Event and trigger design
Queues, topics, schedules and streams chosen per workload, with dead-letter handling and replay defined before the first function is deployed rather than after the first lost message.
Infrastructure & Cloud
Serverless Architecture
Event-driven services that scale to zero, stay affordable, and do not melt under cold starts.
The work
What this actually does
Serverless pays off when the workload is spiky, event-driven and mostly idle. We look at your actual traffic shape first, because a steady high-throughput service is usually cheaper and simpler on containers. Where functions fit, we design around small handlers, explicit timeouts and idempotent processing, since retries are a normal part of the contract, not an error.
Cold starts, concurrency limits and the cost of a chatty queue are the things that go wrong in practice, so they get measured rather than assumed. We tune memory and runtime, move unavoidable work out of the request path, and set concurrency ceilings that protect the database sitting behind the function.
If any of these sound familiar
- The monthly bill is fine until one batch job runs wild
- Cold starts add two seconds to the request users notice most
- Nobody can trace a failed event through five queues and a retry
- Local development does not resemble the deployed function at all
Scope
What's included
Every engagement on this page covers the following, sized to your setup rather than delivered as a fixed package. If something here is not relevant to you, it comes off the scope and off the price.
Cold-start tuning
Runtime and memory measured against real payloads, with provisioned concurrency reserved for the handful of paths where the first request latency actually matters to users.
Concurrency and limits
Reserved and burst concurrency set per function so one noisy tenant cannot exhaust the account, and downstream databases are protected by a deliberate ceiling rather than good intentions.
Step and workflow orchestration
Multi-step processes expressed as state machines with visible history, so a stuck order can be inspected and retried without reading logs across four separate services.
Cost and usage controls
Budgets, alarms and per-function cost reporting, plus a review of the log volume that quietly becomes the largest line on many serverless invoices.
Local development parity
A local runtime that matches the deployed environment, seeded events for testing, and a deploy path a single engineer can run without waiting on a shared environment.
What changes
What teams typically see
0Idle compute charges
300 msTypical warm response
1 triggerPer business event
Handover
What you keep
Everything produced during the engagement is yours: the repositories, the accounts, the documentation. There is no proprietary layer and nothing to unlicense if you take the work in-house.
- Function and event topology documentation with diagrams
- Infrastructure code for functions, queues and permissions
- Concurrency and timeout settings for each endpoint
- Observability setup with trace correlation across services
- Cost report broken down by function and trigger
Tooling
Tools we use here
A starting point, not a requirement. We work in whatever you already run wherever it does the job.
AWS
Microsoft Azure
Google Cloud
Node.js
Python
Go
OpenTelemetry
PostgreSQL
How it runs
From first call to handover
The same four steps on every engagement. You see each one before it starts and can stop at any of them.
- 01
Profile the traffic
We chart request volume, burstiness and tolerance for latency, then say plainly whether functions will save money or add a moving part for nothing.
- 02
Model the event flow
Every trigger, queue and failure path drawn on one page before implementation, which is where most of the value in a serverless design is actually created.
- 03
Build and load test
Handlers are written small and deployed early, then pushed with realistic traffic to expose throttling, connection limits and the cold starts that only appear under load.
- 04
Instrument and hand over
Tracing, structured logs and cost alarms go in before launch, and your team gets the deployment runbook plus a short guide on adding the next function.
Questions
Asked before we start
Is serverless cheaper than containers?
Sometimes. For spiky traffic that is idle most of the day, usually yes. For steady, high-throughput workloads, containers on reserved capacity often cost less and are easier to reason about. The traffic profile decides, not the marketing.
Do cold starts make this unusable for user-facing APIs?
Not if you measure them. Many endpoints warm in well under a second once memory and runtime are tuned. For the few paths where the tail latency matters, provisioned concurrency costs a little and removes the problem entirely.
How do we test event-driven code locally?
With a local runtime that mirrors the deployed one and a set of recorded or synthetic events kept in the repository. It is never identical to the cloud, so we also run integration tests in a disposable account against the real services.
What about vendor lock-in?
It is real, and pretending otherwise is unhelpful. Keep business logic in plain handlers with thin adapters around the provider's triggers and queues, so moving is a contained piece of work rather than a rewrite.
Infrastructure & Cloud
Often needed alongside this
Platform & Containers
Kubernetes & Containers
Production-grade clusters with sane defaults, safe rollouts and an operator experience your team will actually enjoy.
- EKS, AKS, GKE and self-managed clusters
- Helm, Kustomize and GitOps-driven deployments
- Node autoscaling, resource tuning and cost control
Reliability & Performance
Monitoring & Observability
Know what broke, why it broke and who it affects — before your customers have to tell you.
- Prometheus, Grafana, Datadog & CloudWatch
- OpenTelemetry tracing and structured logging
- SLO dashboards and actionable alert routing
Infrastructure & Cloud
Cloud Architecture & Migration
Well-architected landing zones and migrations that move workloads without moving your risk profile.
- AWS, Azure and Google Cloud landing zones
- Lift-and-shift, replatform and re-architect paths
- Network, IAM and multi-account structure design
Worth a conversation about Serverless Architecture?
Bring the specific problem. We will tell you honestly whether this is the service that fixes it, and what it would take.