This video provides a complete study course for the Google Cloud Associate Cloud Engineer certification, including lectures, practice exams, and learning support. The certification exam is two hours long and costs $125. The course is recommended for students with over six months of experience with Google Cloud.
00:00:00 This YouTube video provides a complete study course for the Google Cloud Associate Cloud Engineer certification. The course consists of lecture content, followed by practice exams and learning support, and culminates with the certification exam. The instructor, Anthony Tavelos, has 18 years of industry experience and is a certified cloud engineer. He has published multiple cloud courses and is a big fan of the cartoon Looney Tunes.
00:05:00 The video demonstrates how to install git on a Windows computer. After installing git, it is used to clone a repository from the internet.
00:10:00 The video demonstrates how to install and use Git on a Windows and Linux computer, and how to clone a GitHub repository.
00:15:00 This online course covers the Google Cloud Associate Cloud Engineer certification. It is recommended that students have over six months of experience with Google Cloud before taking the certification exam. The exam is two hours long and costs $125.
00:20:00 The Google Cloud Associate Cloud Engineer Course is a good way to get started in the Google Cloud Platform professional level. The course is two hours long, and consists of 50 questions. The exams are harder than the Associate Cloud Engineer exams, and require more knowledge of Google Cloud.
00:25:00 In this video, the instructor discusses a fictitious organization called Bow Tie Ink, which manufactures and sells bow ties. The instructor explains how the company's retail locations tie in with the scenario. He also discusses how the company's wholesale sales tie in with the scenario.
00:30:00 The company, Bow Tie Inc., is a global fashion retailer with over 300 employees in sales and marketing. The company has a retail location in Montreal, Canada, as well as two offices in London, England, and Los Angeles, California. The company is experiencing technical debt and is considering transitioning to Google Cloud. Management is weary of the costs and benefits of transitioning, but they are open to suggestions. The company's current infrastructure includes on-premise hardware and outdated software.
00:35:00 The video discusses some of the challenges that a small business faces when it comes to its infrastructure. One of the biggest challenges is a lag in performance between store locations and the head office due to a poor VPN connection. Additionally, backups are taking a lot of time and bandwidth, and the business is struggling to keep up with the demand due to its limited scalability. Cloud computing can help ease these challenges by providing a reliable connection between all locations, efficient backups, and the ability to scale up quickly when needed.
00:40:00 The Google Cloud Associate Cloud Engineer Course covers key topics in cloud computing, including understanding cloud-based scenarios and how to resolve common issues. The practice exams included in the course help you better prepare for the final exam.
00:45:00 The video explains the five essential characteristics of cloud computing, which are on-demand self-service, broad network access, resource pooling, and rapid provisioning.
00:50:00 This video explains the four common cloud deployment models: public cloud, multi-cloud, private cloud, and hybrid cloud. These models are distinguished by their mode of deployment: public cloud is accessible over the public internet, private cloud is accessible only by its owner, multi-cloud allows for multiple clouds to be connected and used together, and hybrid cloud combines elements of multiple cloud deployment models. Knowing the different models can help you choose the best cloud for your specific needs.
00:55:00 This video provides a comprehensive overview of different cloud deployment models, including private, hybrid, and public cloud. The video emphasizes the importance of distinguishing between hybrid and true hybrid cloud, noting that using on-premises infrastructure connected to public cloud is not considered hybrid cloud.
This video provides a brief overview of the Google Cloud Platform, including the different compute options available and the resource hierarchy. It also covers the basics of cloud storage and how to sign up for a free trial.
01:00:00 This YouTube video provides a brief overview of the cloud service models available on Google Cloud Platform, including infrastructure as a service, platform as a service, and pizza as a service. The video then goes on to explain the concept of the pizza as a service.
01:05:00 In this video, Google Cloud associate instructor Justin Cooke discusses the company's global infrastructure and how it is connected. He also discusses the company's geographic distribution and its dedication to customer satisfaction.
01:10:00 Google Cloud Associate Cloud Engineer Course covers the basics of the company's global infrastructure including its regions, zones, and multi-regions. The course also discusses the benefits of using zones for improved performance.
01:15:00 This video provides an overview of the various compute options available in Google Cloud, starting with Infrastructure as a Service (IaaS) and moving on to Compute Engine and Google Kubernetes Engine. Several other platform as a service options are also covered, including App Engine.
01:20:00 In this video, Google Cloud instructor discusses the different compute service options that are available on the Google Cloud platform, including Cloud Storage, Cloud Functions, and Cloud Run.
01:25:00 The Google Cloud Associate Cloud Engineer Course covers the basics of cloud storage, from durability to availability. Cloud storage is versatile, with options for standard storage, low-cost archival storage, and file store.
01:30:00 This tutorial provides a brief overview of the various Google Cloud storage and database options, as well as their respective networking features. Next, firewall and routing rules are covered, followed by a discussion of virtual private cloud (VPC) and the default networks it provides. Finally, the basics of Google Cloud Firewall are covered.
01:35:00 In this video, the instructor discusses the concept of resources and how they are organized in Google Cloud. He also discusses permissions, which are inherited through the resource hierarchy. Finally, he provides an example of a resource.
01:40:00 The Google Cloud Associate Cloud Engineer Course covers the hierarchy of Google Cloud resources, which can help organizations manage permissions and access control. The course also covers the domain, organization, projects, and resources layers of the Google Cloud resource hierarchy.
01:45:00 This video covers the Google Cloud resource hierarchy and the differences between the free and always free tiers. The free tier is for personal use, and the always free tier is for regular use of certain Google Cloud resources without charging for each use.
01:50:00 This instructional video demonstrates how to sign up for a free trial of Google Cloud and secure the account using two-step verification.
01:55:00 In this lesson, the different ways to secure and protect your Google account are discussed, as well as the different options available for two-step verification. A scenario is provided in which a trouble-causing manager logs into an account belonging to another user, and then goes on to make malicious changes to that user's reputation. Two-step verification is described, as well as the option of using backup codes in case of a lost or stolen phone. Finally, the importance of using a security key is stressed, and how it can be used to protect against phishing attacks.
The Google Cloud Associate Cloud Engineer Course covers the basics of billing and payments, as well as managing users and permissions. After completing the course, students are prepared to create and manage their own billing accounts. The course also covers how to purchase committed use discounts for Google Cloud services, and how to create a budget and set up budget alerts.
02:00:00 In this video, Google Cloud Associate Tony demonstrates how to enable two-step verification on an account. First, he shows how to find the security menu and then explains how to enable two-step verification. Next, he demonstrates how to log in using his phone and password. Finally, he shows how to verify that the login was successful by sending a Google prompt to his phone.
02:05:00 This lesson covers the Google Cloud Console, two-step verification, and securing your account. The instructor demonstrates how to customize the cards on the main page, and how to find the Google Cloud Platform services and resources. He then demonstrates how to find specific information using the search bar.
02:10:00 In this video, the instructor covers the basics of billing in Google Cloud, and provides a brief overview of the different resources involved. Lessons will follow up on the concepts discussed in this video, and will show how to create, edit, and delete a cloud billing account.
02:15:00 The Google Cloud Associate Cloud Engineer Course covers the basics of billing and payments, as well as managing users and permissions. After completing the course, students are prepared to create and manage their own billing accounts.
02:20:00 The Google Cloud Associate Cloud Engineer Course covers billing and managing billing accounts. The course introduces the various billing roles and their associated permissions. After creating a new billing account, the course demonstrates how to switch projects to and from the account.
02:25:00 In this video, the instructor covers how to purchase committed use discounts for Google Cloud services. He covers the two available commitment types, spend-based and resource-based, and explains how the commitment fee is billed monthly. He also covers how to use Google Cloud resources.
02:30:00 Google Cloud offers spend-based commitments that give you a 25% discount on on-demand pricing for a one-year commitment and up to a 52% discount off of on-demand pricing for a three-year commitment. These commitments apply to resources like cloud sql database instances and google cloud vmware engine. The other committed use discount is the resource-based commitment, which is ideal for predictable workloads. When you purchase a committed use contract, you purchase compute resources like vcpus, memory, and gpus at a discounted price in return for committing to paying for those resources for one or three years. Sustained use discounts apply to the general purpose compute and memory optimize machine types as well as sole tenant nodes and GPUs. Sustained use discounts are applied automatically to usage within a project separately for each region, so there's no action required on your part to enable these discounts. The Google Cloud Pricing Calculator can help you identify pricing for the resources that you plan to use in your future architecture, without having to find out the hard way.
02:35:00 Cloud billing budgets are essential for automating cost control in environments where business owners deem necessary. This lesson covers the concepts of cloud billing budgets, committed use discounts, and how to create budget alerts.
02:40:00 The video discusses Google Cloud Associate Cloud Engineer Course, and how to create a commitment and reservation for a vm instance. The video also discusses spend-based commitments and committed use discounts.
02:45:00 In this video, the instructor explains how to create a budget and set up budget alerts, and how to create a new budget.
02:50:00 In this video, the instructor explains how to enable billing export in Google Cloud Platform, how to export billing data to a bigquery data set, and how to use data studio to visualize the data.
02:55:00 The video provides a brief overview of the bigquery export feature, which is used to export billing data. The video then goes on to explain how to set up the billing export data set and enable the bigquery data transfer service API. Finally, the video shows how to query the billing export data.
This video provides an introduction to the Google Cloud Associate Cloud Engineer Course, which covers topics such as cloud storage, authentication, and project management. Cloud Shell, which is integrated into the course, is described as a "global distributed" tool for accessing resources across multiple regions.
03:00:00 In this hands-on video, the instructor shows how to create a new Gmail user with fewer privileges, and how to configure it so that the user is an admin user for future use.
03:05:00 In this video, the presenter explains the difference between a super administrator account and a gmail account, and how the tony bowtie ace gmail account was created with less privileges than the antony gcloud ace gmail account. The presenter then explains how to assign roles to a new gmail user, and how to switch between users on a computer with multiple users.
03:10:00 This video covers the basics of the Google Cloud SDK, including the command line interface and how to work with resources. It is important for candidates for the Google Cloud Associate certification exam, and is a valuable tool for anyone working with Google Cloud.
03:15:00 The Cloud SDK includes command line tools that allow you to manage resources through the terminal in Google Cloud. The Cloud SDK includes commands such as gcloud, gsutil, bq, and cubectl. These commands allow you to manage resources such as compute engine, cloud storage, bigquery, and Kubernetes. The Cloud SDK is so powerful that you can do everything that the console can do, yet has more options. The Cloud SDK comes with some built-in commands that allow you to configure different options using gcloud init. Additionally, gcloud auth login and gcloud config allow you to configure accounts and projects.
03:20:00 In this YouTube video, an associate cloud engineer demonstrates how to install the Google Cloud SDK on Windows. After installing the Google Cloud SDK, he runs various commands to verify its functionality.
03:25:00 This Google Cloud Associate course shows how to install the Google Cloud SDK for Mac OS. After completing the installation, the course walks through how to run the "gcloud init" command.
03:30:00 In this video, the Google Cloud Associate demonstrates how to install and configure the Google Cloud SDK on a Mac and a Linux system. The video also covers how to log in to the Google Cloud SDK and initialize the installation.
03:35:00 In this video, the instructor explains how to install and configure the Google Cloud SDK, and shows how to switch between different users.
03:40:00 The video explains how to set up a default configuration for the Google Cloud Platform using the gcloud command line tool. It also explains how to switch between configurations.
03:45:00 The video shows how to configure and use the Google Cloud Associate Cloud Engineer Course's default configuration. It also explains how to install and use components.
03:50:00 Cloud Shell is a browser-based shell that allows you to access your Google Cloud resources from the console. Cloud Shell comes with a built-in code editor that allows you to browse file directories as well as view and edit files.
03:55:00 The video provides an introduction to the Google Cloud Associate Cloud Engineer Course, which covers topics such as cloud storage, authentication, and project management. Cloud Shell, which is integrated into the course, is described as a "global distributed" tool for accessing resources across multiple regions.
The video provides an overview of the Google Cloud Platform and demonstrates how to work with various features of the platform, including the Cloud Shell, limits and quotas, and the IAM Policy Management interface.
04:00:00 In this video, Tony Bowtie Ace demonstrates how to work with the Google Cloud Platform using Cloud Shell. He shows how to install Terraform, and how to customize and persist the environment.
04:05:00 The Google Cloud Associate Cloud Engineer Course provides a basic understanding of how to use the Cloud Shell, which is a feature of Google Cloud Platform. Cloud Shell provides a console interface for managing Google Cloud Platform resources, and the course demonstrates how to use various features of Cloud Shell, including the ability to run a web application in a new browser tab.
04:10:00 In this lesson, the instructor covers limits and quotas for using Google Cloud. The instructor demonstrates how to view and edit limits for a particular resource, as well as how to create alerts when quota limits are reached.
04:15:00 The Google Cloud Associate Cloud Engineer Course provides an overview of how quotas work in the Google Cloud Platform. In this video, the instructor demonstrates how to view quota limits in the Google Cloud Console using the quotas page and the api dashboard. To increase a quota, the instructor demonstrates how to enter multiple quota changes in bulk using the api dashboard.
04:20:00 In this video, the instructor discusses the benefits of using Google Cloud's IAM (Identity and Access Management) and describes the policy architecture. He then goes into more detail about the individual components of a policy and how they work together.
04:25:00 In this video, Google Cloud associate Cloud Engineer Course instructor, Ivan, covers the different types of Google Cloud IAM accounts, policies, and roles. Ivan discusses the advantages and disadvantages of using Google groups and Google domain names as identity sources for Google accounts, and he provides a brief overview of the different types of Google Cloud IAM accounts and the different types of roles that can be used with those accounts. Finally, Ivan discusses the different types of IAM permissions that are available with Google Cloud.
04:30:00 The Google Cloud Associate Cloud Engineer Course includes the permissions in the viewer role and you can apply primitive roles at the project or service resource levels by using the console, the api, and the gcloud tool. You cannot grant the owner role to a member for a project using the iam api or the gcloud command line tool, you can only add owners to a project using the cloud console. Google recommends avoiding these roles if possible due to the nature of how much access the permissions are given in these specific roles. Primitive roles and pre-defined roles are created and maintained by Google, their permissions are automatically updated as necessary, and custom roles are user defined and allow you to bundle one or more supported permissions to meet your specific needs. Unlike predefined roles, custom roles are not maintained by Google, and when new permissions features or services are added to Google Cloud your custom roles will not be updated automatically. You must choose an organization or project to create it in, and then grant the custom role on the organization or project as well as any resources within that organization or project. The custom roles user interface is only available to users who have permissions to create or manage custom roles by default. Project owners can create new roles, but there is one limitation that i wanted
04:35:00 This video provides a brief overview of Google Cloud's policy architecture and how it is used in order to control access to resources. It also covers how policy inheritance works and how to query a project's granted policies using the command line.
04:40:00 This video demonstrates how to pass the Google Cloud Associate Cloud Engineer Exam by using the bowtie command-line tool and the gcloud projects get command. The video also covers how to use the gcloud resource dash manager command to get information about resource policies.
04:45:00 This video introduces the Google Cloud Associate Cloud Engineer Course, which covers policies, conditions, and identity. Tony Bowtie Ace, a Gmail user, is created and then used to demonstrate how policies can be added and edited. Finally, an organization policy is discussed.
04:50:00 In this video, the instructor discusses the different types of Google Cloud resources, the different ways to manage and use these resources, and the various settings available. He also covers the various Google Cloud compliance features.
04:55:00 The video demonstrates how to enable audit logging on a Google Cloud Platform project using the command line. The policy is then saved to a file for later use. Finally, the video demonstrates how to view and manage groups using the IAM Policy Management interface.
The video explains how to create a new user and grant her permissions to work on the project. The video covers best practices for service accounts, discusses how to audit service accounts, and covers how to create and use service accounts for specific services.
05:00:00 This video demonstrates how to add a new user, Laura Delightful, to a project and give her permissions to work on the project. Laura needs access to the project's storage, which is granted to her by granting her the storage admin role.
05:05:00 In this lesson, the instructor explains what a service account is, how service accounts are used in Google Cloud, and the different types of service account. He also explains how to create and manage service account keys.
05:10:00 In this video, Google Cloud Associate instructor John Lewis discusses how to create and use user managed keys, which are credentials that represent a security risk if not managed correctly. Lewis also discusses service account permissions and demonstrates how to use access scopes to grant permissions to an instance that will run as a service account.
05:15:00 This video demonstrates how to impersonate a service account in Google Cloud using the iam service account API. The video covers best practices for service accounts, discusses how to audit service accounts, and covers how to create and use service accounts for specific services.
05:20:00 This video explains how to grant permissions to a service account for accessing cloud storage. It first shows how to create a default service account and then creates a custom service account. The custom service account is given permissions to read and write files to cloud storage.
05:25:00 This video explains how to create a service account and grant permissions to it. The service account is given read and write access to the cloud storage bucket and a storage object creator role.
05:30:00 In this video, the instructor explains how to create and use a new service account using the Google Cloud Command Line. After creating the account, the instructor shows how to assign permissions to the account and use it to access Google Cloud resources.
05:35:00 The Google Cloud Associate Cloud Engineer Course covers the configuration of cloud identity, security, device management, and reporting.
05:40:00 Google Cloud Directory Sync is a free Google provided tool that synchronizes Active Directory to Cloud Identity. The principle of least privilege is followed to limit access to what is needed to be done. Predefined roles are used to grant minimal access to needed permissions.
05:45:00 In this YouTube video, Google Cloud Assistant Cloud Engineer Course instructor Brian Lipovsky explains how to best structure your environment to avoid security issues. He recommends using projects to group resources that share the same trust boundary, setting policies at the organization level and at the project level, and using service account keys that are kept safe. He also advises using auditing to check for changes that might be unauthorized and exporting audit logs to cloud storage to prevent them from being lost.
05:50:00 In this video, an instructor covers the layers of the Open Systems Interconnection (OSI) model and how they relate to networking concepts. Layer 3 is the network layer, and the instructor covers the Internet Protocol (IP). Layer 4 is the transport layer, and layer 7 is the application layer.
05:55:00 In this video, Google Cloud Associate Cloud Engineer Course instructor Richard Stevens covers the basics of IPv4 and IPv6. He notes that IPv4 addresses are represented in dotted decimal notation with four numbers, each ranging from 0 to 255, separated by dots. He explains that IPv4 can support over 4.2 billion addresses and that the range for IPv4 addresses is viewed as large when first introduced, but that this number has dwindled as more devices have been added to the internet. He goes on to explain that classful addressing was introduced to address this problem, and that the first and second octets of IPv4 addresses are assigned by the registries, while the third and fourth octets are free for the business to assign. He then covers the next two ranges, class A and class B, which are similar in size. Class A addresses can support up to 2.1 billion hosts and class B addresses can support up to 1 billion hosts. He finishes the video by discussing class C and class D, which are smaller than class B, and class E and class F, which are even smaller.
This video explains the basics of classless inter-domain routing (CIDR), how it works with Google Cloud, and how it can be helpful for real-world situations. It also covers the different types of IP addresses that are available, how to assign them, and how they are used for internal communication within a private network.
06:00:00 The main problem with classful addressing was that it was difficult to manage large address blocks, and the same problem arose with requiring more IP addresses than a class B network could provide. Classless interdomain routing (Cider) was introduced to solve this problem, and it allows for more granular network block allocation. I will be covering Cider in a different lesson.
06:05:00 In this video, an instructor covers the basics of classless inter-domain routing (CIDR) and how it relates to Google Cloud. The instructor covers the different prefixes that can be used with CIDR and how to determine the size of a network with those prefixes. Finally, the instructor covers how classless inter-domain routing works with Google Cloud, and how it can be helpful for real-world situations.
06:10:00 This video covers the basics of IPv6, including the network and host parts of an IPv6 address, and how to abbreviate them.
06:15:00 This video discusses the core networking service of Google Cloud Platform (GCP), which is called a "virtual private cloud" or "vpc." It covers the benefits of using a vpc, as well as the various networking features that are available. The video also goes over the different types of projects that are available on GCP, and how the networking within them is managed.
06:20:00 In this video, the instructor covers the basics of Google Cloud's associate cloud engineer certification exam. He explains that a vpc network is simply a collection of individual ip addresses and services, and that traffic can be controlled with network firewall rules. He also notes that vpc networks only support unicast traffic and that vms in a vpc network can only communicate with other vms in the same network, or with vms in a vpc network that is connected to a custom network. Finally, the instructor covers the difference between auto mode and custom mode networks, and explains that custom mode networks are more suited for production use.
06:25:00 The video provides a tour of the Google Cloud Platform's default vpc and explains the various settings available for the vpc. It also demonstrates how to expand a subnet in the default vpc.
06:30:00 This 1-paragraph summary explains how to change the subnet range for a Google Cloud project. First, the video shows how to change the subnet range for a subnetwork. Next, the video shows how to change the subnet range for a whole Google Cloud project. Finally, the video explains how to delete a Google Cloud project.
06:35:00 In this lesson, the instructor covers subnets and how they work in Google Cloud. The instructor also covers how to create custom vPC networks.
06:40:00 This video explains how Google Cloud routes traffic to destinations inside and outside of a virtual private cloud (VPC). Routes consist of a single destination and a single next hop, and are stored in the routing table for a VPC. If a destination address is within the route's destination range, the packet is delivered to the appropriate next hop. If the destination address is not within the route's destination range, the packet is dropped. Google Cloud only uses a system generated default route if a more specific route does not apply to a packet.
06:45:00 Google Cloud provides subnet routes that define paths to each subnet in a virtual private cloud network. These routes can be system generated or can be maintained automatically by one or more cloud routers. You can delete a subnet route, but only if you convert the auto mode virtual private cloud network to a custom mode. Static routes can use any of the static route next hops and these can be created manually using the Google Cloud Console. Custom routes that use this next hop cannot be scoped to specific instances by network tags. When creating a static route, you will always be asked for different parameters that are needed in order to create the route.
06:50:00 In this video, the instructor covers topics related to static and dynamic routes, routing order, and private Google Access. They also discuss the effects of disabling private Google Access on instances with external IP addresses.
06:55:00 This video explains how Google Cloud resources communicate internally within a private network, and also covers the different types of IP addresses that are available to use. The video also covers how to assign an internal IP address to a VM instance or use a reserved static IP address.
This video provides an overview of how to create and configure static and ephemeral IP addresses in Google Cloud Platform, as well as how to create firewall rules to control traffic to and from instances.
07:00:00 In this video, Google Cloud Associate Cloud Engineer Course instructor John Sonmez walks through the different internal and external IP address options available to Cloud Professionals, as well as how to reserve and release these addresses.
07:05:00 Google Cloud offers two ways to reserve internal IP addresses: statically and automatically. If you need a static address for a specific project, you can either reserve it before you create the resource or promote an ephemeral address to a static one. You can also reserve external IP addresses.
07:10:00 In this video, Google Cloud associate Cloud engineer Course student demonstrates how to create internal and external static ip addresses.
07:15:00 This video explains how to reserve a static internal IP address in Google Cloud Platform. After reserving the address, the user is then able to create an instance and view the static internal IP address in the console.
07:20:00 In this video, the instructor discusses how to create and use static and ephemeral internal and external IP addresses in Google Cloud Platform. First, they delete an existing instance, then create and reserve a static external IP address. Next, they create and reserve an external static IP address for a global load balancer, and finally they attach the external static IP address to an instance.
07:25:00 In this video, the Google Cloud Associate teaches how to create and use static and ephemeral external ip addresses on the Google Cloud Platform. The instructor also demonstrates how to promote an ephemeral external ip address to a static external ip address.
07:30:00 In this video, the instructor covers the basics of Google Cloud's firewall rules. This includes an introduction to vpc networks, firewall rules, and how they are enforced. He then goes on to focus on how to create and use vpc firewall rules to allow or deny network traffic to or from VM instances.
07:35:00 The Google Cloud Associate Cloud Engineer Course teaches how to create and modify firewall rules for a Google Cloud VPC. The course covers the following topics:
- Definition of firewall rules at the network level, including consideration of instances within the same network.
- Implied firewall rules that apply to outgoing and incoming connections.
- Rule priority and applicability.
07:40:00 In this video, Google Cloud Associate Cloud Engineer Course instructor Paul Alaba discusses firewall rules and how they work. He explains that firewall rules are stateful and that when a connection is allowed through the firewall, all response traffic is also allowed. He also notes that firewall rule components include the network and priority, direction of traffic, and action on match. Finally, he explains that a target is what defines which instances the rule applies to, and that you can specify a target by using one of the three options.
07:45:00 This YouTube video covers how to create a custom VPC network, subnets, instances, and firewall rules.
07:50:00 This video provides instructions on how to create a Google Cloud VPC network using the console. The network is called "custom" and is divided into private and public subnets, with a public subnet located in the us-east-1 region and a private subnet located in us-east-4 region. The network includes a gateway and private Google access. The routes and firewall rules are not yet in place, but will be added in a few minutes. The network is enabled for DNS.
07:55:00 In this video, the instructor explains how to create a public and private instance of Google Cloud Platform's Compute Engine, upload files, and configure networking.
In this video, Jason Zweig covers the theory and concepts of vpc peering and demonstrates how to create a peering connection between two VPCs in two separate Google Cloud projects. He also explains how to use Google Cloud's vpc flow logs to monitor network throughput and performance, traffic changes, and network flows.
08:00:00 In this video, a Google Cloud Associate demonstrates how to create a custom VPC network, create a storage bucket, create a private and public instance, and assign the service account on the public instance read/write access to both compute engine and cloud storage.
08:05:00 This video demonstrates how to set up a firewall rule for public access to a private instance, copy an instance's public IP address, and ping the public instance from a private instance.
08:10:00 This video explains how to enable private Google access on a private subnet so that you can access cloud storage.
08:15:00 In this video, Google Cloud Associate Cloud Engineer Course instructor Jason Zweig covers the theory and concepts of vpc peering. He then demonstrates how to pair two networks together and verify communication between them.
08:20:00 This video demonstrates how to create a peering connection between two VPCs in two separate Google Cloud projects. Afterwards, it shows how to verify the connection by creating two instances in each network, and then pinging one instance from the other.
08:25:00 This video provides an overview of how to create a Google Cloud Associate Cloud Engineer Course - Pass the Exam! network, create firewall rules, and create instances. Finally, the video demonstrates how to create a vbc peering connection.
08:30:00 This video tutorial teaches the concepts and terminology of shared virtual private clouds (VPCs). You'll learn how to create two separate VPC networks and set up firewall rules, instances, and a peering connection between them. Finally, you'll delete all the resources created in the demo.
08:35:00 Shared vpcs allow multiple projects to share resources and communicate securely, while abiding by the principle of least privilege. In order to administer shared vpcs, a shared vpc admin must have the permissions to enable host projects, attach service projects to host projects, and delegate access to subnets in shared vpc networks to service project admins.
08:40:00 VPC flow logs capture a sample of network traffic between vm instances in a subnet, allowing for monitoring and security analysis, as well as optimization of billing. Flow logs are enabled on a subnet-by-subnet basis, and can be exported for 30 days or longer.
08:45:00 This video explains how to use Google Cloud's vpc flow logs to monitor network throughput and performance, traffic changes, and network flows. Flow logs can also be used for network forensics.
08:50:00 In this lesson, we learn about the Domain Name System (DNS), its history, and how it works. We also look at how IP addresses are converted to domain names and how a zone file is used to store this information. Finally, we learn about a type of DNS server called a Name Server (NS).
08:55:00 The DNS system organizes web addresses into a hierarchical data structure, provides dynamic system for protocols and methods for storing and retrieving IP addresses for host computers, and has a root server at the top of the system. Below the DNS route in the hierarchy are the top level domain servers, known as TLDs. These servers handle the resolution of second level domain names for users.
The video discusses how to manage multiple operating systems on one computer using a hypervisor, which is a process known as virtualization. This technique helps to keep systems stable and prevent the operating systems from interfering with each other. Para virtualization is a way to make virtualization more efficient by replacing instructions that cannot be virtualized with hyper calls that communicate directly with the hypervisor.
09:00:00 The Google Cloud Associate Cloud Engineer Course covers how DNS works, and explains how the DNS lookup process works. It covers the eight steps in a DNS lookup, and explains how a recursive resolver can help resolve queries. The course also covers how DNS caching works, and how the TTL value affects caching.
09:05:00 This video discusses DNS records and their purposes. Name server records identify the DNS server that holds records for a domain. Address records point a domain name to an IP address. Canonical name records map one domain name to another. CNAME records point a domain name to another domain name.
09:10:00 In this video, a Google Cloud Associate Cloud Engineer Course instructor covers how mx records are used for email routing. The first mx record is for mail.bowtieinc.co, and the second mx record is for aspmx.l.google.com, which is a fully qualified domain name. If both values are the same, then the server gets the result of the query back and uses it to connect to the mail server for bowtieinc.co via the smtp protocol.
09:15:00 This lesson covers network address translation (NAT), which is a process used in home businesses and any cloud networks. NAT is used to map multiple local private IP addresses to a public IP address before transferring the information. NAT is a way to alter the network address data in the IP header of a data packet while traveling through a network. NAT is also used in most home routers that are provided by your internet service provider. NAT was originally designed to deal with the scarcity of free IPv4 addresses.
09:20:00 In this video, a Google Cloud Associate Cloud Engineer Course discusses the different types of NAT (Network Address Translation) and how they work. Static NAT is used when one specific device with a private IP address needs access to the public internet. Dynamic NAT is used when multiple internal hosts with private IP addresses are sharing an equal or fewer amount of public IP addresses, and Port Address Translation (PAT) is used when multiple private IP addresses are translated using a single public IP address and a specific port.
09:25:00 In this video, the instructor describes how static NAT works. Devices are assigned a permanent public IP address from a pool, and the mapping of public to private is allocation-based. When a device on the network wants to access a service on the internet, it generates a packet with the source IP address being the private address of the device and the destination IP being the public IP address.
09:30:00 This video teaches how to pass the Cloud Associate Cloud Engineer Certification exam. The video discusses the different types of NAT, dynamic NAT, and port address translation. It also provides an example of how these technologies are used.
09:35:00 Cloud DNS is a DNS service provided by Google which manages authoritative DNS servers for public zones and private zones that are visible only within your network. Cloud DNS servers are located around the globe, making it a globally resilient service.
09:40:00 Cloud DNS is a service offered by Google that allows for the deployment of zones and policies across Google's global network backbone. Cloud DNS offers flexibility in hosting both public zones and privately managed zones.
09:45:00 This video explains how virtualization works and how it enables different applications to run on one computer. The video also covers a basic foundation of virtualization, including how a kernel operates under privilege mode and manages the distribution of hardware resources among multiple processes.
09:50:00 The Google Cloud Associate Cloud Engineer Course teaches students how to manage multiple operating systems on one computer using a hypervisor. This technique, known as virtualization, prevents the operating systems from interfering with each other and helps to keep systems stable. However, virtualization has been slow and inefficient historically, and this has prevented it from becoming more widespread. Para virtualization, which replaces instructions that cannot be virtualized with hyper calls that communicate directly with the hypervisor, solves this problem.
09:55:00 In this lesson, the author discusses virtualization concepts, specifically kernel level virtualization. He covers what is included in an instance, the different options for creating an instance, and how kernel level virtualization works. He also provides a brief overview of virtualization in Google Cloud.
This video provides an overview of the Google Cloud Associate Cloud Engineer Course, which covers topics such as how to create and manage instances, how to choose the right machine type, and how to configure pricing. The video also discusses the different types of machine types that are available on the Google Cloud Platform, as well as the different types of memory that are available.
10:00:00 Google Cloud offers compute engine, which lets you create and run virtual machines known as instances. You can choose from different machine types that correspond to your specific workload, and you can also create custom images.
10:05:00 This video tutorial explains how to create a custom image from boot disks or other images, use the custom image to create an instance, and add no cost to your instances, but incur an image storage charge. The third option is to use a marketplace image, which lets you quickly deploy functional software packages that run on Google Cloud.
10:10:00 In this video, the Google Cloud Associate demonstrates how to create a new vm instance from scratch. The video covers the left-hand menu options for creating an instance, as well as the marketplace where users can find pre-configured images and software.
10:15:00 The course discusses the different types of cloud instances, how to choose the right machine type, and how to configure the instance. It also covers pricing and how to use the confidential VM service.
10:20:00 This video covers how to set up a Google Cloud instance and configure various options, such as the use of public images or custom images. It also covers how to manage the instance using the Google Cloud Console.
10:25:00 In this video, Google Cloud Associate instructor Jonathan Corbett walks through configuring an instance, highlighting the different types of machine types that are available on the Google Cloud Platform. He explains that, when creating an instance, you must choose a machine type, and describes the different families and workloads each machine type is designed for. He goes on to explain the different series and types of machine types, and concludes the video by discussing the use cases for each type of machine type.
10:30:00 The Google Cloud Associate Cloud Engineer Course covers the various types of Google Cloud Platform machines, including general purpose, high memory, and high cpu types. The course also provides information on the e2, n1, and n2 machine types.
10:35:00 The Google Cloud Associate Cloud Engineer Course covers the different machine types that are available on the Google Cloud Platform, as well as the different types of memory that are available. The course also covers the different types of compute that are available on the Google Cloud Platform, as well as the different types of machine types that are available for those types of compute. Finally, the course covers the different types of custom machine types that are available on the Google Cloud Platform.
10:40:00 This video discusses the life cycle of Google Cloud instances, and provides an overview of the stages an instance goes through during its lifetime. Once an instance enters the running state, it should be able to be accessed using SSH or RDP. There are no costs incurred during the provisioning or staging state, but once an instance enters the running state, costs will start to accrue. Finally, once an instance exits the running state, it can be deleted.
10:45:00 In this video, Google Cloud associate cloud engineer instructor Dave Lee discusses the different instance states and their associated costs. He also provides a high-level overview of the instance lifecycle and explains how to create and manage shielded virtual machines.
10:50:00 This 1-hour Google Cloud Associate Cloud Engineer Course covers policy baseline and integrity monitoring for shielded virtual machines. In addition, the course covers the installation of a guest environment on Linux or Windows.
10:55:00 This video provides an overview of the Google Cloud Associate Cloud Engineer Course, which includes a review of how to access your Windows instances using different methods. The course also covers how to manage SSH Keys and local user accounts on Google Cloud. Finally, the video discusses how to manage your Windows instances using live migration.
In this video, we learn about the Google Cloud Associate Cloud Engineer Course, including how to connect to instances, set passwords, and use metadata. We also cover billing and discounts, as well as the different types of cloud storage.
11:00:00 This lesson discusses how to log in to an instance, how to set a Windows password, and how to connect to an instance from different platforms.
11:05:00 This video demonstrates how to connect to a Windows Server instance in Google Cloud using various methods, including Remote Desktop Connection, PowerShell, and the Chrome extension.
11:10:00 In this video, the Google Cloud associate Cloud Engineer Course instructor shows how to connect to a Windows instance and a Linux instance using the Google Cloud platform.
11:15:00 In this video, Tony Bowtie demonstrates how to enable os login on a linux instance using the gcloud init command. This feature relieves the complexity of managing multiple key pairs, and is the recommended way to manage users across multiple instances or projects.
11:20:00 This video explains how to use metadata to manage your Google Cloud Platform (GCP) resources. It covers the basics of assigning metadata to projects and instances, and how to use default metadata entries. The video also explains how to use startup scripts to create dynamic metadata.
11:25:00 This 1-paragraph summary provides a brief introduction to the Google Cloud Associate Cloud Engineer Course, and how to query metadata on an instance.
11:30:00 This video provides an overview of the Google Cloud Associate Cloud Engineer Course, including how to query instance and project metadata. Additional features of the course include how to create and run startup and shutdown scripts, and how to use metadata to automate tasks.
11:35:00 In this video, we learn about Google Cloud's billing model, which is based on "resource-based billing." This means that each CPU and eachGB of memory on a Google Cloud instance is charged separately, and you are not charged for usage up until one minute after the first minute of usage. In addition, instance up time (the total number of seconds an instance has been running) is another determining factor for cost.
11:40:00 The video explains how to use reservations to ensure that desired resources are always available. Reservations are applied automatically to compute engine data processing and Google Kubernetes Engine resources. Sustained use discounts are applied to usage within a project, separately for each region. Note that sustained use discounts are not applied to app engine Flexible environment or Data Flow resources.
11:45:00 Google Cloud offers discounts on machine usage to help optimize costs, and offers three types of discounts: sustained use discounts, committed use discounts, and preemptable vms. Preemptable vms are up to 80% cheaper than regular instances, and pricing is fixed. To purchase a discount, you must first create a commitment. After you create a commitment, you cannot cancel it, and you must pay the agreed upon monthly amount. Commitment recommendations give you opportunities to optimize your compute costs.
11:50:00 This video covers the basics of cloud storage, with a focus on block storage. It covers the theory behind data presentation in different storage options, and goes over the various cloud services that offer block storage.
11:55:00 In this video, Google Cloud Associate Cloud Engineer Course instructor Ryan Lowe covers the three main types of storage: block storage, file storage, and object storage. Each type of storage has its own benefits and drawbacks, with block storage being the most popular due to its fast performance and large capacity. Cloud Storage is a flat, logical container for storing data, which can be accessed by users anywhere in a VPC network using the NFS protocol.
This video explains how to create and manage persistent disks and snapshots in Google Cloud Platform. It covers the different types of persistent disks available, and how to attach and manage them. It also explains how to use scheduled snapshots to reduce data loss in case of an unexpected failure.
12:00:00 This video covers the different types of storage available on Google Cloud Platform, and discusses the performance of each. It discusses persistent disks and local SSDs, and explains which type to use for an instance.
12:05:00 The video covers the different types of storage available in Google Cloud, including persistent disks and local SSDs. It describes the different characteristics of each type of storage, and explains how to set up and use persistent disks and local SSDs. It also covers snapshots and how to use regional persistent disks in combination with snapshots for high availability.
12:10:00 The three types of Google Cloud persistent disks are the standard, zonal, and regional persistent disks. The standard persistent disk is backed by standard hard disk drives and is best suited for large data processing workloads that primarily use sequential ios. The zonal persistent disk is accessed by two different zones and has a higher latency than the regional persistent disk. The balance persistent disk is designed for general purpose use and has a lower iops per gigabyte than the standard or zonal persistent disks but is faster than the ssd persistent disk. The pd SSDs have a single digit millisecond latency and are higher in cost than the standard or zonal persistent disks.
12:15:00 Google Cloud Associates teaches how to pass the Cloud Engineer exam. This course covers different types of persistent disks and local SSDs. Local SSDs have higher throughput and lower latency than any of the other options. Local SSDs persist only until the instance is stopped or deleted, and each local SSD is 375 GB in size.
12:20:00 In this video, Tony Bowties demonstrates how to create and attach a persistent disk to an instance, interact with the disk, and resize it. He also shows how to delete the disk.
12:25:00 In this video, the instructor demonstrates how to create a new persistent disk in the Google Cloud Platform Console. The disk will be in the US East 1b zone, and the size will be set to 500GB. The disk will be a regional persistent disk, and the instructor will show how to attach it to an instance. Finally, the instructor will show how to list and attach block devices to an instance.
12:30:00 In this YouTube video, the Google Cloud Associate Cloud Engineer Course instructor demonstrates how to mount a disk on Google Cloud Platform using the sudo file-less command. After creating the disk and formatting it to a file system, the instructor mounts the disk and shows that the disk is not mounted after the instance is rebooted. The instructor then edits the fstab file to include the disk's unique identifier and the disk is automatically mounted every time the instance is rebooted.
12:35:00 In this video, the instructor demonstrates how to resize a disk on an instance, attach a new disk, and delete all the resources created during the demonstration.
12:40:00 This video explains how to create and manage snapshots of persistent disks in Google Cloud Platform.
12:45:00 The Google Cloud Associate Cloud Engineer Course covers how to create and manage persistent disk snapshots. The course also covers how to use scheduled snapshots to reduce data loss in case of an unexpected failure.
12:50:00 This video demonstrates how to create and delete snapshots, and schedule snapshots for an instance. The example uses the console and command line.
12:55:00 In this video, the Google Cloud Associate Cloud Engineer Course instructor demonstrates how to create a snapshot schedule for two VM instances. The instructor also explains how to attach the snapshot schedule to a disk.
This video introduces Google's "Deployment Manager" tool, which allows users to deploy updates and tear down resources from within Google Cloud using yaml jinja and python code templates. The video covers the architecture of the tool and explains how to create a configuration.
13:00:00 This video introduces Google's "Deployment Manager" tool, which allows users to deploy updates and tear down resources from within Google Cloud using yaml jinja and python code templates. The video covers the architecture of the tool and explains how to create a configuration.
13:05:00 A configuration must contain a resources section, followed by the list of resources to create to instantiate the deployment. The first component of the configuration is the name, which is a user-defined string to identify the resource. The second component is type, which can represent a single API source (base type) or a set of resources (composite type). The third component is properties, which includes all the parameters for the resource type. A configuration can contain templates, which are parts of the configuration file that have been abstracted into individual building blocks. With templates, you can separate your configuration out into different pieces that you can use and reuse across different deployments.
13:10:00 This video provides a brief overview of how to create a Google Cloud deployment, update it, and delete it. The main points covered are:
- Formation of a Google Cloud deployment is done through the command line;
- A configuration file is required for deployment;
- There are best practices to follow when creating and updating a deployment, such as breaking the deployment into logical units, using references, and previewing the deployment.
13:15:00 In this lesson, you will learn how to use the Google Cloud Editor to create and copy files, clone a GitHub repository, and deploy a web server using Deployment Manager.
13:20:00 The video demonstrates how to create a Google Cloud Deployment using the Bowtie Deploy configuration tool. First, the user turns on the API for deployment manager. Next, the user creates a mock deployment using the Bowtie Deploy configuration tool. Finally, the user executes the mock deployment.
13:25:00 In this video, the Google Cloud Associate Cloud Engineer Course instructor demonstrates how to deploy a custom configuration using the Google Cloud Deployment Dash Manager. The instructor first verifies the project and configuration settings before deploying the configuration.
13:30:00 In this video, the instructor covers the basics of Google Cloud load balancing. He explains the differences between low balancing and high balancing, and provides examples of when each might be used. He also covers the different types of load balancers available on Google Cloud Platform, and explains how to choose the right one for a specific scenario.
13:35:00 Google Cloud offers load balancers that can distribute traffic as close to users as possible, reducing latency and improving user experience. Load balancers can be global or regional, and have a variety of settings such as health checks, session affinity, and traffic distribution.
13:40:00 In this video, Google Cloud Associate instructor Bill Spitz discusses the different types of load balancers available in Google Cloud Platform, and how they distribute traffic. He also touches on content-based load balancing, and how it uses URL maps to determine which backend service to use for a particular request. Finally, he explains how to set up a load balancer using different types of backends.
13:45:00 The Google Cloud Associate Cloud Engineer Course teaches how to use the different load balancers available in the Google Cloud Platform. The course covers the following load balancers:
-- Global external and internal load balancers that can handle both IPv4 and IPv6 traffic
-- SSL proxy low balancing that distributes SSL traffic to VM instances
-- TCP proxy low balancing that distributes TCP traffic to VM instances
Each load balancer is explained in detail, and the courses also cover how to configure each load balancer for specific use cases. The course also covers how to use load balancers for non-HTTP traffic, and how to use load balancers with SSL offload.
13:50:00 Instance groups are a way to set up a group of identical servers used in conjunction with instance templates, which handle the instance properties to deploy the instance groups into your environment. This lesson will dive into the details of the features use cases and how instance groups and instance templates work together to create a scalable and performing environment.
13:55:00 The Google Cloud Associate Cloud Engineer Course covers the use cases and features of migs, including stateless serving, batch work, and stateful workloads. Auto healing and scaling are also covered.
The Google Cloud Associate Cloud Engineer Course is designed to help students pass the Google Cloud Exam. The course covers the basics of setting up a cloud infrastructure, including back end and front end configurations, and a load balancer. In this video, the instructor covers the cluster control plane in Google Cloud Platform (GCP), including overview of nodes and node pools, node versioning, and cluster management using APIs and the Google Kubernetes Engine (GKE).
14:00:00 This video describes how to use Google Cloud's auto scaling, load balancing, and Canary testing features to deploy updates and new versions of software more safely and efficiently.
14:05:00 In this video, an instructor explains how to create a new instance template and an instance group, and how to use custom or public images in instance templates and instance groups.
14:10:00 In this video, the instructor creates an instance group, firewall rule, and load balancer. Next, the instructor creates a back end service and names it bowtie backend service. The instructor then selects the available bowtie group as the back end service's instance group. The instructor then enters the port number and other options for the back end service, and then clicks on Done. Finally, the instructor demonstrates how to add a cache using cloud CDN.
14:15:00 This video introduces the Cloud Associate Cloud Engineer Course, which is designed to help students pass the Google Cloud Exam. The course covers the basics of setting up a cloud infrastructure, including back end and front end configurations, and a load balancer. Part 1 of the course covers creating a low-balance load balancer.
14:20:00 In this video, the Google Cloud Associate Cloud Engineer course instructor walks through how to delete an instance template, an instance group, and a load balancer.
14:25:00 In this video, the instructor covers the difference between virtual machines and containers, describes the benefits of containerization, and provides an example of how containers work. He then covers how to create and delete firewall rules for Google Cloud's Premier Container Orchestration Service, Kubernetes.
14:30:00 This video introduces containers, teaches how to create and run containers using a Docker image, and explains how to use a public container registry, such as Docker Hub.
14:35:00 In this lesson, the instructor covers key topics related to Google Cloud's Kubernetes engine, such as the cluster architecture and components, and how they work together to provide a platform for automating containerized applications. He also covers some of the challenges that have been faced with Kubernetes' widespread adoption, such as scaling. Finally, the instructor provides a brief introduction to Google Cloud's managed Kubernetes offering, which provides a managed environment for deploying, managing, and scaling containerized applications.
14:40:00 In this video, Google Cloud Associate Cloud Engineer Course instructor, Brian Graf, describes the architecture of a Google Cloud infrastructure, including the control plane and nodes. The control plane is the unified endpoint for your cluster, and it makes global decisions about the cluster, such as scheduling and detecting and responding to cluster events. The architecture also includes components within the control plane and nodes that you should be familiar with, such as the cubelet agent that runs on each node and communicates with the control plane, and the cube controller manager, which runs controller processes and is responsible for things like noticing and responding when nodes go down, maintaining the correct number of pods populating the services and pods, and creating default accounts and API access tokens for new namespaces. Finally, the container runtime is the software that is responsible for running containers on Kubernetes, and it supports container runtimes like Docker and Container D.
14:45:00 This video covers the cluster control plane in Google Cloud Platform (GCP), including overview of nodes and node pools, node versioning, and cluster management using APIs and the Google Kubernetes Engine (GKE).
14:50:00 In a Google Cloud Zone, a multi-zonal cluster has nodes running in multiple zones, while a single-zone cluster has a single replica of the control plane running. A regional cluster has multiple replicas of the control plane running in multiple zones within a given region. Nodes in a regional cluster still run the same number of nodes as in a single-zone cluster, but the cluster's nodes and its workloads cannot be configured until the control plane is available. Private clusters give you the ability to isolate nodes from having inbound and outbound connectivity to the public internet. Private clusters also have a private endpoint in addition to a public endpoint. The control plane for a private cluster has a private endpoint in addition to a public endpoint.
14:55:00 The Google Cloud Associate Cloud Engineer Course discusses the various cluster upgrades that are available, including cluster auto-scaler and surge upgrades. Cluster upgrades are generally disruptive, so it is important to weigh the benefits of an upgrade against the potential disruption to workloads.
This video covers the basics of using Google Cloud Platform to deploy a containerized application. It explains how to create a cluster, select a zone for the cluster, and deploy the application.
15:00:00 In this lesson, the instructor covers the basics of Kubernetes objects and how they are managed. He covers objects such as pods, which are the smallest deployable objects in Kubernetes, and objects such as containers, which are running instances of an application. He also covers how to create and manage these objects using a manifest file.
15:05:00 In this video, Google Cloud Associate Cloud Engineer Course instructor Paul Shapiro explains how Kubernetes works and how pods are created and managed. He goes on to say that it is generally recommended to use a controller to manage pods, and that pods will remain on their nodes until their processes are complete. Finally, Shapiro covers the pod life cycle and describes the phases it goes through.
15:10:00 This video covers the basics of Google Cloud's services, including pods and object management. It discusses the different types of services and their uses, and provides an overview of the exam topics related to services.
15:15:00 A cluster IP service is a logical set of pods that provides a single persistent IP address and DNS name for pods to access. It allows for routing external traffic into your cluster and used inside your cluster for more intelligent routing with services. Services are an abstraction in the sense that they are not processes that listen on some network interface, and each pod that is created receives its own IP address.
15:20:00 The video describes the different types of services that are available in Google Cloud Platform, and explains how to create and expose each type of service. It also explains how to use exposed ip addresses and port numbers when connecting to services.
15:25:00 In this lesson, the different service types available in Kubernetes are introduced. Load balancers are covered in detail, with the option to create headless services. Next, external name services are described, which provide an internal alias for an external DNS name. Finally, the headless service type is explained, as well as how it differs from the other service types.
15:30:00 In this lesson, the instructor will be going over ingress in Kubernetes, a built-in and managed ingress controller that implements ingress resources as Google Cloud load balancers. The instructor will also be discussing the load balancer's url map and how it references back-end services. Finally, the instructor will give a demonstration of how ingress works.
15:35:00 In this video, the Google Cloud Associate Cloud Engineer Course is explained, including the different types of ingress controllers and the ingress manifest. It is also mentioned that each service has its own independent manifest and that health checks for services can be specified using custom resources or default parameters. Finally, it is explained how to provide certificates for an ingress controller using either managed certificates from Google Cloud or self-managed certificates.
15:40:00 In this video, the Google Cloud Associate Cloud Engineer Course teaches how to create and manage ssl certificates, create a secret to keep the certificates safe, and use the secret to specify an ingress for an http or https load balancer.
15:45:00 In this video, Google Cloud's Associate Cloud Engineer Course instructor discusses the different volume types available in Google Cloud Platform, and how they're used. Among these are empty dir, config map, and secret volumes, which provide convenient storage for applications running in a pod. Finally, persistent volume claims are introduced, which allow applications to dynamically provision durable storage.
15:50:00 This video covers persistent volumes and persistent volume resources, as well as storage classes and access modes for persistent disks. The video also covers stateful sets and persistent volume claim templates.
15:55:00 In this YouTube video, Tony Bowtie discusses how to set up a gKE cluster and deploy a containerized application. He names the cluster "bowtie dash cluster" and specifies that it be a single zonal cluster. He then selects the us east 1b zone as the cluster's location.
The video demonstrates how to set up a Google Cloud cluster, including setting up networking and security. They then demonstrate how to add a workload and configure auto scaling. Next, they show how to deploy a Box of Bowties application on a Google Cloud Platform (GCP) cluster. Finally, they explain how to scale a deployment of a workload on Google Cloud Platform, by scaling down the number of replicas and then scaling it back up again.
16:00:00 The Cloud Engineer Course, which is hosted on the YouTube channel "Google Cloud", lets users create a regional cluster on Google Cloud Platform. By specifying at least one zone, users can create nodes in each zone, resulting in a cluster with a greater number of nodes. Cloud Engineer Course instructor, John Papa, goes over the settings for a new cluster, including node pool configuration, enabling auto scaling, and setting up auto upgrade and auto repair.
16:05:00 In this video, the presenter demonstrates how to set up a Google Cloud Platform (GCP) cluster, including setting up networking and security. They then demonstrate how to add a workload and configure auto scaling.
16:10:00 This video tutorial demonstrates how to create a Google Cloud cluster using the Cloud Shell tool. The tutorial covers the following topics: configuring the cluster, retrieving cluster credentials, and deploying a serverless workload to the cluster.
16:15:00 In this video, the instructor explains how to build a docker image for a box of bow ties using the Google Cloud Platform and Cloud Build. Cloud Build is a serverless CI CD platform that allows you to package source code into containers and push them out to Google Cloud Container Registry.
16:20:00 This video shows how to pass the Google Cloud Associate Cloud Engineer Exam. The video covers how to configure a container image, deploy it to a Kubernetes cluster, and view the results.
16:25:00 This video shows how to deploy a Box of Bowties application on a Google Cloud Platform (GCP) cluster. The user first clones the Box of Bowties repository into a cloud shell environment, builds a container image using Cloud Build, pushes the image to container registry, creates a deployment using the image, and verifies the deployment using the Cube Ctl command line tool. They then launch a service of type low balancer to expose the application to the web.
16:30:00 This video explains how to scale a deployment of a workload on Google Cloud Platform, by scaling down the number of replicas and then scaling it back up again. Next, the instructor explains how to perform a rolling update of the application.
16:35:00 In this video, the instructor walks the viewer through the process of deploying a new application on Google Cloud Platform, using the gcloud command-line tool. This process includes scaling the application to accommodate more or fewer replicas, editing the application in the cloud shell editor, and rebuilding the container image using Cloud Build. Finally, the update is applied to the deployment, and the viewer can monitor the progress of the update using the deployment's status details.
16:40:00 In this video, the presenter covers the features of Cloud VPN, which is an essential service for any engineer looking to connect to Google Cloud. Cloud VPN securely connects your peer network to your vPC network through an encrypted tunnel, traversing the public internet. Cloud VPN is also a site-to-site VPN only, and does not support site-to-client connections. Cloud VPN can be used in conjunction with private Google Access for your on-premises hosts.
16:45:00 In this video, Google Cloud Associate instructor Kurt Wimmer discusses the Cloud VPN options available to Google Cloud users, including Classic VPN and HAVPN. He explains that Classic VPN offers a 99.9% SLA, while HAVPN offers a four-nines SLA. Classic VPN supports both static and dynamic routing, while HAVPN only supports dynamic routing. With Classic VPN, Google Cloud automatically chooses a single external IP address for the gateway interface, while with HAVPN, Google Cloud selects two external IP addresses automatically. Finally, Kurt Wimmer discusses how Cloud VPN works and compares and contrasts classic and HAVPN.
16:50:00 In this video, the instructor covers the different types of connections that exist between an on-premises environment and a Google Cloud VPC, including Cloud Interconnect. Cloud Interconnect is the most common connection type for organizations and offers fast, low-latency connections.
16:55:00 This video explains how to establish a dedicated interconnect connection between a vpc network and an on-premises network using a service provider. This connection type is useful if a dedicated interconnect co-location facility is not physically accessible or your workloads do not warrant an entire 10 gigabit per second connection. Additionally, 50 megabits per second to 50 gigabits per second vlan attachments are available with the maximum supported attachment size of 50 gigabits per second.
This video provides an introduction to the Google Cloud Associate Cloud Engineer Course, which covers how to deploy functions using the GCP console and the command line. The course also covers how to use Cloud Storage.
17:00:00 Google Cloud offers several connection types to allow developers to easily connect to its services. Cloud Interconnect is the best option for connecting to Google Cloud's data centers, and is recommended for applications that experience regular traffic fluctuations or newly deployed applications where you're unsure about the load. Cloud Interconnect is a dedicated physical connection right to Google's data centers, and is always the best option for connecting to Google Cloud.
17:05:00 The Google Cloud Associate Cloud Engineer Course covers how to route traffic to specific versions of an application in order to perform rollbacks or other temporary events, use traffic splitting to specify a percentage distribution of traffic across two or more of the versions within a service, and how to do a b testing or blue green deployment between your versions when rolling out new features. App Engine is available in two separate flavors, standard and flexible, and each environment offers its own set of features. Standard app engine is designed for sudden and extreme spikes of traffic and pricing is based on the vm resources and not on instance hours. Flexible app engine is designed for consistent traffic or for applications that experience regular traffic fluctuations. Deploying applications to app engine is simple using the gcloud app deploy command. App Engine services become loosely coupled and can communicate with each other.
17:10:00 In this video, Google Cloud associate cloud engineer course, the instructor discusses how app engine manages traffic, including traffic migration and traffic splitting.
17:15:00 In this lesson, Google Cloud Engineer Tony Bowtie covers app engine basics and demonstrates how to deploy a website application on the platform. Cloud shell is used to clone the repository and run the app deployment command. The app has two handlers: one to upload files to the cloud storage bucket and another that displays static files. The application is deployed to region "us-east-1" and verified.
17:20:00 This 1-hour video shows how to deploy a static website application to Google Cloud Platform using App Engine. The instructor demonstrates how to set up traffic splitting and diagnostics, as well as how to deploy a new version of the application.
17:25:00 This video teaches how to migrate traffic from one version of an appengine application to another version, and verify the deployment success.
17:30:00 In this video, Google Cloud Associate Cloud Engineer Course instructor Mark provides a walkthrough of how Cloud Functions work. After selecting the name and region for your function, you would select the trigger you wish to use. Cloud Functions also supports event-driven triggers, such as firestore and firebase. After setting up authentication and networking preferences, your written code can be put into the function. Cloud Functions are priced according to how long the function runs and how many resources are provisioned. Cloud Functions include a perpetual free tier which allows for 2 million executions.
17:35:00 Cloud functions are a serverless product from Google that allow users to process data. This video covers the binding of a trigger to a function, the automatic building of an image of the function, passing data to the function via parameters, and the limitations of functions. The next video in the series will show how to create and deploy a function.
17:40:00 This video explains how to deploy a Google Cloud function using the Cloud Console. The video also covers how to invoke the function using the Cloud Shell, and how to monitor function performance and logs.
17:45:00 This video provides an introduction to the Google Cloud Associate Cloud Engineer Course, which covers how to deploy functions using the GCP console and the command line. The course also covers how to use Cloud Storage.
17:50:00 The video discusses the basics of using Google Cloud Storage, specifically focusing on buckets and objects. It explains that buckets can contain any number of objects, and that you can change the default storage class for newly created objects. Finally, the video discusses how to manage permissions and access control for objects stored in buckets.
17:55:00 The Google Cloud Associate Cloud Engineer Course covers the basics of using Google Cloud Storage. Storage classes, buckets, and objects are all explained, and four storage options are described. Cloud storage is durable and reliable, and permissions can be controlled using standard IAM policies or access control lists.
This video provides an overview of how to manage objects in Google Cloud Storage using versioning and lifecycle management. The video discusses how to connect to a cloud sql instance, how to replicate databases, and how to enable HA for cloud sql.
18:00:00 In this lesson, the instructor covers object versioning and life cycle management features of Google Cloud Storage. These features help manage older files and save money on storage.
18:05:00 In this video, Google Cloud Associate Cloud Engineer Course instructor Stephen Brown demonstrates how object versioning works and how it can be helpful in managing costs. Cloud storage offers this feature as part of its lifecycle management feature, which allows you to specify rules for when current and older versions of an object should be updated or deleted. Lifecycle management can be used to support a variety of uses cases, like downgrading an object's storage class to save money, or deleting older versions of an object to save space.
18:10:00 This 1-minute video explains how to create a cloud storage bucket and upload files to it, using the Google Cloud console. The video also covers how to use the gsutil command line tool to manage cloud storage.
18:15:00 In this video, the instructor explains how to set up a Google Cloud account and create a bucket, files, and an instance. Next, the instructor shows how to copy files from an instance to a cloud storage bucket using the gsutil command. Finally, the instructor demonstrates how to use the gsutil command to copy files to and from a cloud storage bucket.
18:20:00 This video provides an overview of how to copy files from a local folder to a cloud storage bucket using the Google Cloud Associate Cloud Engineer Course's gsutil command line tool. The bucket is then made publicly available.
18:25:00 In this video, the Google Cloud Associate Cloud Engineer Course explains how to add public access to a bucket and then how to remove public access. Next, the course demonstrates how to create a signed url using the command line. Finally, the course shows how to use the cloud shell editor to upload and rename a key.
18:30:00 This video demonstrates the steps necessary to version and manage objects in a cloud storage bucket, including the use of the command line and the Cloud Shell. Versioning is enabled for the bucket, and the plaid bowtie.jpg file is deleted.
18:35:00 This YouTube video discusses how to use the gsutil and v commands to move and promote files. The video also discusses how to keep track of versioning for files.
18:40:00 This video demonstrates how to add and edit lifecycle rules for Google Cloud Storage. Lifecycle rules can delete non-current objects after seven days, move current files to a storage class that can save money, and set the storage class for archived objects not to change.
18:45:00 In this video, the instructor covers how to create and manage objects in Google Cloud Storage, using versioning and lifecycle management.
18:50:00 The video discusses the recommended methods for connecting to a cloud sql instance, which include using the cloud sql proxy and using private IP addresses. The video also discusses the recommended methods for database replication.
18:55:00 The video discusses the different types of clouds and how they work with cloud sql. It explains that to use cloud sql, you need an instance that meets certain requirements, including automated backups and binary logging. It also discusses how to promote a read replica or cross-region replica, should you need to in case of a primary instance becoming corrupted or unavailable. Finally, it mentions how HA works with cloud sql and how to enable it.
This video covers the basics of the Google Cloud Associate Cloud Engineer Course, including an overview of the different services offered and how to use them.
19:00:00 Cloud Spanner is a relational database service offered by Google that is designed to be highly scalable and consistent. Cloud Spanner is another database as a service offering and is similar to Cloud SQL in that it allows for querying and transactions, but differs in the way data is handled under the hood. Knowing this database at a high level is important for the exam.
19:05:00 Cloud Spanner is a database that is used by Google Cloud Platform, and is designed to achieve high availability and scale. Cloud Spanner uses replicas in different zones to keep data available in the event of a zone failure. Cloud Spanner uses sharding to improve performance and availability.
19:10:00 In this lesson, we discuss the four managednosql databases available in Google Cloud: Bigtable, Cloud Bigtable, Cloud Datastore, and Cloud Spanner. Cloud Bigtable is designed for massive scale workloads, low latency, and high throughput. Cloud Datastore is a redundant, scalable, document database for automated scaling and ease of application development. Cloud Spanner is a relational SQL database that is different than its cloud SQL cousin. Cloud Spanner can provide up to 10,000 queries per second.
19:15:00 Google Cloud offers a variety of features for storing data, including Cloud Datastore and Firestore. Cloud Datastore is ideal for applications that rely on highly available structured data, while Firestore is more suited for applications that need a flexible, scalable, and fast NoSQL cloud database. Cloud Firestore also offers a variety of security and management features.
19:20:00 This YouTube video provides an overview of the different big data ecosystems available on Google Cloud, including relational and NoSQL databases, as well as mobile application development platforms.
19:25:00 Google Cloud's bigquery service is a serverless data warehouse that enables scalable analysis over petabytes of data. It supports querying using SQL and holds built-in machine learning capabilities. You can load data into bigquery either by batch upload or streaming it in real time. bigquery also makes it easy to access this data by using the cloud console, the bq command line tool, or making calls to the bigquery rest api. bigquery provides strong security and governance controls with fine-grained controls through integration with identity and access management.
19:30:00 In this video, Google Cloud associate Cloud Engineer Course instructor Brian Han discusses the three cloud-based services that are covered in the course - BigQuery, PubSub, and Composer. BigQuery allows you to store and analyze petabytes of data, PubSub is a messaging service that allows you to send and receive messages between independent applications, and Composer is a managed workflow orchestration service that is built on Apache airflow.
19:35:00 In this video, Google Cloud Associate Cloud Engineer Course instructor, Jonathan Brownlee, introduces the Google Cloud Platform services data flow and data proc. He explains how these services work together to implement data processing pipelines. Brownlee also points out the strengths and weaknesses of each service. Finally, he provides an overview of Cloud Data Lab, a developer tool that uses open source notebooks to explore, analyze, transform, and visualize data.
19:40:00 This video covers the basics of Google Cloud's machine learning services. The video covers what machine learning is, what it can do, and when to use it. The video also covers the Google Cloud Site API and how to use it.
19:45:00 Google offers a variety of cloud-based machine learning services that can be used to perform various tasks, such as recognizing objects and faces in images, translating text, and recognizing sentiment in social media conversations.
19:50:00 In this lesson, the Google Cloud Associate Cloud Engineer Course instructor covers the different tools available in the Google Cloud Operation Suite, which includes monitoring, logging, and application diagnostics. He goes into detail on each product, starting with monitoring. Cloud monitoring collects measurements and metrics to help you understand how your applications and system services are performing. Cloud monitoring can then take the data provided and use pre-defined dashboards that require no setup or configuration effort. Cloud monitoring also gives you the flexibility to create custom dashboards that display the content you select. Cloud logging has an agent that sends system and application metrics to Cloud Monitoring. Finally, the instructor covers the best practices for using the Google Cloud Operation Suite.
19:55:00 The Google Cloud Associate Cloud Engineer Course covers topics such as cloud monitoring and logging, cloud functions, and debugger.
The Google Cloud Associate Cloud Engineer Course is a great way to learn about the different tools available for use on the Google Cloud Platform. The video includes information on the Google Cloud debugger and profiler, which can be extremely helpful when working with the platform.
20:00:00 This video provides a high level overview of the Google Cloud tools available for use on various platforms. The video includes information on the Google Cloud Associate Cloud Engineer Course, the Google Cloud debugger, and the Google Cloud profiler.
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