Overview
In this hands-on lab you'll learn the differences between a network load balancer and an HTTP load balancer and how to set them up for your applications running on Compute Engine virtual machines (VMs).
Overview
You must complete a series of tasks within the allocated time period. Instead of following step-by-step instructions, you'll be given a scenario and a set of tasks - you figure out how to complete it on your own! An automated scoring system (shown on this page) will provide feedback on whether you have completed your tasks correctly.
Overview
Google Data Studio turns your data into informative dashboards and reports that are easy to read, easy to share, and fully customizable. Dashboarding allows you to tell great data stories to support better business decisions.
Overview
Google Kubernetes Engine (GKE) provides a managed environment for deploying, managing, and scaling your containerized applications using Google infrastructure. The Kubernetes Engine environment consists of multiple machines (specifically Compute Engine instances) grouped to form a container cluster. In this lab, you get hands-on practice with container creation and application deployment with GKE.
Overview
BigQuery is Google's fully managed, NoOps, low cost analytics database. With BigQuery you can query terabytes and terabytes of data without having any infrastructure to manage or needing a database administrator. BigQuery uses SQL, and you can take advantage of the pay-as-you-go model. BigQuery allows you to focus on analyzing data to find meaningful insights.
Overview
BigQuery is Google's fully managed, NoOps, low cost analytics database. With BigQuery you can query terabytes and terabytes of data without having any infrastructure to manage or needing a database administrator. BigQuery uses SQL and can take advantage of the pay-as-you-go model. BigQuery allows you to focus on analyzing data to find meaningful insights.
Overview
Storing and querying massive datasets can be time consuming and expensive without the right hardware and infrastructure. BigQuery is an enterprise data warehouse that solves this problem by enabling super-fast SQL queries using the processing power of Google's infrastructure. Simply move your data into BigQuery and let us handle the hard work. You can control access to both the project and your data based on your business needs, such as giving others the ability to view or query your data.
Overview
SQL (Structured Query Language) is a standard language for data operations that allows you to ask questions and get insights from structured datasets. It's commonly used in database management and allows you to perform tasks like transaction record writing into relational databases and petabyte-scale data analysis.
Overview
In this lab, you create and deploy a simple App Engine application using a virtual environment in the Google Cloud Shell.
Google Could Self-Paced (GSP) Labs 001 - Creating a Virtual Machine
Google Could Self-Paced (GSP) Labs 002 - Getting Started with Cloud Shell and gcloud
Overview
In this lab, you create a Google Kubernetes Engine cluster containing several containers, each containing a web server. You place a load balancer in front of the cluster and view its contents.
Overview
In this lab, you create a Cloud Storage bucket and place an image in it. You'll also configure an application running in Compute Engine to use a database managed by Cloud SQL. For this lab, you will configure a web server with PHP, a web development environment that is the basis for popular blogging software. Outside this lab, you will use analogous techniques to configure these packages.
You also configure the web server to reference the image in the Cloud Storage bucket.
Overview
In this lab, you will create virtual machines (VMs) and connect to them. You will also create connections between the instances.
Overview
In this lab, you use Cloud Marketplace to quickly and easily deploy a LAMP stack on a Compute Engine instance. The Bitnami LAMP Stack provides a complete web development environment for Linux that can be launched in one click.
If I want to check that how many MBps traffic and top 10 IPs from source IP 10.20.33.39?
AWS TGW Reference Architectures for Multi-VPC - 5/5 - Backhaul to On-Premises Traffic
To get traffic from on-premises resources to AWS EC2, we can use VPN connections or AWS Direct Connect.
For VPN connections from on-premises gateways connect to the TGW as a VPN attachment.
Multiple tunnels and ECMP provide resiliency.
AWS TGW Reference Architectures for Multi-VPC - 4/5 - East-West Traffic
East-west traffic, or traffic between VPCs, flows through the NGFW in the security VPC.
I will share how to SSH from one Linux EC2 instance to another using the target EC2 instance's Private IP address.
3. AWS TGW Reference Architectures for Multi-VPC - 3/5 - Outbound Traffic
This design uses overlay routing for outbound security on the NGFW.
Outbound traffic from EC2 in the WEB VPCs traverses the TGW and egresses the AWS environment through the NGFW.
2. AWS TGW Reference Architectures for Multi-VPC - 2/5 - Inbound Traffic
Inbound traffic originates outside the VPC, such as the Internet, and is destined to applications or services hosted within your VPCs, such as web servers.
When traffic go out from ELB, does source IP (SIP), destination IP (DIP), Source port (SP) and destination port (DP) will be change?
The architecture will share 5 topics:
1. AWS TGW Reference Architectures for Multi-VPC - 1/5 - Brief
2. AWS TGW Reference Architectures for Multi-VPC - 2/5 - Inbound Traffic
3. AWS TGW Reference Architectures for Multi-VPC - 3/5 - Outbound Traffic
4. AWS TGW Reference Architectures for Multi-VPC - 4/5 - East-West Traffic
5. AWS TGW Reference Architectures for Multi-VPC - 5/5 - Backhaul to On-Premises Traffic
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