Services / Data & Cloud
We automate the path from commit to production: build, test, security gates and deploy, with tested rollbacks and monitoring that answers to named owners. Same artifact everywhere, same steps every time, no Friday-night heroics.
Measured pipelines. Tested rollbacks. Infrastructure as code.
The business case
Manual deploys are slow, risky and depend on whoever knows the steps. Automated delivery changes the maths: releases happen more often, each one carries less change, and when something breaks you go back in minutes. The point is not more releases — it is smaller, safer ones.
Deploys are manual or require a specific person, releases are rare and risky, environments have drifted apart, or nobody is sure what is running in production. Access to repositories, cloud accounts and the people who deploy today is essential.
If your pipeline works but the applications themselves are the problem, product or AI engineering fits better. If the issue is the cloud estate rather than the delivery path, start with cloud architecture & migration.
Where this applies
These are example situations, not pre-packaged promises or claims about past results.
Replace manual, error-prone release rituals with automated pipelines that build, test and deploy the same way every time, so releases become routine.
Learn: how often do releases happen, and how many fail or need rollback?
Add rollback paths, health checks and deployment strategies that make a bad release a non-event instead of an outage.
Learn: how long does recovery actually take after a bad deployment?
Make staging and production reproducible from code, so 'works on staging' stops being a mystery and config drift disappears.
Learn: can any engineer recreate an environment from the repository?
Cut build and test times so developers get signal in minutes, keeping momentum instead of context-switching while CI runs.
Learn: how long do developers wait for pipeline feedback?
Move infrastructure from console clicks and tribal knowledge into versioned, reviewed code that anyone on the team can read and apply.
Learn: is every environment change traceable to a commit?
Centralise credentials, rotate them on schedule and scope access per environment, ending shared passwords and long-lived keys.
Learn: can you list every secret and who can use it, today?
How the pipeline works
Every change travels the same road: build, test, security gates, then a deploy strategy with automated health checks. If a check fails after release, the deployment returns to the previous version — a rehearsed path, not an improvisation.
A single artifact promoted through environments, automated health checks with rollback, secrets managed properly and every change traceable to a commit.
Pipeline theatre nobody maintains, tools adopted for fashion rather than fit, and process gates that slow delivery without catching anything real.
Pipelines & release automation
A pipeline is software that ships software: it deserves the same tests, reviews and documentation. We build pipelines that are boring in the best way — predictable, fast and identical across environments.
Compile, lint, unit and integration tests run on every change, with flaky tests quarantined and fixed rather than retried into meaninglessness.
Rolling, blue-green or canary releases chosen per workload, with automated health checks deciding whether to proceed or roll back.
A tested return route to the previous version, so recovery is a command, not an incident bridge.
The same artifact promoted through environments, so what you tested is exactly what you deploy — no rebuilds in between.
Infrastructure as code
Console changes and undocumented environments are where outages and security gaps hide. We define everything in code so the estate is readable, reproducible and reviewable.
Cloud resources defined in Terraform or Pulumi, applied through pipelines with plan reviews rather than changed by hand.
Staging and production generated from the same modules with different inputs, so surprises come from real differences, not drift.
Scheduled checks that flag manual changes, so the code stays the source of truth instead of decaying into fiction.
Reusable, documented infrastructure modules your engineers adopt, so the next project does not start from scratch.
Observability & operations
Shipping is only half the job. We wire up logging, metrics and alerts with owners and runbooks, so the on-call engineer has an answer instead of a mystery.
Logs and traces in a consistent format, correlated across services, queryable when something goes wrong at 3 a.m.
Error rates, latency and saturation tracked against agreed objectives, so 'is it healthy?' has a measurable answer.
Alerts routed to named engineers with runbooks attached, tuned so pages mean something rather than training people to ignore them.
Rehearsed failure scenarios, so the first time the team practices a rollback is not during a real outage.
Security & supply chain
Security that depends on someone remembering is security that fails. We automate the checks so the safe path and the fast path are the same path.
Automated vulnerability scans on dependencies and container images, with fixes tracked rather than accumulating as a backlog.
Credentials stored in a secrets manager, injected at runtime, rotated on schedule and never committed to a repository.
Pipeline and runtime identities scoped to what each job needs, with production access gated and logged.
Every deploy, infrastructure change and access grant recorded with who and why, ready for review when it matters.
Tools & frameworks
We work with your existing platform first and improve incrementally. These are options, not a requirement to use everything on the list.
Pipeline platform matched to where your code already lives and how your team works.
Packaging and runtime for services that need scale or portability.
Reproducible environments with plan reviews and drift detection.
GitOps delivery, progressive rollouts and decoupled releases from deploys.
Metrics, logs and traces with alerts routed to owners.
Credential handling and automated vulnerability scanning.
Static analysis, end-to-end tests and load checks as pipeline gates.
Automation glue written in maintainable, testable code.
Tool selection depends on your repository host, cloud, team skills and existing investments. We prefer fewer, well-understood tools over a broad stack nobody owns.
Delivery approach
You work with engineers inside the delivery process. The pipeline is visible early, and every stage is demonstrated on a real service rather than a slide.
Map the current build, deploy and operations flow, measure what hurts — release frequency, failure rate, recovery time — and prioritise the fixes.
Output: Delivery assessment with measured baselines and a prioritised roadmap.
Agree the branch model, artifact flow, environment topology and deployment strategy before building.
Output: Pipeline design and environment architecture, written down.
Implement the pipeline and infrastructure code for the highest-priority service, delivering a working automated path end to end.
Output: Automated build-to-deploy pipeline for a pilot service.
Extend to remaining services, add security gates, observability and rollback drills, and retire the manual steps.
Output: Pipelines with security gates, monitoring and tested rollbacks.
Transfer ownership with documentation, pairing and on-call runbooks; optionally stay on for ongoing operations support.
Output: Runbooks, ownership model and a team that runs its own delivery.
A decision-maker, repository and cloud access, the people who deploy today, and whoever owns the on-call rota. For regulated workloads, bring compliance stakeholders into scoping early.
The pipeline design, environment topology and rollout order are written down and agreed before building. Delivery metrics — frequency, lead time, failure rate, recovery time — are measured from day one, so improvement is evidence.
Handover & ownership
Everything lives in your repositories from day one. Handover includes the design rationale and the operational practices, so delivery keeps improving after we leave.
Build, test and deploy automation lives in your repositories, maintained and extended by your engineers.
Environments defined in versioned modules with plan reviews, so infrastructure changes are reviewable and reproducible.
Release frequency, lead time, failure rate and recovery time tracked over time, so improvement is evidence rather than opinion.
Dashboards, alerts with named owners, and incident runbooks your team can operate the day we leave.
Delivery does not include unlimited maintenance or a service-level commitment. We can agree ongoing DevOps support, or hand over fully to your own team.
Related engineering services
Delivery work often connects to cloud platforms, data platforms or dedicated engineering capacity.
Questions before starting
You need the parts that remove your actual pain. A small team may need one solid pipeline, infrastructure code and monitoring — not a platform programme. We size the work to your reality and skip the ceremony that does not pay for itself.
The first service usually runs through an automated build-to-deploy pipeline within the initial two-week sprint. Extending to the rest of the estate follows in waves, prioritised by risk and release pain.
Yes. We start from what exists — your repository host, your cloud, your current pipeline fragments — and improve incrementally rather than demanding a rewrite. Migration off a legacy CI system is a phase, not a precondition.
Manual deploys are a common starting point. We automate the current steps first, exactly as they happen, then improve the process once it is automated — so the team gains reliability before it has to change habits.
Schema migrations run as versioned, tested steps in the pipeline with expand-and-contract patterns, so deploys and rollbacks do not corrupt data. Destructive changes are staged and reviewed separately.
The opposite is the goal: faster, more reliable feedback. We measure build and test times during the assessment and treat pipeline speed as a requirement, with caching, parallelisation and test selection where they help.
Secrets move into a secrets manager, are injected at runtime, scoped per environment and rotated on schedule. Long-lived keys in config files are eliminated, and we show you how to keep it that way.
Your team owns the pipelines, the infrastructure code, the dashboards and the runbooks. We pair with your engineers throughout so knowledge transfers with the work, and we can stay available for review or later phases if useful.
Start with the question
Share what deploying looks like now, what breaks, and who does it. We will agree a practical first pipeline.