Professional Cloud Architect Certification

Professional Cloud Architect Exam Prep Workshop

DreamsPlus offers an in-depth exam preparation workshop in Singapore for Cloud Engineers aiming to pass the Google Professional Cloud Architect certification exam. Led by industry experts, this workshop will cover the latest cloud architecture concepts, best practices, and strategies to equip you with the skills needed to excel in the exam and advance your career in cloud technology. Gain hands-on experience and insights into cloud infrastructure, security, and solutions design to ensure you pass with confidence.

Workshop Overview:

Syllabus 

Section 1: Setting up a cloud solution environment (~20% of the exam)

1.1 Setting up cloud projects and accounts. Considerations include:

• Establishing a hierarchy of resources
• Implementing resource hierarchy policies inside the organization
• Assigning IAM roles to participants in a project
• Handling groups and users in Cloud Identity (both automatically and manually)
• Making APIs available for projects
• Provisioning and configuring items within the operations suite of Google Cloud
• Determining quotas and asking for raises

1.2 Managing billing configuration. Considerations include:

• Establishing one or more accounts for billing
• Connecting a project to an invoice
• Setting up notifications and billing budgets
• Establishing exports for billing

Section 2: Planning and configuring a cloud solution (~17.5% of the exam)

2.1 Planning and configuring compute resources. Considerations include:

• Choosing the right compute options (such as Compute Engine, Google Kubernetes Engine, Cloud Run, and Cloud Functions) for a given workload
• Using Spot VM instances and custom machine types as necessary

2.2 Planning and configuring data storage options. Considerations include:

• Selecting a product (such as BigQuery, Firestore, Spanner, Cloud SQL, etc.)
• Selecting storage options (such as Standard, Nearline, Coldline, Archive, Standard, Regional, and zonal persistent disks)

2.3 Planning and configuring network resources. Considerations include:

• Network Service Tiers 
• Availability of resource locations in a network 
• Load balancing 

Section 3: Deploying and implementing a cloud solution (~25% of the exam)

3.1 Deploying and implementing compute engine resources. Considerations include:

• Launching a compute instance (e.g., assign disks, availability policy, SSH keys)
• Using an instance template to create an autoscaled managed instance group
• Setting Up OS Login
• Setting up VM Manager 

3.2 Deploying and implementing Google Kubernetes Engine resources. Considerations include:

• Installing and configuring the command line interface (CLI) for Kubernetes (kubectl)
• Setting up separate Google Kubernetes Engine cluster configurations (Autopilot, regional clusters, private clusters, GKE Enterprise, etc.)
• Installing a Google Kubernetes Engine containerized program 

3.3 Deploying and implementing Cloud Run and Cloud Functions resources. Considerations include:

• Launching an application
• Setting up an application to receive events from Google Cloud (like Eventarc, Pub/Sub events, and Cloud Storage object change notification events)
•  Determining where to use Cloud Run (fully managed), Cloud Run for Anthos, or Cloud Functions to deploy an application

3.4 Deploying and implementing data solutions. Considerations include:

• Setting up data products (such as AlloyDB, Cloud SQL, Firestore, BigQuery, Spanner, Pub/Sub, Dataflow, and Cloud Storage)
• Loading data (using Storage Transfer Service, Cloud Storage, command line upload, etc.) 

3.5 Deploying and implementing networking resources. Considerations include:

• Establishing a virtual private cloud (VPC) with subnets (such as a shared or custom mode VPC) 
• Developing firewall rules and policies for ingress and egress (such as IP subnets, network tags, and service accounts)
• Peering over external networks (such as VPC Network Peering and Cloud VPN) 

3.6 Implementing resources through infrastructure as code. Considerations include:

• Infrastructure as code tooling, such as Terraform, Helm, Config Connector, and Cloud Foundation Toolkit 

Section 4: Ensuring successful operation of a cloud solution (~20% of the exam)

4.1 Managing Compute Engine resources. Considerations include:

• Remotely connecting to the instance
• Viewing current running VM inventory (e.g., instance IDs, details)
• Working with snapshots (e.g., create a snapshot from a VM, view snapshots, delete a snapshot, schedule a snapshot)
• Working with images (e.g., create an image from a VM or a snapshot, view images, delete an image)

4.2 Managing Google Kubernetes Engine resources. Considerations include:

• Examining the cluster inventory that is currently in use (such as nodes, Pods, and Services)
• Setting up Google Kubernetes Engine for Artifact Registry Access
• Managing node pools, such as adding, modifying, or eliminating one
• Working with Statefulsets, Pods, Services, and other Kubernetes resources
• Handling configurations for both horizontal and vertical autoscaling 

4.3 Managing Cloud Run resources. Considerations include:

• Updating application traffic splitting parameters 
• Implementing new application versions 
• Configuring scaling parameters for autoscaling instances 

4.4 Managing storage and database solutions. Considerations include:

• Organizing and safeguarding items within Cloud Storage containers
• Establishing policies for object lifecycle management in Cloud Storage buckets
• Running queries on data instances (like Cloud SQL, BigQuery, Spanner, Firestore, and AlloyDB) in order to retrieve data
• Calculating the price of data storage resources 
• Backing up and restoring database instances (such as Firestore and Cloud SQL)
• Examining the status of the job (such as Dataflow, BigQuery) 

4.5 Managing networking resources. Considerations include:

• Extending an existing VPC with a subnet
• Adding more IP addresses to a subnet
• Setting aside static IP addresses, either internal or external
• Utilizing cloud NAT and cloud DNS 

4.6 Monitoring and logging. Considerations include:

• Generating alerts for Cloud Monitoring using resource metrics

• Generating and consuming custom metrics for Cloud Monitoring (from logs or applications, for example)
• Exporting logs to third-party platforms (like BigQuery on-premises)
• Setting up log routers, log analytics, and log buckets
• Using Cloud Logging to view and filter logs
• Accessing particular log message information in Cloud Logging
• Looking into an application problem with cloud diagnostics
• Checking the status of Google Cloud
• Setting up and implementing Ops Agent
• Prometheus Managed Service Deployment
• Setting up audit logs 

Section 5: Configuring access and security (~17.5% of the exam)

5.1 Managing Identity and Access Management (IAM). Considerations include:

• Seeing and generating policies for IAM
• controlling the different role kinds and creating distinctive IAM roles (basic, predefined, custom, etc.)

5.2 Managing service accounts. Considerations include:

• Establishing service accounts 
• Utilizing service accounts in IAM policies with minimal authorization 
• Assigning service accounts to resources 
• Managing an account’s IAM 
• Handling service account impersonation 
• Creating and maintaining temporary service account credentials