AWS Cloud Engineering
We design, deploy, and operate AWS workloads with explicit account boundaries, least-privilege access, observability, cost controls, and a tested path back when a change fails.
If any of this sounds like a Tuesday in your business…
Cloud architecture is an operating model, not a list of service logos. The right design follows the workload, risk, team, and recovery requirements.
- A web application needs a secure delivery path, domain, certificate, cache behavior, and repeatable deployment process.
- Container or serverless workloads have grown without a clear boundary between production, staging, and development.
- PostgreSQL, object storage, background jobs, and external APIs need a documented network and identity design.
- Cloud spend exists, but the team cannot connect cost to active workloads or safely pause idle environments.
- An AI or document workflow needs controlled use of services such as Textract without an unbounded batch-cost surprise.
Specific workflows we build
- Static and edge delivery with Amazon S3, CloudFront, Route 53, ACM, origin access controls, cache policies, and deployment verification.
- Container and managed-compute patterns using ECS/Fargate and App Runner, plus Lambda and API Gateway where event-driven or serverless designs fit.
- Data layers using RDS/PostgreSQL, S3 object storage, backup planning, environment separation, and migration runbooks.
- Identity and security controls using IAM, KMS, Secrets Manager, WAF, CloudTrail, Config, and scoped service roles.
- Operational visibility with CloudWatch logs, metrics, alarms, health checks, deployment evidence, and incident-ready runbooks.
- Cost and usage controls using Cost Explorer, schedules for non-production resources, resource inventory, and workload-specific guardrails such as Textract page caps.
Ready to see what your workflows are actually costing?
The Workflow Audit maps the workflows taking the most time across your team — and tells you which are worth automating. Start with a free 30-minute discovery call, or book the $1,500 Workflow Audit; implementation is quoted separately after review.
A defined process from first conversation to handoff
Current-state inventory
We map accounts, regions, domains, workloads, data stores, identity paths, costs, and dependencies before recommending a target design.
Architecture and threat review
The proposed boundary includes data flows, trust relationships, least privilege, failure modes, observability, backup, and recovery expectations.
Incremental implementation
Infrastructure and application changes are introduced in reversible stages with environment-specific verification.
Public and provider readback
We verify the deployed service, the AWS control plane, routing, security posture, and rollback evidence rather than stopping at a successful build.
Outcomes we expect — without making up numbers
We deliberately avoid specific percentage claims until real engagement data supports them. The audit gives you calibrated estimates for your specific scope.
- Teams can identify which AWS resources serve a current workload and which are candidates for review or retirement.
- Deployment, cache invalidation, health, and rollback steps become repeatable release gates.
- Cost controls can preserve needed environments while limiting avoidable idle and batch usage.
- Security and recovery claims are tied to the actual account, workload, and verification evidence.
Industries this solution serves
See how AWS Cloud Engineering fits the specific workflows of:
Based in Orlando, Florida · Veteran-owned operational software company · Local implementation and support across Central Florida
Ready to see what is worth automating?
Bring the current architecture, AWS accounts, workload inventory, and recovery expectations. We will separate observed facts from assumptions, identify the highest-risk gaps, and propose a reversible path forward.