Master Google Cloud tools with a structured learning path
Well-organised curriculum featuring four core modules
Get prepared for Google Cloud Certified Associate Cloud Engineer exam
Learn from instructors with extensive industry experience
Earn the globally recognised GCP - Associate Cloud Engineer certification
Gain experience through hands-on labs and collaborative projects
Flexible learning modes that adapt to your personal schedule
What you will learn:
Upcoming sessions
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
Successful completion of the training will help you to:
1
Gain expertise in IAM roles to manage secure access in Google Cloud environments
2
Configure cloud networking with VPN, subnets and routing for secure communication
3
Deploy scalable containerised apps using GKE and Kubernetes CLI efficiently
4
Use Cloud Run to implement serverless & event-driven application solutions
5
Build and manage multi-region storage solutions with Cloud Storage and BigQuery tools
6
Automate Infrastructure as Code (IaC) management using Terraform scripts and Helm charts
There are no mandatory requirements to enrol for the Google Cloud Certified Associate Cloud Engineer Course. However, it is strongly recommended that candidates should have the following:
Overall ratings by our students
Our Google Cloud Certified – Associate Cloud Engineer Course trains you to develop the skills to deploy and manage the Google Cloud Platform (GCP). We cover important aspects of GCP like storage, compute, networking and security. This course serves as a foundational certification training for anyone aspiring to build a career in cloud engineering or IT infrastructure management using Google Cloud services.
There are no specific eligibility criteria for this Google Cloud Certified Associate Cloud Engineer Course. However, we strongly recommend that candidates have the following:
After completing this course, you can pursue in-demand job roles in Bahrain and globally. Some of these job roles are listed below:
With our Google Cloud Certified – Associate Cloud Engineer Training, students will master the important tools for deployment and management of cloud solutions, optimising cloud resources and ensuring security. Some of these tools are listed below:
Yes, our course specifically prepares you for the official Associate Cloud Engineer certification exam. Our course includes the following features that help you get fully prepared for the exam:
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