Platforms that let your engineers ship faster, safely.
Most teams can deploy. Fewer can roll back at 2am or rebuild the environment from scratch. We close that gap and hand it over.
Outcomes you can expect.
CI/CD & infrastructure as code
We design delivery pipelines with quality and supply-chain security gates in line, and put every environment in code, so a release or a rebuild never depends on one person.
Who it is for
- Teams whose releases depend on one engineer who understands the build and cannot take a holiday.
- Organisations whose staging and production have drifted apart and nobody can say by how much.
- Regulated businesses that must show how a change reached production and who approved it.
What you get
- Pipelines in your repository that any engineer on the team can read and change
- Environments you could rebuild from code if you lost them
- Quality and security gates with a written reason for each
- A tested rollback and an audit trail for every release
- A recorded handover so the pipeline no longer depends on one person
What we do
Map how change reaches production
We trace a change from commit to running, including the manual steps, approvals and hand-offs nobody wrote down.
Design the pipeline
We build pipelines in GitHub Actions, GitLab or Jenkins with tests, SAST and dependency scans, SBOMs and signed artifacts as gates that run on every change, trunk-based and not as a review at the end.
Put environments in code
We write infrastructure as versioned Terraform modules with policy as code and remote state, so environments are built the same way every time and drift is detected, not discovered.
Make promotion boring
Changes move to production through the same path with progressive delivery, canary or blue-green, an automatic rollback we have exercised, and records of who approved what. We track the DORA metrics so improvement is measured.
Delivery pipeline assessment
A bounded look at how a change reaches production, where it depends on people, and what to fix first, ending in a written report and a prioritised plan.
What is examined
- How a change travels from commit to running, including every manual step and approval
- Which parts of the build and release depend on one person or one machine
- How far staging and production have drifted, and whether environments could be rebuilt from code
- Which tests, scans and approvals run as gates, and which are skipped under pressure
How it works
- 01 Scope. We agree which teams, services and pipelines are in, and who we need to talk to.
- 02 Discover. We read your pipelines and infrastructure code, trace real releases, and talk to the people who run them.
- 03 Assess. We find the single points of failure, the drift and the missing gates, and rank them by the risk they carry.
- 04 Report. We write up findings and a prioritised plan in plain language, with the first fixes marked.
- 05 Review. We walk through the report with your team, answer questions and agree what happens next.
What you receive
- A written report with prioritised findings
- A map of how change reaches production, with the risks marked
- A plan of fixes in order, with the reasons
- A readout session with your team
- If you want help, we can carry out the fixes, or hand the plan to your own team.
- If you do not, you keep a clear record of where the pipeline stands and why.
Scope and timing are agreed on a call, before anything is committed.
Kubernetes & developer platforms
We build production Kubernetes with GitOps, policy and secrets handled properly, then add an internal developer platform with golden paths that your engineers actually choose to use.
Who it is for
- Teams running a cluster that only one person is comfortable touching.
- Engineering groups where every team builds its own way to deploy and nobody can help another.
- Organisations starting on Kubernetes who want it run as a platform from the first day.
What you get
- A production cluster you can rebuild from the repository
- GitOps, policy and secret handling set up and documented
- Self-service environments and templates for the common cases
- Upgrade runbooks that have been rehearsed
- Training and recorded sessions for the team that will run it
What we do
Design the cluster
We choose EKS, AKS, GKE or self-managed Kubernetes, CNI networking, workload identity, Karpenter or Cluster Autoscaler, and the upgrade approach, and write down what each decision costs later.
Run it through Git
We set up GitOps with Argo CD, with Helm and Kustomize for packaging, so the state of every cluster is declared in a repository, reviewed like code, and recoverable.
Add policy and secrets
Admission policy with OPA Gatekeeper or Kyverno, secrets from AWS Secrets Manager, Azure Key Vault or Google Secret Manager via External Secrets, network policy and image signing stop unsafe workloads before they start.
Build the paved road
We give teams self-service environments and templates, on a developer portal such as Backstage where it fits, so the easy way and the correct way are the same way.
Plan the upgrades
Upgrades follow a written runbook with node pool rotation and pod disruption budgets, rehearsed first, so staying current is routine and not a project.
Observability & SRE
We instrument what matters with OpenTelemetry, set SLOs with the business, and run incident practice, so alerts page someone because something is actually wrong.
Who it is for
- Teams whose alerts fire so often that the real ones are ignored along with the rest.
- Organisations that find out about an outage from customers before they find out from monitoring.
- Engineering leaders who want reliability discussed in terms the business can weigh against new features.
What you get
- Instrumentation that is not tied to a single vendor
- Service levels and error budgets agreed with the business
- A smaller set of alerts, each with a runbook
- Dashboards organised around the golden signals
- An incident process your team has actually rehearsed
What we do
Instrument the services
We add metrics, logs and distributed traces with OpenTelemetry and its collector, feeding Prometheus, Grafana, CloudWatch, Azure Monitor or Google Cloud Monitoring, so you are not tied to one tool.
Set service levels
With the business we agree what reliable means for each service, then turn it into SLIs, SLOs and error budgets people can use to decide, with burn-rate alerts that warn early.
Fix the alerts
We remove alerts nobody acts on and keep those that need a person, routed through on-call with a runbook attached to each one.
Build dashboards that answer questions
Prometheus and Grafana dashboards organised around the golden signals, with traces and logs linked to metrics, so on-call can tell what is wrong in minutes.
Practise incidents
We run incident drills and chaos experiments, and write blameless post-incident reviews, so the second incident is handled better than the first.
Ready to get started?
Book thirty minutes with our team for a clear view of scope and cost.