Google Cloud Certified – Associate Cloud Engineer Course

Creating a resource hierarchy

Applying organizational policies to the resource hierarchy

Granting members Identity and Access Management (IAM) roles within a project

Managing users and groups in Cloud Identity (manually and automated)

Enabling APIs within projects

Provisioning and Setting up products in Google Cloud Observability

Assessing quotas and requesting increases

Setting up standalone organizations

Setting up cloud networking

Confirming availability of products in geographical locations (e.g., regional, global)

Configuring Cloud Asset Inventory and using Gemini Cloud Assist to analyze resources

Creating one or more billing accounts

Linking projects to a billing account

Establishing billing budgets and alerts

Setting up billing exports

Selecting appropriate compute choices for a given workload (e.g., Compute Engine, Google Kubernetes Engine [GKE], Cloud Run, Cloud Run functions, Knative serving)

Launching a compute instance (e.g., availability policy, SSH keys)

Choosing the appropriate storage for Compute Engine (e.g., zonal Persistent Disk, regional Persistent Disk, Google Cloud Hyperdisk)

Creating an autoscaled managed instance group by using an instance template

Configuring OS Login

Configuring VM Manager

Using Spot VM instances and custom machine types

Installing and Configuring the command-line interface (CLI) for Kubernetes (kubectl)

Deploying a GKE cluster with different configurations (e.g., GKE Autopilot, regional clusters, private clusters)

Deploying a containerized application to GKE

Deploying an application to serverless compute platforms, including for the processing of Google Cloud events (e.g., Pub/Sub events, Cloud Storage object change notification events, Eventarc)

Choosing and deploying data products (e.g., Cloud SQL, BigQuery, Firestore, Spanner, Bigtable, AlloyDB, Dataow, Pub/Sub, Google Cloud Managed Service for Apache Kaa, Memorystore)

Choosing and deploying storage products (e.g., Cloud Storage, Filestore, Google Cloud NetApp Volumes) and Cloud Storage options (e.g., Standard, Nearline, Coldline, Archive)

Loading data (e.g., command-line upload, load data from Cloud Storage, Storage Transfer Service)

Maintaining multi-region redundancy across data solutions

Creating a VPC with subnets (e.g., custom mode VPC, Shared VPC)

Creating and applying Cloud Next Generation Firewall (Cloud NGFW) policies with ingress and egress rules and attributes (e.g., action, source, destination, targets, protocols, ports)

Using Tags (e.g., secure Tags) and service accounts in Cloud NGFW policy rules

Establishing network connectivity (e.g., Cloud VPN, VPC Network Peering, Cloud Interconnect)

Choosing and deploying load balancers

Differentiating Network Service Tiers

Infrastructure as code tooling (e.g., Fabric FAST, Cong Connector, Terraform, Helm)

Planning and executing infrastructure as code deployments, including versioning, state management and updates

Remotely connecting to a Compute Engine instance

Viewing current running Compute Engine instances

Working with snapshots and images (e.g., create, view, and delete images or snapshots; schedule a snapshot)

Viewing current running GKE cluster inventory (e.g., nodes, Pods, Services)

Configuring GKE to access Artifact Registry

Working with GKE node pools (e.g., add, edit, or remove a node pool; autoscaling node pool)

Working with Kubernetes resources (e.g., Pods, Services, StatefulSets)

Managing horizontal and vertical Pod autoscaling configurations

Managing GKE Autopilot Pod resource requests

Deploying new versions of a Cloud Run application

Adjusting application traffic splitting parameters (e.g., Cloud Run, Cloud Run functions, GKE)

Configuring autoscaling for a Cloud Run application

Managing and securing objects in Cloud Storage buckets

Setting object lifecycle management policies for Cloud Storage buckets

Executing queries to retrieve data from data instances (e.g., Cloud SQL, BigQuery, Bigtable, Spanner, Firestore, AlloyDB)

Estimating costs of data storage resources

Backing up and restoring database instances (e.g., Cloud SQL, Firestore, Spanner, AlloyDB, Bigtable)

Reviewing job status (e.g., Dataow, BigQuery)

Using Database Center to manage the Google Cloud database fleet

Adding a subnet to an existing VPC

Expanding a subnet to have more IP addresses

Reserving static external or internal IP addresses

Adding custom static routes in a VPC

Working with Cloud DNS and Cloud NAT

Creating Cloud Monitoring alerts based on resource metrics

Creating and ingesting Cloud Monitoring custom metrics (e.g., from applications or logs)

Exporting logs to external systems (e.g., on-premises, BigQuery)

Configuring log buckets, log analytics and log routers

Viewing and ltering logs in Cloud Logging

Viewing specic log message details in Cloud Logging

Using cloud diagnostics to research an application issue (e.g., Cloud Trace, Cloud Profiler, Query Insights, index advisor)

Viewing the Personalized Service Health dashboard

Configuring and deploying Ops Agent

Deploying Google Cloud Managed Service for Prometheus

Configuring audit logs

Using Gemini Cloud Assist for Cloud Monitoring

Using Active Assist to optimise resource utilisation

Viewing and creating IAM policies

Managing the various role types and defining custom IAM roles (e.g., basic, predefined, custom)

Creating and developing service accounts

Using service accounts in IAM policies with minimum permissions

Assigning service accounts to resources

Managing IAM permissions of a service account

Managing service account impersonation

Creating and managing short-lived service account credentials

Using a Google Cloud service account with a GKE application