CI/CD Consulting & Pipeline Automation

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.

Sound familiar?

Deploys require a specific person

One engineer holds the keys to production. When they're on leave, nothing ships.

Builds take 15+ minutes

PRs queue up. Developers context-switch. Feedback that should take seconds stretches to hours.

Friday releases terrify the team

"Let's wait until Monday" is your unofficial deployment policy.

PRs pile up faster than you can review them

AI agents open more pull requests than your team can read. Review is now the bottleneck, not writing code.

No staging environment

Code goes from a laptop to production with nothing in between.

Secrets live in plaintext

API keys in Git, credentials in Slack, tokens in shared docs.

Rollback means "revert and pray"

No blue-green. No canary. No automated recovery when things go wrong.

What changes after we're done

Multiple deploys per day

Multiple deploys per day

Automated pipelines mean any team member can ship to production in minutes, not days.

90% fewer deployment failures

90% fewer deployment failures

Automated tests, security scans, and environment promotion catch problems before users do.

Hours back per sprint

Hours back per sprint

No more manual release rituals. Your engineers build product instead of babysitting deployments.

Audit trail for every change

Audit trail for every change

Who deployed what, when, and why. Full traceability for compliance and incident response.

How we solve deployment problems

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.

What we implement

Automated testing and builds

Unit, integration, and E2E tests triggered on every push. Quality gates that block broken code from progressing.

Terraform pipelines

Plan on PR, apply on merge. No manual terraform apply from anyone's laptop. State locking and drift detection included.

Container build and deploy

Multi-stage Docker builds with caching, vulnerability scanning, image signing, and push to ECR or your registry.

Deployment strategies

Blue-green, canary, and rolling deploys to ECS, EKS, or Lambda with automated rollback on failure.

GitOps with ArgoCD

Declarative Kubernetes delivery with automated sync, drift reconciliation, and multi-cluster support.

Pipeline security

SAST/DAST scanning, dependency checks, OIDC auth, and least-privilege runners built into every pipeline.

AI code review in the 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.

The engagement

1

Week 1: Audit

We map your current deployment process, measure build times and failure rates, and identify the highest-impact improvements.

2

Week 2: Design

We architect the pipeline stages, branching strategy, environment promotion, and security model. You review before we build.

3

Weeks 2-3: Build

We implement pipelines in your repository as code. Automated tests, deploys, rollbacks, secrets - all committed and working.

4

Week 4: Handover

Documentation, runbooks, and knowledge transfer sessions. Your team owns it. We provide a support window for questions.

Ready to ship with confidence?

Who trusts us

"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

  • ✓ AWS Advanced Tier Partner with DevOps Engineer Professional certification
  • ✓ Senior engineers only - no juniors, no offshore handoffs
  • ✓ Both application and infrastructure pipelines (Terraform included)
  • ✓ Flexible engagements from 4-hour reviews to full sprints

Frequently asked questions

We scale engagements to fit the work: from a focused half-day pipeline review to full implementation projects of 3-4 weeks, priced by complexity and number of services. We also offer ongoing pipeline maintenance as part of a cloud support retainer.

A pipeline audit takes 3-5 days. Design and implementation for a single-service application takes 2-3 weeks. Complex multi-service architectures with infrastructure CI/CD and multi-environment deployments take 4-8 weeks. Most teams see measurable improvement within the first week of implementation.

Primarily GitHub Actions and AWS CodeBuild. We also support GitLab CI, AWS CodePipeline, ArgoCD, Bitbucket Pipelines, and Tekton. The choice depends on where your code lives, where you deploy, and what your team already knows. We optimise for tools your team will maintain long-term.

Yes. We design pipelines for both application code and infrastructure as code (Terraform, OpenTofu). Infrastructure CI/CD includes automated plan/apply workflows, state locking, policy checks, cost estimation, and approval gates. No more manual terraform apply from laptops.

Absolutely. Most engagements start with optimising what exists rather than replacing it. We reduce build times, add missing security scanning, fix secret management, and add deployment stages incrementally. A full rewrite is only necessary when the existing setup is fundamentally broken.

Security at every stage: SAST and DAST scanning, dependency vulnerability checks, container image scanning, OIDC authentication (no long-lived credentials), least-privilege runner access, signed artifacts, and full audit logging of all deployments.

CI/CD consulting focuses on architecture design, pipeline strategy, and guiding your team. Implementation means we write the pipeline code, configure the runners, and deliver working automation. Most of our engagements combine both: we design the overall strategy with you, then implement the critical pipelines while documenting patterns for your team to replicate.

We offer two models. Project-based: we audit, design, and build your pipelines in 3-4 weeks, then hand over ownership to your team. Ongoing: we maintain and evolve your CI/CD as part of a monthly CloudOps retainer, handling pipeline updates, security patches, and performance optimisation. Both models start with senior engineers only — no juniors, no offshore.

Yes. We deliver CI/CD consulting to teams in the US as well as the UK and Europe. Engagements are remote and pipeline work is committed directly to your repository, so the time overlap with US teams is enough for the reviews, working sessions, and async handovers a pipeline project needs. All work is delivered by senior engineers in English.

Yes. We wire AI code review into your pipeline as a pull-request gate in GitHub Actions or Azure DevOps, using blast-radius triage: low-risk changes can ship on the AI review, while high-risk ones (authentication, public APIs, database schema) still require a human. Crucially, we build the guardrails underneath - tests, security scanning, observability, and a working rollback - that make auto-merging low-risk changes safe rather than just faster.

Not entirely, and we do not recommend it. The pattern that works is a split by risk: AI handles the volume of low-blast-radius changes, and a human stays in the loop for high-stakes changes and architectural intent that a model cannot judge. AI review sits alongside your linter and SAST as a complementary layer, not a replacement for either the tools or the reviewer.

CI/CD Consulting: From Audit to Production-Ready Pipelines

Who needs CI/CD consulting?

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.

CI/CD implementation vs CI/CD consulting

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.

Tools we implement

Use casePrimary toolAlternatives
Application CI/CDGitHub ActionsGitLab CI, Bitbucket Pipelines
Infrastructure CI/CDTerraform + GitHub ActionsOpenTofu, Atlantis
Kubernetes deliveryArgoCDFlux, Helm + GitHub Actions
Security scanningTrivy, SnykGrype, Dependabot
Secrets managementAWS Secrets Manager + OIDCHashiCorp Vault

CI/CD for regulated industries

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 consulting

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.

CI/CD pipeline consulting for cloud-native teams

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).

CI/CD automation services

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.

AI code review in your CI/CD pipeline

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) →

Related resources

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