Ship faster, break less. We design and implement CI/CD pipelines that let your team release multiple times per day without manual steps, without fear, without "the one person who knows how." As AI agents write more of your code, we also wire AI-assisted review into the pipeline - with the guardrails that keep auto-merge safe.
One engineer holds the keys to production. When they're on leave, nothing ships.
PRs queue up. Developers context-switch. Feedback that should take seconds stretches to hours.
"Let's wait until Monday" is your unofficial deployment policy.
AI agents open more pull requests than your team can read. Review is now the bottleneck, not writing code.
Code goes from a laptop to production with nothing in between.
API keys in Git, credentials in Slack, tokens in shared docs.
No blue-green. No canary. No automated recovery when things go wrong.
Automated pipelines mean any team member can ship to production in minutes, not days.
Automated tests, security scans, and environment promotion catch problems before users do.
No more manual release rituals. Your engineers build product instead of babysitting deployments.
Who deployed what, when, and why. Full traceability for compliance and incident response.
Problem
Deploys require a specific person
We automate the entire path from commit to production. Any team member can trigger a release.
Problem
Builds take 15+ minutes
We parallelise jobs, add layer caching, split test suites, and eliminate redundant steps.
Problem
No staging environment
We build environment promotion pipelines - dev, staging, production - with automated gates between each.
Problem
Secrets in plaintext
We implement OIDC authentication, vault integration, and scoped secrets with zero long-lived credentials.
Problem
No rollback strategy
Blue-green or canary deployments with automated rollback triggered by error rate thresholds.
Problem
No deployment audit trail
Every deploy is logged, attributed, and linked to the triggering commit and approval.
Problem
PRs pile up faster than you can review them
We add AI code review as a PR gate with blast-radius triage - low-risk changes ship on the AI review, high-risk ones (auth, public APIs, schema) still require a human - backed by tests, scans, and rollback that make it safe.
Unit, integration, and E2E tests triggered on every push. Quality gates that block broken code from progressing.
Plan on PR, apply on merge. No manual terraform apply from anyone's laptop. State locking and drift detection included.
Multi-stage Docker builds with caching, vulnerability scanning, image signing, and push to ECR or your registry.
Blue-green, canary, and rolling deploys to ECS, EKS, or Lambda with automated rollback on failure.
Declarative Kubernetes delivery with automated sync, drift reconciliation, and multi-cluster support.
SAST/DAST scanning, dependency checks, OIDC auth, and least-privilege runners built into every pipeline.
AI review wired in as a PR gate with blast-radius triage and human-in-the-loop for high-risk changes - integrated into GitHub Actions or Azure DevOps, backed by the tests, scans, and rollback that make auto-merge safe.
1
We map your current deployment process, measure build times and failure rates, and identify the highest-impact improvements.
2
We architect the pipeline stages, branching strategy, environment promotion, and security model. You review before we build.
3
We implement pipelines in your repository as code. Automated tests, deploys, rollbacks, secrets - all committed and working.
4
Documentation, runbooks, and knowledge transfer sessions. Your team owns it. We provide a support window for questions.
"Devopsity has delivered a high-quality CI/CD performance improvements in our delivery pipelines. They implemented solutions that we still use to facilitate further app developments. Their team was committed to the project and customised their initial plan and offering to accommodate our budget."
Łukasz Królak
Head of Product Development, ZIPZERO Global LTD
"Devopsity helped us improve deployment efficiency and reduce costs for running deployments and cloud services. We appreciated how they helped us meet our immediate goals on time."
Dave
Head of Engineering, Educational Game Developer, Edinburgh based EdTech
Engineering teams that have outgrown manual deployments but lack the DevOps expertise to build automated pipelines in-house. Common triggers: scaling from 5 to 20+ developers, preparing for SOC2/ISO compliance, migrating from Jenkins to GitHub Actions, or adopting Kubernetes with GitOps.
Implementation means we build your pipelines. Consulting means we design the architecture, review what exists, and guide your team to build it. Most engagements blend both: we design with you, build the critical path, and document the rest for your team to complete.
| Use case | Primary tool | Alternatives |
|---|---|---|
| Application CI/CD | GitHub Actions | GitLab CI, Bitbucket Pipelines |
| Infrastructure CI/CD | Terraform + GitHub Actions | OpenTofu, Atlantis |
| Kubernetes delivery | ArgoCD | Flux, Helm + GitHub Actions |
| Security scanning | Trivy, Snyk | Grype, Dependabot |
| Secrets management | AWS Secrets Manager + OIDC | HashiCorp Vault |
We implement pipelines that satisfy SOC2, ISO 27001, and FCA requirements: signed artifacts, immutable audit logs, separation of duties, and automated compliance gates. Read our approach to UK fintech cloud compliance →
Continuous delivery means every commit is deployable to production at any time. Our continuous delivery consulting focuses on the practices and tooling that make this possible: trunk-based development, feature flags, automated quality gates, and environment promotion strategies. We design systems where deploying is a non-event — predictable, repeatable, and safe.
Cloud-native CI/CD differs from traditional approaches. Container builds, multi-environment Kubernetes deployments, infrastructure-as-code pipelines, and GitOps require different patterns than simple application deploys. We specialise in CI/CD for teams running on AWS (ECS, EKS, Lambda), Azure (AKS, Container Apps), and GCP (GKE, Cloud Run).
Our CI/CD automation services eliminate manual steps from your delivery process: automated testing on every push, security scanning integrated into pipelines, infrastructure provisioning triggered by code changes, and deployment strategies that roll back automatically on failure. The result is a fully automated path from developer commit to production deployment.
As AI agents generate more of your code, review becomes the bottleneck. We wire AI code review in as a pull-request gate with blast-radius triage: low-risk changes ship on the AI review, while high-risk ones (authentication, public APIs, database schema) still require a human. The guardrails underneath are what matter - tests, scans, observability, and a working rollback - without them it is not automating review, just removing it. How to wire AI code review into your pipeline (and what it misses) →