
Kick off your Google associate cloud engineer prep with an overview of Google Cloud, its benefits, how it differs from other providers, and practical demos of core services.
Discover how cloud benefits like flexibility, on-demand scaling, and secure storage enable quick application deployment, remote access, and cost efficiency while choosing from IaaS to hybrid solutions.
Explore the Google Cloud Platform basics, including creating a Google Cloud account, logging into the Cloud Console, and understanding regions, zones, and ways to interact with GCP.
Learn to create a Google cloud account with a valid email on cloud dot google dot com, and use the $300 free trial while providing tax, name, and address.
Explore how to interact with Google Cloud Platform via Cloud Shell, a web-based command line launched from Cloud Console, featuring persistent storage, vm sessions, and the bq command for BigQuery.
Explore Google Cloud services, including compute, storage, big data, identity and security, and machine learning APIs, with a focus on monitoring, alerting, and hybrid deployment.
Install and initialize the Google Cloud SDK on Windows via the command line, log in, select a default project, and run commands from the prompt to interact with Google Cloud.
Configure gcloud by setting up the cloud SDK, choosing between existing or new configurations, selecting your Google account, and assigning a default project and account for global use.
Learn to list cloud resources with gcloud, filter images using boolean expressions, and understand listing operations. Apply sorting by name and identify unique identifiers for efficient resource discovery.
Describe resources via gcloud and learn how to display event information using cloud commands, building practical skills for the latest Google Associate Cloud Engineer Certification.
Learn how to enable and disable APIs in GCP, view default APIs enabled for new projects, and use the API library to search, enable, and monitor cloud services.
Explore how Google Cloud uses projects as resource containers to manage resources and costs, including creating projects, linking to a billing account, enabling APIs, and project lifecycle.
Learn who pays for cloud resources by managing billing accounts, creating new accounts, and using the billing account overview to track costs by project, service, or region.
Learn how billing account management links a project to a billing account, with multiple projects per account and a single invoice. Create and manage accounts, payment profiles, and access controls.
configure the billing export to automatically send billing data to BigQuery for analysis, and learn to set up datasets in a selected project and save the configuration.
Introduce identity and access management in the cloud, explain permissions, roles, and role types, and show how to assign roles and policies to identities to enforce access control.
Explore Google Cloud identities and learn how to grant access using Google accounts, service accounts, groups, and nested groups, including all authenticated users and all users.
Learn how permissions define granular operations on Google Cloud resources, how roles group those permissions into resource roles, and how primitive and predefined roles control access and billing.
Understand billing accounts and invoices, including charges by credit card or direct debit, and the roles of creator, administrator, and user for linking projects and billing exports.
Learn to create and assign custom roles in Google Cloud IAM, tailor permissions to enforce least privilege, and manage predefined versus custom roles for each member.
Master policy related commands to view deep level policies, set project policies, manage cloud storage roles, and apply granular, atomic policy binding and removal one change at a time.
Demonstrates how to enable or disable audit logs for APIs, view admin activity, and filter logs in cloud logging and the GCB dashboard by activity type or resource.
Understand what an image is, its bootloader and operating system, and how it loads onto Google Compute Engine, including public and custom images and starting instances from a chosen image.
Create a custom image from a disk in Google Cloud, name it, choose regions, add labels, and select encryption keys, then click create to reuse the image for new instances.
Learn to configure VM networking in Google Cloud, including firewall rules to restrict access, manage traffic, and assign internal and external IPs with multiple interfaces.
Create a Google Cloud compute engine VM, install and configure the Apache web server, deploy a web app, and access it from a local browser via a public IP.
Demonstrates manual snapshot creation, including naming, description, sources, and region options; shows that cloud-stored snapshots are accessible within the same project and can create a disk in any region.
Create and schedule automated network backups by configuring a snapshot with name, description, region (asia), storage bucket, daily timing, and rotation; attach the schedule for regular backups.
Explore startup scripts on Google Compute Engine, automating initialization with Bash or Python, using Cloud Storage and metadata; learn about on-host maintenance, pre-emptible VMs, live migration, and automatic restart.
Learn to use gcloud compute commands to create and customize compute instances, including selecting default machine types, images, and delete options, and to list, filter, and manage instances.
Decide the zone for a vm instance by evaluating project-level goals and configuration. Learn to set region preferences and priority rules when information is missing.
Learn essential gcloud compute commands to manage cloud instances, including listing, starting, stopping, deleting, and describing instances, and verifying their status in a project.
Use an instance template in Google Cloud to create identical virtual machines with the same memory, networking, and security settings; it's a global resource that does not define location.
Create a boot VM custom image containing software and revisions to speed up deployment of web servers. Then build an instance template from this image to launch multiple VMs efficiently.
Learn how to manage instance templates via the CLI, creating and loading instances from templates, and controlling deletion operations to ensure consistent, scalable deployments.
Manage identical instances from a template as a single group to enable auto scaling, auto healing, rolling updates, and multi-zone load balancing; unmanaged groups host heterogeneous instances without these features.
Learn to create and manage a managed instance group in Google Cloud, configure templates, autoscaling policies based on CPU or load, set health checks and region or zone deployment.
Explore rolling updates in a managed instance group, progressively applying a new template across instances, testing on a subset before rollout, configuring maximum surge, maximum unavailable, and minimum waiting time.
Demonstrates performing a rolling update in a Google Cloud managed instance group, configuring min/max instances, testing new models, and choosing opportunistic or proactive rollout for seamless VM replacement.
Learn how to manage instance groups with gcloud, create and list groups, describe instances, delete groups, and configure autoscaling with a maximum number of replicas.
Use gcloud commands to manage a managed instance group, update policies and auto healing, modify the instance template, and apply rolling updates to replace or adjust the group's instances.
Learn to perform rolling updates on instance groups using restart and replace actions, set maximum unavailable and replacement methods, and apply a new template to update instances gradually.
Explore categorization of Google Cloud load balancers, including global vs regional, external vs internal, and SSL termination, with guidance on choosing near to users and routing external and internal traffic.
Explore Google Cloud network load balancer, an external regional software-defined managed service that balances internet traffic, supports UDP, and is a pass-through load balancer that does not terminate SSL.
Explain how external global load balancers direct internet traffic to a three-tier web app, then internal regional and GCP or UDP load balancers distribute traffic to web servers and storage.
Explore the load balancer data model, defining forwarding rules, target proxy, and back-end services, with content-based, host, and URL routing across multiple microservices and static storage backends.
Decide which Google Cloud load balancer to use by weighing external vs internal options, regional vs global scope, and features like SSL proxy and IPv6 support.
Learn how to set up an external Google Cloud load balancer that distributes internet traffic across two instances, using a backend service, health checks, and a static IP.
Compare App Engine with Compute Engine, highlighting how App Engine offers quick deployment and automated scaling with less customization, while Compute Engine provides maximum infrastructure flexibility.
Discover App Engine features in the flexible environment, run any language via Docker, auto scale, test and release across development to production, with cloud monitoring, logging, debugging, and security tools.
Explore how App Engine components organize a Google Cloud app, with an application containing services and instances, supporting multiple versions and traffic routing, and offering automatic, basic, or manual scaling.
Explore microservice architecture by comparing monolithic and multi-service deployments, illustrating isolated services with independent versions, and using shared cloud storage, databases, and mail services for scalability and testing.
Learn how to create an App Engine application within a project, choosing a nearest location, and deploying a service, with one app per project and no deletion after creation.
Compare flexible and standard environments for the Google associate cloud engineer certification, highlighting sandbox runtime support for languages like Java, Python, Node.js, and Go, and auto scaling options.
Explore the flexible environment in Google Cloud and how it differs from standard. Learn to deploy with Docker, customize via Dockerfile, manage scaling, and define memory and vcpu.
Learn how to deploy a Python service in the flexible environment using Docker images and YAML configurations, with manual scaling and CPU/memory settings, and compare to standard deployments.
Learn to deploy and manage App Engine applications with gcloud app commands, inspect services, control traffic across versions, and promote or pause deployments in the standard environment.
Explore how App Engine scaling modes manage instances—from automatic scaling with min/max instances and CPU utilization to basic and manual scaling, including maximum concurrent requests.
Learn to route requests in App Engine using rules, traffic shifting, and load balancer configurations, including default and service-specific routing and YAML-defined rules.
Explore task scheduling in app engine by defining time intervals and invoking a ctp endpoint to automate jobs, such as daily reports or data updates every 10 minutes.
Explore Google Kubernetes Engine (GKE) as a managed container orchestration platform for deploying, managing, and scaling containerized apps on Google Cloud, with automated management and health monitoring.
Nodes and the control plane manage cluster lifecycle. A port runs one or more containers, including Docker containers, with logging and network features, coordinated by the API server.
Learn how to attach labels as key-value pairs to objects, at creation or later, manage multiple labels per object, and use label selectors to identify and query objects.
Deploy with a declarative YAML approach in Kubernetes, describing the desired state, using replicas and a deployment controller to ensure stateless pods, ports, and automatic recovery.
Create zonal cluster
gcloud container clusters create first-cluster --zone asia-south1-a
Connect to a GKE cluster using the CLI to prepare deployment. Obtain credentials, authorize access, and select the target cluster within one project as part of the connection process.
Create a deployment and a service with kubectl, verify status and logs, and expose the app to the internet with a load balancer endpoint.
Learn to scale deployments and clusters using the command line interface, configure horizontal pod autoscaling based on cpu utilization, and manage load balancing across multiple pods and node pools.
Learn to delete unused gke cluster resources, including deployments and services, using precise commands, verify deletions, and clean up clusters to prevent resource bloat.
Create and deploy a Google Cloud function using a studio trigger, configure region, memory, timeout, access, and environment variables, and test with a payload.
Learn to create a Cloud Run service and its revision, deploy a public Google Cloud container image, enable the Cloud Run API, and expose an internet endpoint.
Discover how public IP addresses and private IP addresses differ. Private IPs stay inside the local network, while public IPs reach the internet.
Explore Google Cloud VPC features, including subnet IP addressing, internal and external IPs, firewall rules for ingress and egress, VPC networks, and Cloud VPN or Cloud Interconnect with Cloud Logging.
Explore the default VPC network in Google Cloud, including its automatically created subnets across regions, default firewall rules that allow internal and internet traffic, and the global logging view.
Explore how firewall rules act as the first line of defense, controlling inbound and outbound traffic for virtual networks and virtual machines, using targets like network tags and service accounts.
Learn to define and create firewall rules in GCP, specifying ingress or egress traffic, targets, service accounts, protocols, priorities, and enabling logs.
Learn how routing in Google Cloud directs network traffic between virtual machines using destinations and next hops defined in static and custom routes.
Explore hybrid networking options like cloud interconnect, cloud VPN, and dedicated interconnect for on-premises and cloud resources. Assess latency, availability, and budgets to plan phased cloud migration.
Explore cloud DNS, a global, high-availability domain name system that resolves domain names to IP addresses, supports public and private zones, and enables A records with propagation for low latency.
learn how Cloud CDN uses globally distributed edge locations to cache static content and serve it from the nearest edge, reducing latency and offloading from origin.
Create and organize data in cloud storage using globally unique buckets with labels. Manage objects through lifecycle rules, metadata, and versioning while treating them as immutable binaries.
Explore cloud storage classes for buckets, compare availability and cost across standard and nearline options, and learn to choose the right storage class for object durability.
Create and enforce bucket object lifecycle rules to automatically downgrade storage class, move older data to nearline or archive storage, and delete items after seven years.
Learn how to protect data with bucket level uniform access control or fine-grained object level access control, assign roles to members, and avoid misconfigurations that expose personally identifiable information.
Grant public access for all users or all authenticated users from private cloud storage objects, and host static web content with a load balancer and a DNS-backed domain.
Learn how signed URLs grant time-limited, credential-free access to bucket objects for anonymous or third-party users, with expiry control and security considerations.
Learn how object versioning in cloud storage protects data from being overwritten or deleted, manage versions across buckets, and use commands to enable, view, and copy object versions.
This course will help you in becoming a Google Cloud Associate Engineer. It will help in learning what are the various cloud offerings in Google cloud platform and how to use those offerings.
This is an ideal course to learn about Google cloud for all developers and aspiring cloud engineers.
It will help in boosting your career.
This course covers
1. What is Cloud
2. Why use Google Cloud
3. How to use IAM in Google cloud and ensure security in Cloud
4 What are the compute offerings in GCP and how to use those compute offerings. It also covers where to use which compute offerings
5. What are the data storage services offered in Google Cloud and what are the best practices to store and analyze data in Google Cloud.
6. How to distribute request traffic among application backends using various load balancer options in GCP and how to decide which load balancer is best suitable for a particular use case.
7. How to migrate existing Bigdata applications in GCP.
8. How to set up a new Bigdata ETL pipeline in Google Cloud by using Dataflow
9. How to capture and analyze logs in GCP
10. How to monitor applications in Google Cloud
11. How to do application tracing to find performance bottlenecks in Google Cloud
12. How to set up CI/CD pipeline in Google Cloud
13. How to use IAC in Google cloud.