Delivery engineering for platforms that keep changing.

KineticSkunk designs, migrates and governs GitLab delivery paths that support platform and application change across AWS and Azure, from new platform builds through ongoing managed operations.

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GitLab partner programmes you can verify

GitLab partner badges give named proof for vendor review. The stronger proof is how the delivery model connects migrations, CI/CD, runners, security checks, and release evidence to managed AWS and Azure platforms.

GitLab Channel Partner badge

GitLab Channel Partner

Channel partner status supports commercial and platform conversations when GitLab sits inside a wider cloud operating model.

Procurement, platform, and delivery stakeholders can tie GitLab adoption to a named partner programme, not unsupported tooling claims.

GitLab Professional Services Partner badge

GitLab Professional Services Partner

Professional Services Partner status supports implementation work on migrations, CI/CD design, runner strategy, and delivery governance.

Teams get GitLab delivery help tied to practical implementation work, not a generic tooling conversation.

View our GitLab Partner validation

How GitLab supports managed cloud delivery

GitLab is the delivery control layer when AWS and Azure platforms need change to stay reviewed, repeatable, and explainable.

Delivery foundation

Code, infrastructure, environments, and releases follow one governed path into managed platforms.

Built-in controls

Security checks, approvals, runner boundaries, and exception handling stay close to the merge request.

Operational evidence

Artifacts, deployments, approvals, and rollback signals remain visible for support and review.

Below is how each GitLab service lane strengthens that delivery path.

GitLab Services We Can Deliver

Expand each lane to see how GitLab delivery control supports managed AWS, Azure, and cloud platform operations.

Cloud delivery pipelinesCloud Platform Delivery Pipelines
AWS and Azure workloads are designed around repeatable build, scan, approval, deployment, and rollback paths.

GitLab CI/CD paths give cloud workloads a controlled route from source change to release.

We design the pipeline around environments, approvals, artifacts, deployment evidence, and rollback thinking before production pressure lands.

Supports Managed Platform Operations

This is the delivery foundation for managed platforms where releases need to be predictable and explainable.

  • Pipeline templates for application, infrastructure, and release stages
  • Environment promotion with approvals and artifacts visible
  • Rollback and deployment evidence tied to the change record
Toolchain consolidationGitLab Migration and Toolchain Consolidation
Fragmented delivery moves toward one workflow without losing the controls teams rely on.

Jenkins, scripts, and disconnected delivery tools often hide ownership and release evidence.

We map projects, groups, secrets, runners, pipeline parity, and staged cutover so migration decisions stay controlled.

Supports Managed Platform Operations

This is the migration path for teams that need fewer delivery tools and clearer operational ownership.

  • Project and group inventory before cutover
  • Pipeline parity and secrets planning
  • Staged migration with ownership visible
DevSecOps controlsDevSecOps Controls for Managed Platforms
Security and quality checks become part of release control, not a separate late-stage review.

Managed platforms need release paths that show what was scanned, approved, excepted, and deployed.

We embed SAST, dependency scanning, container scanning, secret detection, approvals, and exception handling into the delivery workflow.

Supports Managed Platform Operations

This is the control path for teams that need security evidence to stay connected to release work.

  • Security scans close to the merge request
  • Approval and exception handling before release
  • Evidence that supports customer and risk review
Runner platformRunner and Build Platform Engineering
Build capacity, isolation, and queue behaviour match the workloads the platform needs to release.

GitLab runners become platform infrastructure when they build, scan, package, and deploy production workloads.

We shape runner fleets around workload needs, security boundaries, queue expectations, cost control, and isolation.

Supports Managed Platform Operations

This is the build-platform path for teams whose delivery reliability depends on runner architecture.

  • Runner tags, pools, and isolation aligned to workload risk
  • Queue and build behaviour made visible
  • Cost and access boundaries designed into the build layer
AI delivery governanceAI-Assisted Delivery Governance
AI-assisted development supports delivery without weakening review, test, or security expectations.

AI-assisted development only helps when teams can still explain quality, security, and review decisions.

We connect AI-assisted code quality patterns to review, testing, approval, and governance routines that keep humans accountable.

Supports Managed Platform Operations

This is the governance path for teams adopting AI assistance inside delivery workflows.

  • AI assistance bounded by review and test expectations
  • Quality and security signals kept visible
  • Governance that supports adoption without overclaiming autonomy

SMB Solutions Strengthened by GitLab

GitLab matters when cloud change has to be reviewed, released, and explained.

These are the business outcomes it supports: governed delivery, managed operations, recoverable platforms, defensible access, observability, and validated resilience.

SMB solution
AWS Managed Platform iconGoverned Delivery

Platform assurance for CI/CD and release evidence

GitLab-led pipelines with the same governed outcome on Azure DevOps or AWS CodePipeline when that is your anchor.

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SMB solution
AWS Managed Platform iconAWS Managed Platform

Release control for production platforms

Use GitLab when AWS and Azure workloads need reviewed, repeatable delivery into managed platform operations.

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SMB solution
Data Protection and Recovery iconData Protection and Recovery

Delivery evidence for recoverable systems

Connect release history, approvals, and rollback routines to systems that need recoverable proof.

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SMB solution
Zero Trust Security iconZero Trust Security

Security checks close to change

Use GitLab controls to keep secrets, scans, approvals, and exception handling visible before release.

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SMB solution
AI Automation iconChatbot AI Automation

AI-assisted delivery with review control

Use AI-assisted development where review, testing, quality, and security expectations remain clear.

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SMB solution
Cloud Observability iconCloud Observability

Pipeline signals in the same investigation model

Correlate GitLab pipeline and deployment signals with platform and application telemetry so operators investigate change and runtime together.

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SMB solution
Resilience Testing and Assurance iconQuality Engineering

Validation signals tied to delivery confidence

Quality strategy, functional automation, API validation, and continuous testing wired into GitLab pipelines so quality is proven before merge.

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SMB solution
Resilience Testing and Assurance iconResilience Testing and Assurance

Validation evidence before production pressure

Connect GitLab release paths to performance, reliability, and security validation so non-functional behaviour is proven before customers feel gaps.

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How we make GitLab useful for cloud delivery

GitLab delivery work starts with the current estate, then moves toward a governed operating model that can support AWS, Azure, and managed hosting platforms.

Existing GitLab estate

Already on GitLab? Tighten the delivery controls.

We review groups, projects, runners, variables, pipelines, approvals, scanners, and environment promotion before changing what teams already rely on.

  1. 1

    Delivery estate assessment

    Map repositories, groups, permissions, runners, secrets, CI templates, deployment targets, and current release evidence.

    Known delivery surface

  2. 2

    Control and fit review

    Separate what should stay, what should be standardised, and what needs stronger security or release governance.

    Prioritised control plan

  3. 3

    Pipeline and runner alignment

    Align templates, runner tags, environments, artifacts, approvals, and rollback routines to managed cloud platform needs.

    Repeatable delivery paths

  4. 4

    Security and evidence hardening

    Wire scanning, exception handling, approval policy, and deployment evidence into the normal merge and release flow.

    Reviewable controls

  5. 5

    Managed platform handover

    Document operating routines so GitLab delivery supports AWS, Azure, and managed hosting operations after implementation.

    Operable delivery model

New managed cloud platform

Starting fresh? Build GitLab into the operating model.

We design GitLab delivery alongside the cloud platform so applications, infrastructure, scans, approvals, and release evidence are planned from day one.

  1. 1

    Operating model design

    Define group structure, project templates, branch strategy, runner model, environment promotion, and cloud deployment targets.

    Clear delivery design

  2. 2

    Pipeline foundation

    Create repeatable CI/CD templates for application, infrastructure, security, and release stages across AWS and Azure workloads.

    Ready delivery foundation

  3. 3

    Cloud deployment wiring

    Connect build, scan, package, deploy, and rollback routines to the managed AWS or Azure platform path.

    Controlled promotion

  4. 4

    Governance and training

    Set approval rules, exception handling, ownership, and practical team guidance so controls are usable.

    Sustainable adoption

  5. 5

    Managed operations handover

    Hand over release evidence, runner ownership, security checks, and support routines into the platform operating model.

    Managed cloud delivery

Request the DevSecOps white paper

DevSecOps delivery control for AWS and Azure platforms

Governed pipelines, security checks, and release evidence

Cloud platforms need more than faster releases. Teams need delivery paths where security scanning, approvals, runner boundaries, and release evidence stay visible before production change. This white paper explains how GitLab supports DevSecOps operating models on managed AWS and Azure platforms, and how to tighten controls without slowing delivery.

  • Map GitLab groups, projects, runners, and pipeline templates to managed cloud delivery needs
  • Place security scanning, exception handling, and approval policy close to merge requests
  • Connect CI/CD evidence to AWS and Azure deployment targets with clearer release ownership
  • Plan runner strategy, secrets handling, and environment promotion for regulated workloads
  • Use the framework to review an existing GitLab estate or design delivery from day one

GitLab delivery proof

These insights connect GitLab partner work to migration, CI/CD control, DevSecOps, custom runners, and AI-assisted delivery governance.

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See where your delivery pipeline stands in 3 minutes

Answer 10 quick questions across security automation, CI/CD governance, vulnerability management, compliance, and developer enablement. You get an instant maturity band and the practical next steps to close the gaps that slow secure delivery down.

Take the DevSecOps Maturity Assessment

Free, no obligation, and your results are shown to you straight away.

YOUR DEVSECOPS MATURITY REPORT

Review your overall score, competency breakdown, and recommended next steps before requesting a follow-up.

29 / 40

Advanced

Your DevSecOps practice is well established. Security is integrated into many stages of delivery, and teams use automation and measurable controls to reduce risk. The next step is to improve consistency and connect outcomes to business value.

RESULTS BY COMPETENCY

  • CultureExpert
  • Plan and DevelopAdvanced
  • Build and TestIntermediate
  • Release and DeployExpert
  • OperateBeginner
  • Observe and RespondAdvanced

This is a high-level self-check. A deeper, organisation-specific DevSecOps review is the right next step before you act on these results.

Example only. Your result will reflect your actual delivery practices across all six dimensions.

See governed GitLab delivery in a working demo

Book a short, tailored session and see CI/CD, security scanning, compliance, and governed delivery working on AWS and Azure. We focus on your delivery goals, not a generic slideshow.

Register for a demo

A KineticSkunk engineer walks you through it, no obligation.

GitLab delivery control connecting governed pipelines to managed AWS and Azure cloud platforms
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Make cloud change easier to trust.

If AWS and Azure are becoming more important to your business, your delivery system needs to show how change is reviewed, tested, secured, approved, and released.

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