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Google Professional-Cloud-Architect Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Designing for security and compliance	17.5%	- Enforcing compliance and governance 1. VPC Service Controls and security perimeters 2. Security controls, auditing, and logging - Implementing identity and access management 1. IAM roles, permissions, and service accounts 2. Organizational policies and resource hierarchy - Securing data and communications 1. Encryption at rest and in transit 2. Key management and secret security
Topic 2: Ensuring solution and operations excellence	12.5%	- Applying Well-Architected Framework principles 1. Operational excellence, reliability, security, cost, and performance pillars - Implementing monitoring, logging, and observability 1. Alerting, dashboarding, and root cause analysis 2. Cloud Monitoring, Logging, and Error Reporting - Planning for continuous improvement 1. Technology updates and architecture evolution 2. Feedback loops and optimization cycles
Topic 3: Designing and planning a cloud solution architecture	25%	- Designing cloud solution infrastructure aligned with business requirements 1. Compliance and regulatory requirements consideration 2. Cost optimization strategies 3. Scalability, high availability, and fault tolerance design - Evaluating and selecting Google Cloud services 1. Compute, storage, database, and networking service selection 2. Serverless and managed service adoption - Planning cloud migration and hybrid/multi-cloud environments 1. Interoperability and integration design 2. Data transfer and synchronization 3. Migration planning and execution
Topic 4: Managing implementation	12.5%	- Using Google Cloud tools and APIs programmatically 1. Cloud SDK, Cloud Shell, and Cloud Code 2. Infrastructure as Code (Terraform, Deployment Manager) - Guiding development and deployment teams 1. Application and infrastructure deployment strategies 2. CI/CD pipelines and automation - Testing and validating solutions 1. Functional, performance, and security testing 2. Disaster recovery and failover testing
Topic 5: Analyzing and optimizing technical and business processes	15%	- Streamlining operational workflows 1. Stakeholder communication and alignment 2. Change management and incident response - Improving reliability and performance 1. Latency reduction and throughput optimization 2. SLO, SLA, and error budgeting - Optimizing cost and resource efficiency 1. Committed use discounts and pricing models 2. Resource right-sizing and usage monitoring
Topic 6: Managing and provisioning solution infrastructure	15%	- Provisioning and managing compute resources 1. VMs, GKE, App Engine, Cloud Run deployment and management 2. Auto-scaling and resource management - Configuring network topologies and connectivity 1. VPC design, peering, and hybrid connectivity 2. Load balancing and CDN configuration - Managing storage and data services 1. Cloud Storage, Filestore, Persistent Disk management 2. Database deployment, replication, and backup

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Google Certified Professional - Cloud Architect (GCP) Sample Questions (Q43-Q48):

NEW QUESTION # 43
You have a Python web application with many dependencies that requires 0.1 CPU cores and 128 MB of memory to operate in production. You want to monitor and maximize machine utilization. You also to reliably deploy new versions of the application. Which set of steps should you take?

A. Perform the following:
1) Create a Kubernetes Engine (GKE) cluster with n1-standard-4 type machines.
2) Build a Docker image from the master branch will all of the dependencies, and tag it with "latest".
3) Create a Kubernetes Deployment in the default namespace with the imagePullPolicy set to
"Always".
Restart the pods to automatically deploy new production releases.
B. Perform the following:
1) Create a Kubernetes Engine cluster with n1-standard-1 type machines.
2) Build a Docker image from the production branch with all of the dependencies, and tag it with the version number.
3) Create a Kubernetes Deployment with the imagePullPolicy set to "IfNotPresent" in the staging namespace, and then promote it to the production namespace after testing.
C. Perform the following:
1) Create a managed instance group with f1-micro type machines.
2) Use a startup script to clone the repository, check out the production branch, install the dependencies, and start the Python app.
3) Restart the instances to automatically deploy new production releases.
D. Perform the following:
1) Create a managed instance group with n1-standard-1 type machines.
2) Build a Compute Engine image from the production branch that contains all of the dependencies and automatically starts the Python app.
3) Rebuild the Compute Engine image, and update the instance template to deploy new production releases.

Answer: A

Explanation:
https://cloud.google.com/compute/docs/instance-templates

NEW QUESTION # 44
Your company has an application running as a Deployment in a Google Kubernetes Engine (GKE) cluster When releasing new versions of the application via a rolling deployment, the team has been causing outages The root cause of the outages is misconfigurations with parameters that are only used in production You want to put preventive measures for this in the platform to prevent outages What should you do?

A. Configure health checks on the managed instance group
B. Create a Scheduled Task to check whether the application is available
C. Configure an uptime alert in Cloud Monitoring
D. Configure liveness and readiness probes in the Pod specification

Answer: A

Explanation:
This option can help prevent outages caused by misconfigurations with parameters that are only used in production. Liveness and readiness probes are mechanisms to check the health and availability of the Pods and containers in a GKE cluster. Liveness probes determine if a container is still running, and if not, restart it.
Readiness probes determine if a container is ready to serve requests, and if not, remove it from the load balancer. By configuring liveness and readiness probes in the Pod specification, you can ensure that your application can handle traffic and recover from failures gracefully during a rolling update. The other options are not optimal for this scenario, because they either do not prevent outages, but only alert or monitor them (B, C), or do not apply to GKE clusters, but to Compute Engine instances (D). References:
https://cloud.google.com/kubernetes-engine/docs/how-to/updating-apps
https://cloud.google.com/blog/products/containers-kubernetes/kubernetes-best-practices-setting-up-health

NEW QUESTION # 45
As part of your backup plan, you set up regular snapshots of Compute Engine instances that are running. You want to be able to restore these snapshots using the fewest possible steps for replacement instances. What should you do?

A. Use the snapshots to create replacement disks. Use the disks to create instances as needed.
B. Export the snapshots to Cloud Storage. Create disks from the exported snapshot files.
Create images from the new disks.
C. Use the snapshots to create replacement instances as needed.
D. Export the snapshots to Cloud Storage. Create images from the exported snapshot files.

Answer: C

Explanation:
D (Correct Answer) - D is correct because the scenario asks how to recreate instances.
A, B, and C are not correct because the Google best practice of creating images from running Compute Engine instances is to first take a snapshot, export it to Cloud Storage, and then import that file as the basis for a custom image for use in DR scenarios Reference:
Choosing a storage option https://cloud.google.com/storage-options/
Based on TerramEarth's current data flow environment (refer to the image in the case study), what are the direct GCP services

NEW QUESTION # 46
Mountkirk Games wants to set up a real-time analytics platform for their new game. The new platform must
meet their technical requirements.
Which combination of Google technologies will meet all of their requirements?

A. Cloud Pub/Sub, Compute Engine, Cloud Storage, and Cloud Dataproc
B. Cloud SQL, Cloud Storage, Cloud Pub/Sub, and Cloud Dataflow
C. Cloud Dataflow, Cloud Storage, Cloud Pub/Sub, and BigQuery
D. Kubernetes Engine, Cloud Pub/Sub, and Cloud SQL
E. Cloud Dataproc, Cloud Pub/Sub, Cloud SQL, and Cloud Dataflow

Answer: C

Explanation:
Explanation/Reference:
Explanation:
Ingest millions of streaming events per second from anywhere in the world with Cloud Pub/Sub, powered
by Google's unique, high-speed private network. Process the streams with Cloud Dataflow to ensure
reliable, exactly-once, low-latency data transformation. Stream the transformed data into BigQuery, the
cloud-native data warehousing service, for immediate analysis via SQL or popular visualization tools.
From scenario: They plan to deploy the game's backend on Google Compute Engine so they can capture
streaming metrics, run intensive analytics.
Requirements for Game Analytics Platform
1. Dynamically scale up or down based on game activity
2. Process incoming data on the fly directly from the game servers
3. Process data that arrives late because of slow mobile networks
4. Allow SQL queries to access at least 10 TB of historical data
5. Process files that are regularly uploaded by users' mobile devices
6. Use only fully managed services
References: https://cloud.google.com/solutions/big-data/stream-analytics/
Testlet 1
Company Overview
Mountkirk Games makes online, session-based, multiplayer games for mobile platforms. They build all of
their games using some server-side integration. Historically, they have used cloud providers to lease
physical servers.
Due to the unexpected popularity of some of their games, they have had problems scaling their global
audience, application servers, MySQL databases, and analytics tools.
Their current model is to write game statistics to files and send them through an ETL tool that loads them
into a centralized MySQL database for reporting.
Solution Concept
Mountkirk Games is building a new game, which they expect to be very popular. They plan to deploy the
game's backend on Google Compute Engine so they can capture streaming metrics, run intensive
analytics, and take advantage of its autoscaling server environment and integrate with a managed NoSQL
database.
Business Requirements
Increase to a global footprint.

Improve uptime - downtime is loss of players.

Increase efficiency of the cloud resources we use.

Reduce latency to all customers.

Technical Requirements
Requirements for Game Backend Platform
Dynamically scale up or down based on game activity.

Connect to a transactional database service to manage user profiles and game state.

Store game activity in a timeseries database service for future analysis.

As the system scales, ensure that data is not lost due to processing backlogs.

Run hardened Linux distro.

Requirements for Game Analytics Platform
Dynamically scale up or down based on game activity

Process incoming data on the fly directly from the game servers

Process data that arrives late because of slow mobile networks

Allow queries to access at least 10 TB of historical data

Process files that are regularly uploaded by users' mobile devices

Executive Statement
Our last successful game did not scale well with our previous cloud provider, resulting in lower user
adoption and affecting the game's reputation. Our investors want more key performance indicators (KPIs)
to evaluate the speed and stability of the game, as well as other metrics that provide deeper insight into
usage patterns so we can adapt the game to target users. Additionally, our current technology stack
cannot provide the scale we need, so we want to replace MySQL and move to an environment that
provides autoscaling, low latency load balancing, and frees us up from managing physical servers.

NEW QUESTION # 47
You have an application that makes HTTP requests to Cloud Storage. Occasionally the requests fail with HTTP status codes of 5xx and 429.
How should you handle these types of errors?

A. Use gRPC instead of HTTP for better performance.
B. Make sure the Cloud Storage bucket is multi-regional for geo-redundancy.
C. Implement retry logic using a truncated exponential backoff strategy.
D. Monitor https://status.cloud.google.com/feed.atom and only make requests if Cloud Storage is not reporting an incident.

Answer: C

Explanation:
Explanation/Reference: https://cloud.google.com/storage/docs/json_api/v1/status-codes

NEW QUESTION # 48
......

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