Kubernetes is the most popular container orchestration system and it was designed specifically with Google Cloud Platform integration in mind. In this advanced-level quest, you will get hands-on practice configuring Docker images and containers, deploying fully-fledged Kubernetes Engine applications, and integrating Slackbot and MongoDB databases with Kubernetes. This quest will teach you the practical skills needed for integrating container orchestration into your own workflow.
This lab shows how to perform basic operations in Cloud Spanner using the Google Cloud Platform Console. Watch the short video Get a Highly Consistent, Scalable Database Service with Cloud Spanner.
Cloud Bigtable is Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail. In this lab you'll use Bigtable with the cbt command line. Watch the short video Bigtable: Qwik Start - Qwiklabs Preview.
Containers are becoming a popular way to run and scale applications across multiple cloud providers or on both cloud and on-premise hardware. This lab provides a quick introduction to running a MongoDB database on Kubernetes Engine using Docker.
This lab leads you through the steps to perform basic audits of core AWS resources. You will use the AWS Management Console to understand how to audit the use of multiple AWS services, Amazon EC2, Amazon VPC, Amazon IAM, Amazon Security Groups, AWS CloudTrail and AWS CloudWatch. This lab will help you understand how you can extend your existing auditing objectives related to organizational Governance, Asset Configuration, Logical Access Controls, Operating Systems, Databases and Applications security configurations within AWS. The skills learned will help provide visibility; testability and automated audit evidence gather capabilities.
BigQuery is Google's fully managed, low cost analytics database. With BigQuery you can query many terabytes of data without having any infrastructure to manage or needing a DBA. In this lab, we will load a dataset into BigQuery and query it.
This lab demonstrates how to use AWS Elastic Beanstalk to deploy a simple Ruby on Rails application. In this lab, you will deploy an application that will describe your concept or idea and allow viewers to subscribe to be notified upon launch. The lab will cover using AWS Elastic Beanstalk with an Amazon RDS database to store subscriber email addresses.
This lab takes you through the steps of creating a SQLServer database using the Amazon Relational Database Service using the AWS Management Console, and then connecting to the database in AWS using Microsoft SQL Server Management Studio running on a Microsoft Windows server, also provided in the lab environment. Note: this lab has a longer startup time of 20 minutes to allow the RDS instance to fully launch and initialize. For the lab to function as written, please DO NOT change the auto assigned region.
This lab leads you through the steps to migrate a Microsoft SQL Server database from a pretend (on-premises) SQL server to a SQL Server in your AWS account. In this lab you will launch a Windows Server 2016 with SQL Server 2017 Express instance into a RemoteVPC. This instance will act as your on-premises SQL Server. You will Install Active Directory Services on your DC instance in your AWS LabVPC and promote it to be a Domain Controller. You will join your AWS SQL Server to your Domain. You will configure remote administrator access to your AWS SQL Server. This will allow you to migrate a database to it. You will install the AdventureWorks database to your Remote SQL Server. You will then migrate the AdventureWorks database from your Remote SQL Server to your AWS SQL Server. Finally, you will verify that the database migrated to the other SQL server by querying the database.
Amazon ElastiCache is a web service that helps improve the performance of web applications by allowing you to retrieve information from fast, managed, in-memory caches, instead of relying on slower disk-based databases. Amazon ElastiCache has no upfront costs. With on-demand nodes you pay only for the resources you consume by the hour without any long-term commitments. In this lab, you will use open source Landsat data and a MySQL database to illustrate the capabilities of ElastiCache with Redis.