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Home - Lessons - Google Cloud Development - M8 — Capstone: Build and Operate an Application - Wire secrets and identity correctly

Google Cloud Development Wire secrets and identity correctly
Google Cloud Development
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M1 — Cloud Application Development Lifecycle
How cloud runtimes differ from server deployment
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Twelve-factor application principles on Google Cloud
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Project structure, configuration and environments
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Local development and emulator workflows
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Container images and the distroless approach
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Deployment strategies and rollback planning
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M2 — Serverless Runtimes: Cloud Run and Functions
Cloud Run services, revisions and traffic splitting
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Container contract: port, concurrency and health
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Cloud Functions gen2 triggers and lifecycle
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Cold starts, warm pools and concurrency settings
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Authentication with Identity Platform and IAM
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Choosing between Cloud Run and Functions
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M3 — App Engine, Custom Runtimes and Migration
App Engine standard versus flexible
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Custom runtimes and Dockerfile authoring
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Scaling, instance class and automatic scaling
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Migrating from App Engine to Cloud Run
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Session and state handling
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Blue-green and canary releases
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M4 — Storage, Databases and Secrets in Application Code
Cloud Storage client access and signed URLs
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Cloud SQL connector and connection pooling
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Firestore for document workloads
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Memorystore for caching and sessions
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Secret Manager integration at startup
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Retry, backoff and idempotent writes
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M5 — Async Messaging and Integration
Pub/Sub publishing and subscription patterns
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Ordering, deduplication and dead-letter queues
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Workflows and orchestration for long-running tasks
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Eventarc triggers from Google Cloud events
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Third-party integration patterns
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Backpressure and queue sizing
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M6 — CI/CD with Cloud Build
Cloud Build triggers, substitutions and step ordering
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Building, testing and pushing artefacts
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Binary Authorization and deployment attestation
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Infrastructure as code alongside application code
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Environment promotion and approval gates
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Rollback and release verification
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M7 — Observability, Performance and Cost
Cloud Trace for latency analysis
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Cloud Logging structured logging and correlation
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Cloud Monitoring custom metrics and dashboards
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Error Reporting and crash triage
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Performance profiling and cold-start reduction
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Cost per request and rightsizing concurrency
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M8 — Capstone: Build and Operate an Application
Build a containerised API on Cloud Run
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Add asynchronous processing with Pub/Sub
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Persist data through Cloud SQL and Cloud Storage
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Wire secrets and identity correctly
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Ship through Cloud Build with canary release
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Diagnose a injected latency regression
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