atomsized

Build the AWS platform where GitOps and AI can work safely together.

Services / Four platform capabilities

Start with the constraint that matters now: platform foundations, the change workflow, preview and UAT environments, or the operational signals needed for reliable decisions.

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Hand-drawn platform engineering toolbox with cloud, Kubernetes, security and observability tools

Four platform capabilities

Start with the constraint that matters now.

Each engagement strengthens one part of the controlled delivery model, then leaves the implementation and operating context with the client team.

foundationCapability map
Hand-drawn secure AWS foundation with identity, networking, runtimes, backups, budgets, and Terraform
AccountsIdentityNetworkRuntimeBudgets

Capability 01

AWS foundations and modernisation

Typical delivery
Accounts, IAM and SSO, networking, runtime, backups, budgets, Terraform modules, and handover.
Best fit
AWS growth has outpaced access, documentation, platform boundaries, or cost control.
You keep
The accounts, Terraform, configuration, diagrams, and runbooks.
GitOps + AI role
Defines the identity, environment, data, and permission boundaries used by engineers and AI.
gitopsCapability map
Hand-drawn GitOps and AI delivery workflow from evidence and pull request to review, deployment, and verification
EvidencePull requestReviewGitOpsVerify

Capability 02

GitOps and AI delivery workflows

Typical delivery
Argo CD, Helm, CI, promotion and policy gates, review context, verification, and rollback.
Best fit
Releases still depend on manual steps, console changes, fragmented evidence, or undocumented knowledge.
You keep
The repositories, pipelines, Helm values, Argo CD applications, policies, and release notes.
GitOps + AI role
Makes AI output inspectable and sends every proposal through the existing engineering review path.
previewCapability map
Hand-drawn pull-request workflow for isolated preview and coordinated UAT environments with automatic cleanup
Pull requestBuildReview URLValidateCleanup

Capability 03

Preview and UAT environments

Typical delivery
Pull-request triggers, isolated runtime and data, DNS and TLS, quotas, checks, and automatic teardown.
Best fit
Shared staging slows QA, product review, demonstrations, or cross-repository work.
You keep
The preview workflows, templates, cleanup rules, review URLs, and operating notes.
GitOps + AI role
Provides a controlled place to validate engineer- or AI-prepared changes before production.
reliabilityCapability map
Hand-drawn reliability workspace with observability, security review, load testing, backups, and cost controls
ObserveProtectTestMeasurePrioritise

Capability 04

Reliability, security, performance, and cost

Typical delivery
Monitoring, alerts, SLOs, security reports, load testing, backup checks, budgets, and runbooks.
Best fit
Incidents, security reviews, performance checks, or cloud-spend questions take too long to explain.
You keep
The dashboards, alerts, reports, tests, budget notes, remediation backlog, and runbooks.
GitOps + AI role
Provides approved evidence for AI to organise and engineers to evaluate.

Technical index

The working toolbox, organised by purpose.

Tools are selected to support the control model, not to create another platform layer your team has to maintain.

Cloud

  • AWS
  • IAM / SSO
  • VPC
  • EKS
  • Lambda
  • CloudFront
  • API Gateway
  • S3
  • AWS WAF

Containers

  • Kubernetes
  • Helm
  • Argo CD
  • ApplicationSets

Infrastructure as code

  • Terraform
  • Reusable modules
  • Environment configuration

CI/CD and GitOps

  • GitHub Actions
  • Image promotion
  • Policy gates
  • Rollback evidence

Operational evidence

  • CloudWatch
  • Prometheus
  • Grafana
  • Security reports
  • SLOs

Validation and controls

  • Preview environments
  • JMeter
  • Budgets
  • Backups
  • Runbooks
Schedule a platform call View case studies