We containerize applications and run them on AWS — ECS Fargate, EKS, or App Runner, whichever actually fits your team. Legacy monolith or greenfield service, we take you from Dockerfile to a hardened, observable, auto-scaling platform. Nine apps moved off Heroku in 6 weeks with zero outages. AWS Advanced Tier Partner, founder-led on every engagement.
The container stack we ship on.
Containerization is not a trend to chase — it is a set of concrete operational wins. These are the three that matter most to the teams we work with, and the broader platform lives under our AWS DevOps services.
Hand-managed instances accumulate over-provisioning. Containers on Fargate bill per vCPU-second and GB-second your tasks actually request, and right-sized task definitions plus scheduled scaling squeeze the rest out. Moving containerized workloads off Heroku onto AWS cut one client's bill by 60%; a broader AWS account optimization delivered a 38% reduction — roughly $18k per month, $214k annualized.
A Docker image runs identically on a laptop, in CI, and in production — the "works on my machine" class of bug disappears. That same portability is what makes a move like DigitalOcean Kubernetes to ECS low-risk: the workload is already a container, so you are changing the orchestrator, not rewriting the app. It also keeps your exit options open across ECS, EKS, and other clouds.
Containers let you isolate per tenant and per workload: a dedicated service with its own least-privilege IAM role, private-subnet networking, and secrets injected at launch rather than baked into an image. A sensitive workload can live in its own service — or its own cluster and account — so one blast radius cannot reach another. We shipped this in production on an ISO-hardened ECS platform with WAF, GuardDuty, AWS Config, and Multi-AZ redundancy.
Container-native CI/CD replaces snowflake deploys with pipelines your team can inspect: automated tests, image scanning, environment promotion, and one-command rollback. After we containerized nine apps onto ECS, deploy frequency rose 14× — the same team shipping far more often, with blue/green cutovers that never took production down. Fast and safe are not a trade-off here.
The container is the easy part — the real decision is where it runs. We deliver all three, so the honest tradeoffs below are how we actually advise clients, not a pitch for one product.
No control plane, no hosts, no cluster upgrades — you define CPU and memory per task and AWS runs the rest, wired into IAM, ALB, CloudWatch, and Secrets Manager by default. This is where the majority of our containerization work lands because it removes the most operational burden for the least complexity. The tradeoff: it is AWS-native, so it is not a Kubernetes portability story.
Choose EKS when the Kubernetes ecosystem is the requirement, not the aspiration: existing Helm charts and operators, a service mesh, custom controllers, or a contractual multi-cloud commitment ECS cannot satisfy. The tradeoff is real — you own a control plane, node patching, and cluster upgrades, which usually means funding a platform engineer. We build it when it is right, and say so when it is not.
For a stateless web app or API where you want a running container URL quickly and do not need fine-grained networking, App Runner deploys straight from an image or repo with scaling and TLS handled for you. The tradeoff: less control over networking and placement than ECS, so it fits simple services rather than complex or compliance-heavy estates. We reach for it when simplicity is the actual goal.
The same five-phase playbook whether it is a legacy monolith or a greenfield service — no big-bang rewrites, a parallel run before any cutover, and numbers to prove each move.
We map dependencies, configuration, state, build steps, and network paths — and score the app against the 12-factor checklist below. This is where we find the local disk writes, hard-coded config, and in-process session state that would break a disposable container. You get a prioritized remediation list before a single Dockerfile is written.
Multi-stage builds for small, fast images; non-root users; pinned base images; and a clean separation of build and runtime. Config moves to environment variables and Secrets Manager, state moves to RDS, S3, or ElastiCache, and logs stream to stdout. The result is an image that is reproducible, scannable, and safe to run anywhere.
Pipelines that build to ECR with image scanning, then deploy with rolling or blue/green strategies. If you are on GitHub Actions we add OIDC federation into AWS so there are no long-lived keys; AWS-native teams get CodePipeline and CodeBuild. Every deploy is inspectable and every release has a one-command rollback.
Task definitions or manifests, auto-scaling on real signals rather than CPU guesswork, Multi-AZ placement, and health-checked zero-downtime deploys behind an ALB. We run old and new in parallel until the numbers prove the switch, then shift traffic. This is the phase where 99.95% uptime and zero-outage cutovers get engineered in, not hoped for.
Structured logs, metrics, and traces into CloudWatch (or your existing stack), with alarms and dashboards your on-call team can actually use. Once it is visible, we right-size and tune — Fargate Spot where it is safe, scheduled scaling for dev environments, ECR lifecycle policies to stop image sprawl. Cost work continues under our optimization practice.
At handover you have reproducible builds, inspectable pipelines, hardened networking, and dashboards — documented, in Terraform, and yours to run. Most clients then move to a monthly retainer for ongoing operations, but you are never locked into us to keep the lights on. Portability cuts both ways, and that is the point.
The 12-factor methodology is the practical bar for whether an app runs cleanly as a disposable container. Almost nothing passes on day one — and that is fine. Every gap on this list is something we remediate as part of the Dockerization work, not a reason to stop.
Run through it before you talk to us and you will already know where the effort will go. We score your app against exactly these points in the audit phase, then fix them on the way to ECS or EKS.
Get your readiness assessment →Not diagrams on a slide — full write-ups with the architecture, the launch type, and the numbers. Every one is a containerized workload running on AWS today.
Containerized production backend for a hospitality SaaS platform: automated CI/CD, blue/green deployments, Multi-AZ Fargate services, and WAF plus VPC isolation — leaner and more reliable than the setup it replaced.
ISO-hardened containerized architecture with AWS WAF, GuardDuty, AWS Config, Multi-AZ redundancy, and audited CI/CD pipelines — the per-workload isolation pattern regulated data demands, running in production.
Nine production applications containerized off Heroku onto ECS Fargate in 6 weeks — zero outages, 60% lower cost, and 14× more frequent deploys once the container-native pipelines were in place.
Containerized application moved from DigitalOcean Kubernetes to Amazon ECS with a zero-downtime cutover, RDS for the data layer, and an optimized footprint in the Mumbai ap-south-1 region.
AWS cost optimization for a UK health-tech platform: a 38% reduction in monthly spend — about $18k per month, $214k annualized — delivered in 90 days without slowing the engineering team.
Containerization rarely happens in isolation — it usually rides alongside a data-layer move and a CI/CD rebuild. Our broader migration practice covers the whole path, from Heroku or DigitalOcean into a hardened AWS estate.
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Book a call →Whether you're containerizing a legacy monolith, choosing between ECS, EKS, and App Runner, or planning a Docker-to-AWS move with compliance in scope — start with a free architecture review directly with the founder. One concrete recommendation, no commitment required.
★AWS Advanced Tier Services Partner · ISO 27001:2022 · Docker to ECS, EKS & App Runner
