AWS application development with the operations built in.
Less to run and fewer surprises: managed AWS databases, storage, queues, and identity replace servers to maintain, with infrastructure defined in code, pipelines with rollback, tested backups, and cost mapped to each application.
- InterfaceReact · Next.js
- MobileReact Native
- ServicesNode.js · TypeScript
- DataPostgreSQL · Python pipelines
- AIOpenAI · Anthropic · chosen per task
- CloudAWS · Azure · Google Cloud
What we build with it
Where AWS fits.
Applications on managed services
Databases, storage, queues, and identity from AWS, so there is less to run and less to fail.
Deployment pipelines
Every change tested and released the same way, with rollback.
Monitoring, backups, and security
Failures show up before customers see them, backups are tested, and access is limited by role.
Moving from servers
Lift, replatform, or rebuild, chosen after an assessment and done in phases.
Use cases
Applications we build with AWS.
Multi-tenant software products
Software products with each customer’s data kept separate, sign-in through Amazon Cognito or another identity provider, and environments for testing and release.
Document storage and processing
Uploaded files stored in Amazon S3 with access controls, then scanned, converted, or read by extraction services as part of a workflow.
Event-driven integrations
Lambda functions, SQS queues, and EventBridge rules that move records between systems as events happen, with failures held for retry.
Data warehouses and reporting
Operational data gathered into Amazon Redshift, Athena, or a managed PostgreSQL reporting database that dashboards and analysts can query safely.
Scheduled batch processing
Recurring jobs for imports, exports, billing runs, and reconciliations, run on managed compute that scales up for the work and shuts down after.
Language model features on Bedrock
Language model features run through Amazon Bedrock where data should stay inside the AWS environment, with access logged and controlled by role.
We choose it when
- Your company already runs on AWS, or has no platform yet and wants the broadest set of managed services.
- The application needs managed databases, queues, and storage rather than servers to maintain.
- You want infrastructure defined in code that your team can operate.
We reach for something else when
- Your company runs on Microsoft 365 and Azure: Azure is usually the better fit.
- Your data and analytics live in Google Cloud: build there.
- A simple site: a managed platform host is easier than a cloud account.
How we use it
We define infrastructure in code, prefer managed services to self-run servers, deploy through a pipeline that works the same way every time, give monitoring and alerts a named owner, test backups, restrict access by role with managed secrets, and map cost to each application.
What it means for you
- Access defined by role, so your team, or any future team, can operate the application.
- Infrastructure is defined in code; nothing is configured by hand and forgotten.
- Runbooks and cost visibility are part of the handover.
Engineering practice
How we build with AWS.
Reviewed infrastructure as code
Every change to networks, databases, and permissions is written in code with Terraform or AWS CDK and reviewed before it is applied.
Least-privilege IAM roles
Each service and person receives only the permissions its job needs, reviewed on a regular schedule, with root access kept out of daily use.
Separate environments
Development, testing, and production run in separate AWS accounts, so a mistake in testing cannot reach live customer data.
Backup restore drills
Database and file backups are restored into a test environment on a schedule, proving that recovery works before it is ever needed.
Cost tagging and alerts
Every resource is tagged by application and environment, with budget alerts that flag unexpected spending to a named owner.
Questions
Questions about AWS.
What business and technology leaders ask us about it.
Which AWS services do you use?
We use managed services wherever possible: managed PostgreSQL, object storage, queues, identity, and containerized or serverless compute. The assessment picks what fits the application.
Can you move our existing application?
Yes, after an assessment that decides between lift and shift, replatform, and rebuild. Central applications move in phases with rollback at every step.
What about the bill?
Cost is mapped to applications from the first release, with the levers written down. Cloud cost is a design decision, not a surprise.
Is AWS a good choice for a mid-sized company?
Yes, when the application benefits from managed databases, queues, and storage. AWS offers the broadest set of managed services, and a well-structured setup with infrastructure in code keeps it understandable for a small team. For companies centered on Microsoft 365, Azure is often a better fit, and the assessment compares them.
How do you keep an AWS environment secure over time?
Access is defined by role with least privilege, secrets are held in AWS Secrets Manager, and CloudTrail records who changed what. Security findings from AWS tools are reviewed on a schedule, managed service versions are upgraded before support ends, and every infrastructure change goes through code review before it is applied.
Who can run the environment after launch?
Any engineer familiar with AWS and the infrastructure-as-code tool in use. Because nothing is configured by hand, the environment can be read, reviewed, and rebuilt from code. The handover includes runbooks for deployment, recovery, and common alerts, plus the cost view by application, so the team operating it has what it needs.
Discuss an AWS application.
Tell us about the application and the systems around it.We’ll come back with what we would build first, and which tools we would use.