWS CloudFormation
CI/CD & automation
- GitHub Actions
- GitLab CI
- Jenkins
- Argo CD
- Azure DevOps Pipelines
- Bash & Python tooling
Observability & security
- Prometheus
- Grafana
- OpenTelemetry
- Datadog
- ELK Stack
- HashiCorp Vault
- Sentry
How we'll work together
Every stage ends with something in your hands — not a status update.
- 01
Platform audit
We read your infrastructure, pipelines, IAM policies and last three months of incidents and cloud invoices. The goal is a shared, unsentimental picture of where time and money are going.
You get: A written audit covering deployment bottlenecks, reliability risks, security gaps and cost drivers, ranked by effort against payoff.
- 02
Target architecture and migration plan
We design the end state and, more importantly, the sequence to reach it — which workload moves first, what runs in parallel, and the rollback position at every step.
You get: An architecture diagram, environment topology and a slice-by-slice migration plan with rollback criteria for each slice.
- 03
Build the platform
Infrastructure as code, pipelines, secrets management, monitoring and alerting, delivered in working increments. Your engineers review the pull requests as we go, so nothing lands as a black box.
You get: Terraform modules, CI/CD pipelines and dashboards in your repositories and your cloud accounts, with environments rebuildable from scratch.
- 04
Cut over and hand the keys across
Traffic shifts gradually, we sit with your team through the first real incidents, and then we work ourselves out of the loop. Ongoing SRE support is available if you want it, but it should be a choice rather than a dependency.
You get: Runbooks, on-call rotation and escalation policy, cost dashboards and a working session with your team on operating the platform.
Where we've applied this
Healthcare
Environments with encryption, audit logging and access controls documented well enough to survive a compliance review, and separate data boundaries between clinical and analytics workloads.
Logistics
Tracking and dispatch systems where traffic spikes with the shipping calendar, so autoscaling and queue-backed processing matter more than raw instance count.
Retail & e-commerce
Peak-season capacity planning, CDN and caching strategy, and the confidence to deploy during a trading week instead of freezing the codebase from November.
Finance
Segregated environments, least-privilege IAM, immutable audit trails, and change approval that lives inside the pipeline rather than in a separate spreadsheet.
Manufacturing
Hybrid setups where plant-floor systems stay on-premise and reporting, integration and analytics move to cloud, connected over private links.
SaaS platforms
Multi-tenant isolation, per-tenant cost attribution, and release pipelines that support several deploys a day without customer-visible downtime.
Clients we've built for
Real products, in production, with real users on them.
Questions buyers ask us
Usually yes, and it is often the better first move. Pipelines, test automation, infrastructure as code and monitoring can be introduced on whatever you run today, including on-premise. That work also de-risks a migration later, because you end up with your environment described in code before you try to reproduce it somewhere else.
We change one thing at a time behind a reversible boundary. New infrastructure runs in parallel with the old, traffic shifts in percentages, and every step has a documented rollback we have actually tested. If a slice misbehaves, we go back and diagnose it with the old path still serving users.
Four things: how many environments and services you run, how much of the current setup is undocumented manual work, whether workloads need re-architecting to move or just re-hosting, and your compliance regime. A single-application pipeline and monitoring build is a short engagement. Re-platforming a legacy estate across several teams is a programme, and we would rather scope it properly in a paid discovery than guess on a first call.
No. We build on mainstream, open tooling — Terraform, Kubernetes, GitHub Actions, Prometheus and the like — and everything lives in your accounts and your repositories from the first commit. There is no Binary Brill agent, dashboard or licence in the path. You can end the engagement and keep operating without us.
That is the common arrangement. We pair with your engineers, raise pull requests they review, and write things down as we go rather than after. Where a team is stretched thin, we take ownership of a workstream — say, the CI/CD rebuild — while they keep the lights on, and hand it back documented.
We will not put a percentage on it before looking at your bill, because the honest answer depends on how much waste is there. What we can commit to is method: tagging and attribution first so you can see spend by team and service, then rightsizing, storage tiering, idle resource cleanup and commitment purchasing, with each change measured against the invoice that follows it.
Tell us what your last deploy felt like
Send us a paragraph on how you release today and what it costs you to run. A senior engineer replies within one business day with a straight read on where the bottleneck is and what it would take to clear it.