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Flowchart Updated 4/16/2026

CI/CD Deployment Flowchart with Test Gates, Approval, and Rollback

A flowchart for a CI/CD deployment pipeline that starts with a code push, moves through build, unit, integration, staging, smoke testing, manual approval, production release, health monitoring, and rollback on failure. It is used to define release control points, clarify pass or fail paths, and reduce deployment risk. DevOps engineers, software teams, QA leads, and release managers use it to align responsibilities and improve delivery reliability.

CI/CDFlowchartDeploymentTest GatesRollback
17 nodes 19 connections

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Feature Flag Rollout Flowchart with Percentage Activation

A flowchart for feature flag rollout decisions, tracing each user request through a kill switch check, flag status, user-key hashing, rollout percentage evaluation, and final delivery of either the new feature or the existing flow before logging exposure. It is used to plan safer progressive releases, control blast radius, and verify fallback behavior, helping product teams, backend engineers, and SREs manage staged launches and rapid disablement.

flowchartfeature flagsrollout strategykill switchprogressive delivery
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IoT Platform Flowchart for MQTT Telemetry and Dashboard Access

This flowchart is used to map how IoT devices publish MQTT telemetry to a broker, how a stream processor routes that event data into a telemetry store, analytics warehouse, and alerting webhooks, and how a dashboard reaches registry and telemetry data through an API gateway. It helps teams design ingestion, monitoring, and integration paths, and is useful for IoT architects, backend engineers, platform teams, and technical stakeholders.

IoT architectureFlowchartMQTT brokerTelemetryDashboard
Flowchart 4/16/2026

Event-Driven Order Processing Flowchart with Kafka and Dead-Letter Queue

This flowchart is used to document an event-driven order processing architecture where order clients send requests through an API gateway to an order service, which writes to the order database and publishes events to Kafka for downstream consumers. It helps teams understand request flow, event handling, failure paths through the dead-letter queue, and archival to S3. Software architects, backend engineers, platform teams, and operations staff would use it.

flowchartorder processingKafkadead-letter queueS3 archive