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Google Cloud Platform Full Course | Google Cloud Platform Tutorial | Cloud Computing | Simplilearn

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The video course on Google Cloud Platform by Simply Learn covers detailed information and training on GCP, including comparisons with other cloud providers, web hosting, machine learning, certifications, and pricing options. The course explores cloud computing concepts, service models, and popular products, emphasizing GCP's features, solutions, and accessibility through the console and command line.

Insights

  • The video course on Google Cloud Platform by Simply Learn covers a wide range of topics, including Azure services, AWS comparison, GCP web hosting, and Google Cloud Machine Learning.
  • Google Cloud Platform offers various featured products and services, such as Compute Engine, Cloud Storage, BigQuery, AI and machine learning products, catering to different organizational needs.
  • Pricing options for Google Cloud include infrastructure modernization solutions, VM migration, SAP Cloud, and high-performance computing, with detailed documentation available for users.
  • Google Cloud's console provides graphical representations of services, billing information, activity history, and access to APIs and services like Compute Engine, BigQuery, and Cloud SQL.
  • Users can access Google Cloud's platform through the console, activate the cloud shell for command-line access, and utilize tools like gcloud for effective service management.
  • Instances on Google Cloud are hosted on Google's infrastructure within specific projects, allowing for public images, custom images, and additional storage space based on requirements.

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Recent questions

  • What is cloud computing and its service models?

    Cloud computing refers to the delivery of services to network users using hardware and software. The service models include Platform as a Service (PaaS), Infrastructure as a Service (IaaS), and Software as a Service (SaaS). PaaS offers a platform for developers to build applications, IaaS provides virtualized computing resources, and SaaS delivers software applications over the internet.

  • How does Google Cloud Platform compare to AWS?

    Google Cloud Platform (GCP) and Amazon Web Services (AWS) are compared in terms of pricing, speed, and capabilities. GCP offers cost-effective solutions, faster performance, and innovative big data, AI, and machine learning services. AWS, on the other hand, provides a wide range of services with over 100 offerings and dominates the cloud market share.

  • What are the key features of Google Cloud Platform?

    Google Cloud Platform offers a variety of services across compute, storage, networking, big data, developer tools, security, IoT, cloud AI, management tools, and data transfer solutions. It provides scalable and efficient solutions for different organizational needs, with features like global load balancing, sole tenant nodes, and serverless compute services.

  • How can one access Google Cloud Platform and manage instances?

    Users can access Google Cloud Platform through the console, cloud shell for command-line access, and cloud SDK on Windows machines. Tools like gcloud are utilized for effective service management. Instances on GCP are hosted on Google's infrastructure, with options for creating, managing, and connecting to instances via SSH keys or external clients like Putty.

  • What are the storage options and database services in Google Cloud Platform?

    Google Cloud Platform offers various storage options like BigTable, Datastore, Firestore, Filestore, SQL-based services, and object storage. Object storage involves storing data in buckets with unique keys, while BigTable is a NoSQL database service for real-time data access. Cloud SQL provides managed relational databases like MySQL, PostgreSQL, and SQL Server.

Related videos

Summary

00:00

"Google Cloud Platform: Comprehensive Training Video"

  • Simply Learn's full course video on Google Cloud Platform covers detailed information about GCP.
  • The video starts with an introduction to GCP, followed by an in-depth look at its concepts.
  • An expert provides quick training on Azure services within the video.
  • A comparison between AWS and GCP is discussed.
  • GCP web hosting is explained in the video.
  • Google Cloud Machine Learning is explored.
  • The video concludes with a discussion on Google Cloud Platform Fundamentals Certification Training.
  • Cloud computing is defined as the use of hardware and software to deliver services to network users.
  • Different cloud computing service models are explained: Platform as a Service, Infrastructure as a Service, and Software as a Service.
  • Google Cloud Platform's popularity, pricing, speed, and big data capabilities are highlighted.

21:01

Google Cloud: Features, Pricing, and Services

  • Google Cloud offers various featured products and services, including solutions for architecture, database, enterprise-level, big data, analysis, gaming, internet of things, and more.
  • Featured products include Compute Engine, Cloud Run, Anthus for migration, Vision AI, Cloud Storage, Cloud SQL, BigQuery, and AI and machine learning products like AutoML Vision AI, Video AI, Text to Speech, and Speech to Text.
  • Compute Engine provides quick starts for Linux machines, guides for working on VM instances, storage, and persistent disks, along with detailed documentation.
  • Pricing options for Google Cloud include infrastructure modernization solutions, VM migration, SAP Cloud, VMware as a service, and high-performance computing (HPC).
  • Google Cloud's platform offers a wide range of services, including quick starts, how-to guides, and in-depth tutorials for working with Compute Engine and other instances.
  • The pricing aspect of Google Cloud includes details on VM instance pricing, networking pricing, sole tenant nodes, GPU-based pricing, disk and image pricing, and different machine types.
  • Google Cloud's console provides a graphical representation of services used, billing information, activity history, and access to APIs and services like Compute Engine, BigQuery, Cloud Data Proc, and Cloud SQL.
  • The navigation menu in Google Cloud's console allows access to various sections like home, marketplace, billing, APIs and services, support, identity access management, getting started, security, and Anthos for migration.
  • Google Cloud's services cover domains like compute, storage, networking, operations, big data, artificial intelligence, and other solutions, offering a wide array of tools and services for different organizational needs.
  • Users can access Google Cloud's platform through the console, activate the cloud shell for command-line access, set up the cloud SDK on Windows machines, and utilize tools like gcloud for managing services effectively.

38:53

Google Cloud Shell: Beginner's Guide to Cloud Services

  • Google Cloud offers a Cloud Shell for working on the platform, beneficial for beginners learning about cloud services.
  • Using the command line, one can type commands like "gcloud create instances" to access the Cloud Console documentation.
  • It is recommended to start with the console for beginners, progressing to the command line as experience grows.
  • Different tasks are easier to perform either from the command line or the console, depending on the complexity.
  • Instances on Google Cloud are hosted on Google's infrastructure and belong to specific projects within the Google Cloud Console.
  • Instances can run public images for Linux or Windows servers, with the option to create or use custom images.
  • Each instance has a boot persistent disk containing the OS, with the ability to add more storage space if required.
  • Projects can have up to five VPC networks, allowing instances in the same network to communicate with each other.
  • Compute Engine instances support launching applications using containers, providing flexibility in deployment methods.
  • SSH keys can be associated with Google accounts for managing access to instances, with the option to connect via gcloud or SSH from the console.

56:05

"SSH Connection and Network Management Tips"

  • To connect via SSH, go to authentication, browse for the ppk file, select the new key, save the session as "my instance one," and open it.
  • If the service host key is not cached, click "yes," and if no authentication method is supported, check if SSH access is enabled.
  • When connecting via Putty, ensure the correct username (ssdu) is used, save the session, and connect by entering the password.
  • Check inbound and outbound rules for network connectivity issues and adjust firewall rules if needed.
  • Access the machine using SSH within the cloud console or an external SSH client like Putty.
  • Verify the connection to the Ubuntu machine, check available space, and confirm successful connection.
  • Review network details to understand and modify firewall rules for specific protocols and IP ranges.
  • Stop, reset, or delete instances as needed, ensuring to clean up to avoid unnecessary billing charges.
  • Learn to connect multiple instances using private files for SSH connections.
  • Explore other options like instance groups, templates, machine images, disks, and snapshots within the Google Cloud console.

01:14:08

Google Cloud: Instance and Storage Management

  • To list instances on Google Cloud, use the command "gcloud compute instances" and add "--help" for assistance or "--format" for output customization.
  • When creating an instance, specify a name like "e1" and view its details, including zone, machine type, IP addresses, etc.
  • Connect to the created instance via SSH and manage it with commands like stop, start, or delete.
  • Utilize the "gcloud compute instances" command to interact with instances, including creating, deleting, and managing them.
  • Explore Google Cloud Storage by creating a bucket through the Cloud Console or Cloud Shell using commands like "gsutil mb" for bucket creation.
  • Choose storage classes like standard, near line, or cold line based on data usage frequency and access needs.
  • Control access to objects within the bucket through permissions settings and view detailed information about the bucket, including region, storage class, and permissions.
  • Upload files to the bucket, manage permissions, and create folders for organizing data within the bucket.
  • Use commands like "gsutil cp" to copy files between local machines and buckets, list bucket contents with "gsutil ls," and navigate through folders and files.
  • Experiment with different options in Google Cloud Storage, such as transferring data from on-premise sources, and utilize tools like "gsutil" for efficient bucket and data management.

01:31:32

"Google Cloud Platform: Efficient, Secure, Innovative Solutions"

  • Cloud storage allows easy data upload and deletion, requiring confirmation of bucket name and deletion through gsutil and a delete command.
  • GCP usage involves creating, uploading, downloading data, creating folders, and managing buckets using gsutil tools via the command line.
  • Cloud computing benefits include on-demand resources, self-service, automatic software integration, and unlimited storage, memory, and computation capacity.
  • Cloud computing traits encompass on-demand self-service, broad network access, resource pooling, rapid elasticity, and measured services.
  • Cloud computing's compelling model attracted organizations due to cost efficiency, freeing up capital, virtualization, and automated services.
  • Major cloud providers include Amazon Web Services, Microsoft Azure, Oracle Cloud, SAP Cloud Solutions, GCP, Salesforce, among others.
  • GCP offers better pricing, speed, performance, live migration of apps, and innovative big data, AI, and machine learning solutions.
  • Google Cloud Platform provides cloud computing services running on Google's infrastructure, offering high productivity, security, flexibility, and cost-effective solutions.
  • GCP services cover compute, storage, networking, big data, developer tools, security, IoT, cloud AI, management tools, and data transfer solutions.
  • Google's infrastructure includes physical data centers, a strong backbone network, global meshed redundant backbone network points of presence, global regions, zones, and global resources.

01:53:25

Google Cloud: Scalable Solutions Across Domains

  • Sole tenant nodes provide access to the same machine types and virtual machine configurations as regular compute instances on Google Cloud.
  • Google Cloud offers various options for instances, including predefined machine types, custom machine types, preemptable VMs, live migration of VMs, persistent disks, local SSDs, and GPU accelerators for computational intensive workloads.
  • Global load balancing is a unique feature of Google Cloud, making it a preferred choice for platform as a service.
  • AWS Lambda by Amazon and Functions by Azure are serverless compute services, while Google Cloud offers Cloud Functions for running code in the cloud easily and reliably.
  • Serverless computing is beneficial for organizations preferring microservices architecture, allowing for dynamic architecture changes without upfront infrastructure planning.
  • Object storage services like Amazon S3, Azure Blob Storage, and Google Cloud Storage offer scalable and efficient data storage solutions.
  • AWS, Azure, and Google Cloud each have distinct advantages, such as enterprise-friendly services, cost-effective solutions, and improved performance, respectively.
  • AWS, Azure, and Google Cloud have limitations and disadvantages, including technical support fees, network connectivity issues, and complex pricing schemas.
  • Domino's Pizza increased monthly revenue by six percent using Google Analytics Premium, Google Tag Manager, and BigQuery to integrate marketing measurement across various devices and connect CRM and digital data for cross-channel marketing analysis.
  • Google Cloud Platform offers a wide range of services across different domains like compute, storage, big data, and machine learning, providing scalable and efficient solutions for various use cases.

02:13:50

"Customizable Machine Configurations for Google Cloud"

  • Different machine configurations are available based on requirements, with options like general purpose and series selection (n1, e2).
  • Machine types can be chosen depending on applications, with default settings of one virtual CPU core and 3.5 gigabytes of RAM.
  • Features like live migration for VMs, preemptable virtual machines, and sole tenant nodes are available for compute options.
  • Boot disk distribution can be selected, such as public images like Ubuntu, with options for standard persistent disk or SSDs.
  • Identity and API access management settings can be customized, allowing HTTP and HTTPS traffic.
  • Connectivity options include SSH access through Google Cloud Console or Cloud Shell, with the ability to provide public and private keys.
  • Management settings include reservations, startup scripts, preemptability for reduced costs, and on-host maintenance for live migration.
  • Sole tenancy nodes offer dedicated physical servers, ideal for specific applications requiring exclusive use.
  • Networking options include default auto subnet setup, with the ability to choose specific IPs at an additional cost.
  • Security measures involve SSH access using public keys, with options for PPK files for external SSH clients like Putty or PEM files for direct SSH connections.

02:30:59

Google Cloud Object Storage and BigTable Overview

  • Changing metadata, region, or adding a startup script is possible from the command line.
  • Compute Engine services are discussed, leading to learning about storage and databases within the Google Cloud Platform.
  • Various storage options like BigTable, Datastore, Firestore, Filestore, SQL-based services, and object storage are available.
  • Object storage in Google Cloud involves storing data with unique keys in buckets, allowing access via URLs.
  • Object versioning creates new versions with changes, offering control access through IAM or ACL.
  • Creating a bucket involves choosing a unique name, location type (region-specific, dual region, or multi-region), and storage class (standard, near line, cold line, archiving).
  • Access control options include fine-grained permissions, encryption, and retention policies for object storage.
  • BigTable, a NoSQL database service, was developed by Google for real-time access to vast amounts of data.
  • BigTable offers scalability, encryption, and access control through IAM roles, with performance metrics based on nodes and storage type.
  • BigTable is suitable for low-latency access with data over one terabyte, not ideal for relational databases or large individual elements.

02:48:56

Comparing Google Cloud Database Services

  • Cloud data store involves paying for monthly storage for reads and writes, while Bigtable requires payment for the cluster when running.
  • Cloud data store is ideal for small data with infrequent access, becoming cost-effective for large amounts of data or big data. Bigtable is cheaper for larger data volumes.
  • Switching to Cloud Firestore in native mode is recommended for more features, especially when the database is empty.
  • Cloud data store offers various features for working with data, though some essential RDBMS features were initially missing.
  • Google introduced Cloud Spanner, a big table-based service, to address the need for RDBMS feature support.
  • Cloud data store allows creating entities with options like default namespace, kind, numeric ID, and adding properties.
  • Detailed documentation is available for learning about Cloud data store in native and data store modes, including feature comparisons, programming languages, regions, and pricing.
  • Cloud Spanner, released in 2017, supports relational schema, strong consistency for SQL-based queries, multi-region deployment, and massive scalability.
  • Cloud SQL is another managed service for fully managed relational MySQL, PostgreSQL, and SQL Server databases, offering features like replication, patch management, and high storage capacity.
  • BigQuery, a data warehouse service, enables processing billions of rows in seconds, real-time analysis of streaming data, and cost-effective data loading and querying.

03:06:51

Cloud Computing Platforms: AWS vs GCP

  • Google Cloud Platform (GCP) offers a real-time managed service for publish-subscribe messaging systems, with Kafka being a popular alternative for such requirements.
  • To access documentation on GCP services, visit cloud.google.com and explore the document section, featuring various products, domains, and services.
  • GCP provides services in compute, storage, databases, networking, big data, developer tools, cloud AI, identity and security, IoT management, and API platforms.
  • Users can create a free account to experiment with GCP services, connecting to, managing, and benefiting from the modernized infrastructure for diverse use cases.
  • AWS and GCP engage in a debate over the best cloud computing platform, comparing their origins, features, performance, pricing, market share, and instance configurations.
  • AWS, established in 2004, dominates the cloud computing market with over 100 services, while GCP, launched in 2011, offers cost-effective instances and multi-regional cloud storage.
  • In the fourth quarter of 2017, AWS held 47% of the cloud market share, surpassing competitors like Microsoft Azure, Google Cloud Platform, and IBM Software.
  • AWS and GCP differ in pricing, with GCP offering cheaper compute instances and cloud storage, resulting in a 25% annual cost reduction compared to AWS.
  • AWS provides access to services for a year with usage limits, while GCP offers $300 in credit over 12 months for all cloud platform products, with an always-free version available.
  • Instance configurations vary between AWS and GCP, with AWS offering up to 128 CPUs and 4 TB of RAM, while GCP provides up to 160 CPUs and 3.75 TB of RAM, along with preemptable instances at a fixed price.

03:24:17

"WordPress, LAMP, GCP: Website Hosting Essentials"

  • WordPress is a free and open-source content management system used to create websites and blogs.
  • LAMP stack consists of Linux, Apache, MySQL, and PHP, used for hosting websites and web applications.
  • Google Cloud Platform (GCP) allows users to build their own websites or web applications directly on Compute Engine.
  • Lush, a global cosmetics retailer, faced website crashes due to high traffic on Boxing Day.
  • Moving Lush's website to GCP allowed for rapid VM deployment and scalability during peak times.
  • GCP's auto-scaling feature improved availability during peak loads and reduced infrastructure hosting costs by 40%.
  • Hosting a website on GCP involves setting up a VM instance, choosing configurations, and managing firewall rules.
  • Installing Apache on a GCP instance allows for hosting web applications, with firewall rules customizable for incoming and outgoing traffic.
  • Accessing the hosted website involves using the public IP address of the instance and customizing the HTML page.
  • Simply Learn offers a course on Google Cloud Platform fundamentals, providing training on data processing capabilities and machine learning with GCP.
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