API and Cloud Integration
An integration project is really a contract negotiation between two systems that were never designed to talk to each other. The interesting engineering is in what happens when that contract is violated - a duplicate webhook, a schema change, a rate limit hit mid-sync.
The Problem
Business tools that don't talk to each other force manual data entry and reconciliation, and a naive point-to-point integration tends to break silently the first time an upstream API changes its response shape.
Our Approach
We build integrations around explicit field-level ownership, idempotent processing, and visible failure - so a sync that can't complete raises an alert instead of silently dropping data.
Authentication and scoped credentials
Each integration uses credentials scoped to only the operations it actually performs - a read-only reporting sync doesn't hold write credentials to the source system, limiting the damage a compromised or misconfigured integration could do.
Mapping and transformation
Field-level mapping between systems is documented explicitly, including what happens when a field is missing or a value falls outside the expected range - undefined mapping behavior is where silent data corruption usually starts.
Idempotency and webhook handling
Webhooks can be delivered more than once by design (most providers document at-least-once delivery), so every webhook handler checks a dedupe key before acting - processing the same event twice is a normal case to handle, not a rare bug.
Monitoring and failure recovery
A failed sync is alerted, logged with enough detail to diagnose without needing to reproduce it live, and queued for retry or manual reconciliation - not retried silently forever or dropped without a trace.
Architecture and Approach
An integration typically has an authenticated API client or webhook receiver, a transformation step that maps fields between systems, an idempotency check against previously processed event IDs, and a monitoring/alerting layer that surfaces failures instead of absorbing them silently.
What We Build
- Third-party API integrations
- Cloud service and database connections
- Payment and CRM integrations
- Custom internal APIs
- Secure authentication and data handling
Use Cases
Common Engineering Challenges
An integration remains dependent on the upstream provider's API staying stable. Monitoring for unexpected response shapes (not just HTTP error codes) is what catches a breaking change before it corrupts data silently.
Most providers deliver webhooks at-least-once, meaning duplicates are expected, not exceptional. A handler that doesn't check a dedupe key will eventually process the same event twice.
FAQ
We monitor for unexpected response shapes, not just error codes, so a breaking upstream change is caught by alerting rather than silently corrupting synced data.
Yes, by design for most providers (at-least-once delivery) - our handlers check a dedupe key before acting, so a duplicate delivery doesn't apply the same change twice.
It's alerted and logged with enough detail to diagnose, then queued for retry or manual reconciliation - not silently dropped or retried indefinitely without visibility.