Google Professional Cloud Developer

Company overview: SkyLend is a peer‑to‑peer micro‑lending platform expanding from one country to global regions (us-central1, europe-west1, asia-southeast1) and targeting a 10x increase in concurrent users (from 5,000 to 50,000) while reducing operational overhead; technical requirement: the public /loan and /payment APIs must meet 99.9% monthly availability and 95th percentile latency under 250 ms per region, teams must define SLIs and SLOs, track error budgets, visualize SLO health, and receive burn‑rate alerts (2x over 1 hour and 5x over 5 minutes) without building custom tooling; compliance and exec reporting require auditable SLO dashboards across services and regions. Question: Which Google Cloud product best meets SkyLend’s need to define, monitor, and alert on service level indicators and objectives (including error budgets and burn‑rate alerts) across regions?

Your IoT analytics company runs a multi-tenant data pipeline on a Google Kubernetes Engine (GKE) Autopilot cluster in us-central1 for 120 production customers, and you promote releases with Cloud Deploy; during a 2-week refactor of a telemetry aggregator service (container image <250 MB), developers will edit code every 5–10 minutes on laptops with 8 GB RAM and limited CPU and must validate changes locally before pushing to the remote repository. Requirements: • Automatically rebuild and redeploy on local code changes (hot-reload loop ≤ 10 seconds). • Local Kubernetes deployment should closely emulate the production GKE manifests and deployment flow. • Use minimal local resources and avoid requiring a remote container registry for inner-loop builds. Which tools should you choose to build and run the container locally on a developer laptop while meeting these constraints?

Your IoT solution in Google Cloud collects data from thousands of sensor devices. Each device must publish messages to its own Pub/Sub topic, and consume messages from its own subscription. You need to ensure that each device can only publish and subscribe to its own Pub/Sub resources, while preventing access to others. What should you do?

You are designing a tablet app for municipal tree inspectors that must store hierarchical observations (city -> district -> park -> tree -> inspection) with up to 5 nested levels and support offline work for up to 72 hours; upon reconnect, the app must automatically sync local changes and handle conflicts gracefully. A backend on Cloud Run will use a dedicated service account to enrich the same records (e.g., geocoding, policy tags) directly in the database, performing up to 5,000 writes per minute at peak. The solution must scale securely to 250,000 monthly active users in the first quarter and provide client SDKs with built-in offline caching and synchronization. Which database and IAM role should you assign to the backend service account?

Your mobile health platform currently stores per-user workout telemetry and personalized settings in a single PostgreSQL instance; records vary widely by user and evolve frequently as new device firmware adds fields (e.g., heart-rate variability, sleep stages), resulting in weekly schema migrations, downtime risks, and high operational overhead; you expect up to 8 million users, peak 45,000 writes/second concentrated by userId, simple key-based reads per user, and only per-user transactional consistency is required, not multi-user joins or complex cross-entity transactions. To simplify development and scaling while accommodating highly user-specific, evolving state without rigid schemas, which Google Cloud storage option should you choose?