Backend & Cloud
Event-Driven Architecture Services
We design and build event-driven architectures that stay reliable: queues/streams, idempotency, retries, and observability so automation and integrations scale without becoming fragile.
Overview
What this service is
This service designs event-driven systems where work is processed asynchronously: producers, consumers, queues/streams, and reliable handling of retries and failures.
We implement idempotency and deduplication patterns so events can be replayed safely without causing duplicate side effects.
You get monitoring guidance and runbook notes so teams can operate event pipelines with confidence and extend them over time.
Benefits
What you get
Better scalability under load
Async processing reduces bottlenecks and keeps user-facing APIs responsive.
More reliable integrations
Retries and dead-letter handling reduce missed events and silent failures.
Traceable workflows
Event logs and monitoring make it easier to debug and verify system behaviour.
Safer reprocessing
Idempotency patterns allow replay without double charging or duplicate writes.
Cleaner system boundaries
Event models and service boundaries reduce tight coupling between modules.
Easier long-term evolution
Add consumers and workflows over time without rewriting the entire backend.
Features
What we deliver
Event model design
Define event types, payload shape, versioning, and contracts between producers and consumers.
Queue/stream implementation
Implement queues or streams and consumer workflows aligned to volume and latency needs.
Retries + dead-letter strategies
Retry policies and dead-letter handling so failures are visible and recoverable.
Idempotency + deduplication
Keys and processing rules that prevent duplicate side effects during retries or replays.
Observability
Logging, tracing, and alerting hooks so event pipelines are operationally manageable.
Deployment + runbook notes
Operational guidance for scaling consumers, handling incidents, and rolling out changes safely.
Process
How we work
Discovery
We map events, producers/consumers, and failure scenarios to define the architecture scope.
Architecture
We design event contracts, retry policies, and observability requirements before building.
Implementation
We build producers, consumers, and processing pipelines with idempotency and logging built in.
Hardening
We test failure modes, replay scenarios, and throughput to validate production behaviour.
Handoff
We deliver runbook notes for operating and extending the event pipeline safely.
Tech Stack
Technologies we use
Core
Tools
Services
Use Cases
Who this is for
Webhook ingestion and processing
Process external events reliably with retries, dedupe, and clear failure routing.
Automation and workflow engines
Coordinate multi-step workflows asynchronously with traceable processing states.
Billing and payments events
Handle payment lifecycle events safely with idempotency and audit trails.
AI tool orchestration
Route tool calls and downstream actions through a reliable event pipeline with guardrails.
Data processing pipelines
Batch and streaming jobs that transform and export data predictably over time.
FAQ
Frequently asked questions
Not always. Many teams start with simpler queues. We’ll recommend streams like Kafka only when volume and requirements justify the complexity.
We use idempotency keys and processing rules so retries and replays don’t cause duplicate side effects.
Yes. Dead-letter handling is important for visibility and recovery when events fail repeatedly.
Yes. Observability is part of delivery so event pipelines are operationally manageable.
Yes. Event pipelines can route into automation tools like n8n and power MCP tool workflows with reliable execution patterns.
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Need event workflows that are reliable at scale?
Share your events and downstream actions. We’ll design an event-driven architecture with guardrails and rollout milestones.
Idempotency + observability included.