Designing Backpressure into Event-Driven Integrations
A production architecture guide to protecting event consumers and downstream systems when event arrival rates exceed processing capacity.
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Designing Contract Evolution for Event-Driven Systems
Event producers and consumers evolve independently. This deep dive explores additive change, semantic compatibility, versioning and migration without turning the event bus into a coordination bottleneck.
Read article →Designing Durable Salesforce CDC Processing with MuleSoft
A production design for consuming high-volume Salesforce Change Data Capture events without depending on the 72-hour event-bus window: durable handoff, replay checkpoints, sequencing, parallel processing, backpressure and recoverable error handling.
Read article →Designing Idempotent Integrations in Distributed Systems
A practical architecture guide to preventing duplicate business effects when APIs, events, batches, and recovery workflows are retried or replayed.
Read article →Designing Observability for Enterprise Integrations
A practical architecture for tracing business transactions across APIs, events, queues and downstream systems without confusing logs with observability.
Read article →Designing Reliable Event-Driven Integrations Across Transaction Boundaries
A practical architecture guide to reliable event publication and consumption when business state, brokers, databases, and external systems cannot share one atomic transaction.
Read article →Designing Safe Replay and Reprocessing in Integration Platforms
Retries are only one recovery mechanism. This deep dive separates retry, replay and reprocessing and shows how to design each without creating duplicate business effects.
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