Audit and framing
Review the current architecture, workloads, failure modes and cost drivers before proposing a target.
AWS serverless architecture consulting
Serverless is not a goal in itself. It is a way to match capacity to activity, keep operations simple and measure cost per business operation.
I design and industrialise event-driven architectures on AWS for data, document and AI workloads, with explicit limits and observability.
The situations this answers
- A pipeline that works on one document but not on a real batch.
- Idle servers, runaway retries and unexplained monthly costs.
- No visibility on processing failures or queue backlogs.
- An architecture that mixes orchestration, business logic and AI calls.
How it fits together
One architecture, two serverless providers
Equivalent AWS and Google Cloud tracks, from gateway and workflow to storage and AI services, sharing observability and an execution sandbox.
What you get
- An event-driven architecture with explicit failure and retry policies.
- Orchestration separated from processing and from business rules.
- Observability on every stage, with traces and cost measurement.
- Infrastructure defined as code, reproducible across environments.
- Documentation and a handover session for the operating team.
How an engagement runs
Design and delivery
Build the event-driven architecture, the orchestration and the processing stages, with tests on real volumes.
Industrialisation and takeover
Add monitoring, alerts, cost controls and infrastructure as code, then hand over the runbook.
Proof and related reading
Frequently asked questions
Is serverless suitable for long-running AI workloads?
For long or bursty jobs, orchestration separates short processing steps from long-running work. The design keeps each step within its limits and handles timeouts explicitly.
Can we keep our existing infrastructure?
Yes. Migration can be progressive: new stages are built serverless while existing services keep running, then the boundary is reviewed.
How do you control costs?
Cost per business operation is measured, not guessed. Billing drivers are instrumented and idle or duplicated resources are removed.
Which AWS services do you use?
Lambda, API Gateway, Step Functions, EventBridge, SQS, S3, DynamoDB and RDS are selected per need. Managed AI services such as Textract or Bedrock are added when they fit the problem.