Examkin

Question

Difficulty: Very hardRelease Management and Deployment Strategies

An enterprise organization is updating its release management pipeline for a mission-critical web application hosted on Google Cloud. The architecture uses Google Kubernetes Engine (GKE) for compute services and Cloud Spanner for backend database operations. The organization plans to implement automated canary deployments using Cloud Deploy and Service Directory, with automated traffic shifting based on real-time Cloud Monitoring error budget burn-rate metrics. To maintain high availability during releases and prevent operational failures, which TWO architectural practices must be incorporated into the deployment pipeline? (Select TWO.)

  1. Structure database schema updates to be strictly backward-compatible with previous application versions prior to initiating canary traffic shifts.Answer
  2. Maintain all Terraform deployment pipeline state files in a versioned Cloud Storage backend with object locking enabled.Answer
  3. C
    Grant the CI/CD automated deployment service account the primitive Project Editor role to prevent permission errors across dynamic infrastructure provisioning steps.
  4. D
    Configure ingress load balancer health check probes to query backend database tables directly on every check interval to verify end-to-end service health before routing canary traffic.
  5. E
    Provision a separate dedicated GKE cluster for each microservice build artifact during the canary stage to ensure complete compute environment isolation.

Answer

The deployment strategy requires implementing backward-compatible database schemas before canary traffic splitting and maintaining IaC deployment state in versioned Cloud Storage buckets with locking enabled.
Safe canary releases require that both old and new code versions can run concurrently against shared backing stores; therefore, database schema changes must be backward-compatible (e.g., expand-contract pattern). Furthermore, reliable automated infrastructure delivery requires state files stored securely in remote versioned storage with locking mechanics to ensure deployment pipeline integrity.

Step-by-Step Solution

1
Analyze database dependency requirements during canary traffic splitting.
Identified that both old and new container versions must run simultaneously against the shared database.
Non-backward-compatible schema migrations will cause immediate failures for requests routed to the baseline version during a canary roll-out.
2
Evaluate Infrastructure as Code state management for automated deployment pipelines.
Determined that concurrent CI/CD pipeline executions risk state locking conflicts and state corruption.
Centralized Cloud Storage backends with versioning and state locking guarantee atomic state updates across pipeline runs.
3
Evaluate distractor configurations against GCP architecture anti-patterns.
Eliminated options advocating primitive IAM role assignment, deep dependency health check probes, and per-build cluster provisioning.
These represent security risk, operational instability, and unnecessary compute overhead respectively.

Key Concept

Release Management Reliability and Zero-Downtime Deployment Strategies
Rate this question

Topics

Release Management and Deployment Strategies

More questions from this topic