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| Section | Weight | Objectives |
|---|
| Topic 1: Microservices Architecture | 14% | - Container orchestration with GKE
- 1. Designing Kubernetes cluster architectures
- 2. Configuring node pools and auto-scaling
- 3. Implementing workload deployment and scaling
- 4. Managing pod lifecycle and resource quotas
- API management
- 1. Exposing APIs with Cloud Endpoints / Apigee
- 2. Implementing API versioning strategies
- Service mesh and networking
- 1. Implementing service-to-service authentication
- 2. Implementing Anthos Service Mesh / Istio
- 3. Configuring traffic management and load balancing
|
| Topic 2: Monitoring, Logging, and Debugging | 12% | - Cloud Operations Suite
- 1. Implementing Cloud Logging with log sinks
- 2. Creating uptime checks and alerts
- 3. Configuring Cloud Monitoring metrics
- Debugging and troubleshooting
- 1. Debugging with Cloud Trace distributed tracing
- 2. Using Cloud Debugger and Error Reporting
- 3. Analyzing performance profiles with Cloud Profiler
- Log management
- 1. Configuring log retention policies
- 2. Structuring logs for efficient querying
- 3. Implementing log-based metrics
|
| Topic 3: CI/CD Pipeline Development | 26% | - Containerization and Docker
- 1. Managing container registries
- 2. Implementing container security best practices
- 3. Creating optimized Docker images (multi-stage builds)
- Designing and implementing CI/CD pipelines
- 1. Implementing build automation scripts
- 2. Configuring build caching strategies
- 3. Setting up artifact management with Artifact Registry
- 4. Configuring build triggers and webhooks
- 5. Designing pipeline architecture (Cloud Build, Jenkins, GitLab CI, etc.)
- CI/CD best practices
- 1. Managing secrets in CI/CD pipelines
- 2. Implementing shift-left testing
- 3. Configuring quality gates and code coverage
|
| Topic 4: Cloud Infrastructure Automation | 24% | - Deployment strategies
- 1. Canary releases and progressive rollouts
- 2. Blue-green deployments
- 3. Rolling updates with Kubernetes
- 4. Feature flags with Firebase Remote Config or LaunchDarkly
- Infrastructure as Code (IaC)
- 1. Implementing with Terraform
- 2. Managing infrastructure modules and state
- 3. Implementing immutable infrastructure patterns
- Configuration management
- 1. Using Ansible for configuration management
- 2. Managing secrets with Secret Manager
- 3. Implementing configuration drift detection
|
| Topic 5: Reliability and Site Reliability Engineering (SRE) | 24% | - SLOs, SLIs, and SLAs
- 1. Creating and interpreting Service Level Indicators
- 2. Defining and implementing Service Level Objectives
- 3. Setting appropriate Service Level Agreements
- 4. Error budget policies and management
- Incident management
- 1. Implementing on-call procedures
- 2. Post-incident reviews and blameless postmortems
- 3. Configuring automated incident response
- Monitoring and observability
- 1. Configuring Cloud Monitoring and Logging
- 2. Creating dashboards for service health visibility
- 3. Implementing distributed tracing with Cloud Trace
- 4. Setting up alerting policies and incident management
|
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Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q70-Q75):
NEW QUESTION # 70
You support a popular mobile game application deployed on Google Kubernetes Engine (GKE) across several Google Cloud regions. Each region has multiple Kubernetes clusters. You receive a report that none of the users in a specific region can connect to the application. You want to resolve the incident while following Site Reliability Engineering practices. What should you do first?
- A. Use Stackdriver Monitoring to check for a spike in CPU or memory usage for the affected region.
- B. Use Stackdriver Logging to filter on the clusters in the affected region, and inspect error messages in the logs.
- C. Reroute the user traffic from the affected region to other regions that don't report issues.
- D. Add an extra node pool that consists of high memory and high CPU machine type instances to the cluster.
Answer: B
NEW QUESTION # 71
You are managing the production deployment to a set of Google Kubernetes Engine (GKE) clusters. You want to make sure only images which are successfully built by your trusted CI/CD pipeline are deployed to production. What should you do?
- A. Enable Cloud Security Scanner on the clusters.
- B. Set up the Kubernetes Engine clusters as private clusters.
- C. Enable Vulnerability Analysis on the Container Registry.
- D. Set up the Kubernetes Engine clusters with Binary Authorization.
Answer: D
NEW QUESTION # 72
You are the Operations Lead for an ongoing incident with one of your services. The service usually runs at around 70% capacity. You notice that one node is returning 5xx errors for all requests. There has also been a noticeable increase in support cases from customers. You need to remove the offending node from the load balancer pool so that you can isolate and investigate the node. You want to follow Google-recommended practices to manage the incident and reduce the impact on users. What should you do?
- A. 1. Communicate your intent to the incident team.2. Add a new node to the pool, and wait for the new node to report as healthy.3. When traffic is being served on the new node, drain traffic from the unhealthy node, and remove the old node from service.
- B. 1. Communicate your intent to the incident team.2. Perform a load analysis to determine if the remaining nodes can handle the increase in traffic offloaded from the removed node, and scale appropriately.3. When any new nodes report healthy, drain traffic from the unhealthy node, and remove the unhealthy node from service.
- C. 1 . Drain traffic from the unhealthy node and remove the old node from service.2. Add a new node to the pool, wait for the new node to report as healthy, and then serve traffic to the new node.3. Monitor traffic to ensure that the pool is healthy and is handling traffic appropriately.4. Communicate your actions to the incident team.
- D. 1 . Drain traffic from the unhealthy node and remove the node from service.2. Monitor traffic to ensure that the error is resolved and that the other nodes in the pool are handling the traffic appropriately.3. Scale the pool as necessary to handle the new load.4. Communicate your actions to the incident team.
Answer: B
NEW QUESTION # 73
You are configuring your CI/CD pipeline natively on Google Cloud. You want builds in a pre-production Google Kubernetes Engine (GKE) environment to be automatically load-tested before being promoted to the production GKE environment. You need to ensure that only builds that have passed this test are deployed to production. You want to follow Google-recommended practices. How should you configure this pipeline with Binary Authorization?
- A. Create an attestation for the builds that pass the load test by using a private key stored in Cloud Key Management Service (Cloud KMS) with a service account JSON key stored as a Kubernetes Secret.
- B. Create an attestation for the builds that pass the load test by requiring the lead quality assurance engineer to sign the attestation by using their personal private key.
- C. Create an attestation for the builds that pass the load test by requiring the lead quality assurance engineer to sign the attestation by using a key stored in Cloud Key Management Service (Cloud KMS).
- D. Create an attestation for the builds that pass the load test by using a private key stored in Cloud Key Management Service (Cloud KMS) authenticated through Workload Identity.
Answer: D
Explanation:
The correct answer is B. Create an attestation for the builds that pass the load test by using a private key stored in Cloud Key Management Service (Cloud KMS) authenticated through Workload Identity.
According to the Google Cloud documentation, Binary Authorization is a deploy-time security control that ensures only trusted container images are deployed on Google Kubernetes Engine (GKE) or Cloud Run1.
Binary Authorization uses attestations to certify that a specific image has completed a previous stage in the CI
/CD pipeline, such as passing a load test2.Attestations are signed by private keys that are associated with attestors, which are entities that verify the attestations3.To follow Google-recommended practices, you should store your private keys in Cloud Key ManagementService (Cloud KMS), which is a secure and scalable service for managing cryptographic keys4.You should also use Workload Identity, which is a feature that allows Kubernetes service accounts to act as Google service accounts, to authenticate to Cloud KMS and sign attestations without having to manage or expose service account keys5.
The other options are incorrect because they do not follow Google-recommended practices. Option A and option D require human intervention to sign the attestations, which is not scalable or automated. Option C exposes the service account JSON key as a Kubernetes Secret, which is less secure than using Workload Identity.
Reference:
Creating an attestor, Creating an attestor.Cloud Key Management Service Documentation, Overview.
Attestations overview, Attestations overview.Using Workload Identity with Binary Authorization, Using Workload Identity with Binary Authorization.Binary Authorization, Binary Authorization.
NEW QUESTION # 74
You support a multi-region web service running on Google Kubernetes Engine (GKE) behind a Global HTTP'S Cloud Load Balancer (CLB). For legacy reasons, user requests first go through a third-party Content Delivery Network (CDN). which then routes traffic to the CLB. You have already implemented an availability Service Level Indicator (SLI) at the CLB level. However, you want to increase coverage in case of a potential load balancer misconfiguration. CDN failure, or other global networking catastrophe. Where should you measure this new SLI?
Choose 2 answers
- A. Your application servers' logs
- B. Instrumentation coded directly in the client
- C. A synthetic client that periodically sends simulated user requests
- D. GKE health checks for your application servers
- E. Metrics exported from the application servers
Answer: D,E
NEW QUESTION # 75
......
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