In this learning path you will learn how to design and architect solutions using various services in Microsoft Azure and prepare for passing exam 70-535 architecting Azure Solutions. This exam will help prepare you for MCSA or MCSE certification with Azure.
In this learning path, you will learn the basics of cloud computing and the fundamentals of Azure. Topics will include the basics of cloud economics, platform as a service (PaaS), infrastructure as a service (IaaS) as well as built in capabilities in the platform for monitoring and management including basic concepts in DevOps and Automation.
Learn how to architect advanced solutions using Microsoft Azure Cloud Workshops. These hands-on labs are typically for intermediate to advanced users and take anywhere from 3-6 hours of time to complete. Happy Learning!
This course introduces a couple of application integration services offered by AWS. Simple Queue Service (SQS) is a message queuing service whereas Simple Notification Service (SNS) is the messaging service. Both services offer decoupling of distributed systems and microservices.
This course introduces a couple of other compute services offered by AWS. Elastic Beanstalk service enables you to upload your web application code, and it automatically takes care of deployment and management. Lambda service enables you to run your code without provisioning and managing any servers which means zero administration.
This is a comprehensive coverage of EC2, as it is a major topic across the exam. This course starts with the launching of EC2 instances, configuring access to them, setting security followed by EBS volumes and their encryption. This course then discusses load balancers, the auto scaling feature and command line interface.
This course instructs you on Route 53, the DNS service from AWS (as it shows the different policies available), how to register a domain name as well as routing setup to your EC2 instances. This course introduces CloudFront, AWS’ Content Delivery Network (CDN) service and demonstrates how to create a CDN and use it with S3 to serve a static website. API Gateway service enables you in creating and managing an API for applications running in AWS resources. Direct Connect service enables you in establishing a dedicated private network connection between AWS and your on-premises datacenter.
This course discusses storage on AWS on different levels and usages. This course guides through S3 and Glacier to include identifying the use case for each, using version control and region replication, and the lifecycle on S3. Storage Gateway, Snowball and their usages are also covered in this course.
This course introduces the architecture of default VPC and the creation of VPC with CIDR notation. This course covers the routing and security features such as Route Table, Network Access Controls Lists and Security Groups. It also introduces you to NAT gateways and NAT instances as well as features such as VPC Peering and VPC Flow Logs.
In this module, attendees will learn how to use features and capabilities within Azure to architect solutions to apply governance at scale with Microsoft Azure. This will include architecting the Azure EA portal for delegated access and charge back and discuss features like implementing role based access control (RBAC), and resource manager policies to enable enterprise control of an Azure deployment.
In this module, the attendee will learn the core capabilities and use cases of Azure Active Directory (AD). This module will emphasize strategies and techniques for integrating on-premises Active Directory with an Azure AD environment
In this module, attendees will learn about the capabilities of the Azure networking stack for connecting networks. This module will focus on capabilities and use cases so the student will be able to make an educated decision on connectivity requirements.
In this module, attendees will learn how to design solutions using Azure Infrastructure as a Service Components. This module will focus on core capabilities, use cases, and general best practices as well as discuss peripheral services such as Azure Backup and Site Recovery.
The Architecting Cloud Connectivity course covers general information about the Azure network, and specific topics related to designing hybrid connectivity solutions. Several example architectures are considered, evaluating key design criteria, such as performance and scale, security and compliance, and cost optimization. This course should help in preparation for the 70-534 exam, Architecting Microsoft Azure Solutions.
The Architecting Global Solutions course covers general information about scaling and architecting for scale. After the overview, the course dives deeper into the techniques of scaling solutions globally using Azure services. The topics and services discussed in this course include: ARR Affinity, Azure Redis Cache, Azure Content Delivery Network (CDN), Azure Traffic Manager, Auto-Healing, and Asynchronous Programming. Finally, this course finishes with an overview of a few example architectures to give a better perspective on architecting global solutions in the cloud. This course should help in preparation for the 70-534 exam, Architecting Microsoft Azure Solutions.
In this module, attendees will learn how to design and scale web applications using Microsoft Azure. This module will discuss deployment and continuous integration as well as scale factors such as CDN, Caching and multi-region design.
This course covers the importance of AWS certification, the process of scheduling the exam, its structure and question types, and it provides references to the practice tests.
This course dives into using various management tools offered by AWS. CloudWatch is the monitoring service which helps you in monitoring your AWS resources. CloudTrail service enables you in logging and monitoring the event history of your AWS account. CloudFormation service enables you in describing your infrastructure and provisioning the resources. Trusted Advisor helps in optimizing your environment, reducing cost, increasing performance and improving the security of your AWS resources.
This course is centralized on IAM’s role across AWS services and how it is used to provide authentication, authorization and access control to all other components. It also covers features such as Multi-Factor Authentication (MFA) and Secure Token Service (STS).
This course dives into the various categories of AWS Whitepapers. The most important category, the Well-Architected Framework, has been developed to help Cloud Architects build the most secure, high-performing, resilient, and efficient infrastructure possible for their applications. This framework provides a consistent approach for customers and partners to evaluate architectures, and it provides guidance to help implement designs that will scale with your application needs over time.
This course introduces key concepts for cloud computing and how Microsoft Azure aligns with those scenarios. Students are introduced to several key Azure services and solutions that align with the following technical disciplines including Infrastructure as a Service, Hybrid Cloud, Application Development, and Big Data and Analytics.
This module will cover all aspects of big data storage and batch processing. We will start by making the case for big data in Azure. Then we will look at Azure service topics to include Blob Storage, Azure Data Lake Store, Azure Data Lake Analytics, and HDInsight clusters running Hadoop, Hive, Interactive Hive (LLAP) and Spark. Storage topics will focus on choosing the right storage, configuring storage and storage optimization. We will also cover Big Data scenarios including batch processing, interactive clusters, multi-cluster deployments and on-demand clusters.
In this module, attendees will learn about the various storage options from SQL Database to NoSQL and Document based database technologies. This module is focused on choosing the right tool for the right job and considering the decision points architects will make when designing storage for their apps.
In this course, you will learn how to create web apps by using various Azure Platform as a Service components as as well as understand how to use Azure Container-based services.This course is part of the AZ 300 learning path for Microsoft Azure Architect Technologies.
Students will learn how to analyze resource utilization and consumption, create and configure storage accounts, create and configure a VM for Windows and Linux, create connectivity between virtual networks, implement and manage virtual networking, manage Azure Active Directory, and implement and manage hybrid identities.This course is part of the AZ 300 learning path for Microsoft Azure Architect Technologies.
This is course four of the exam prep for AZ-301: Microsoft Azure Architect Design. Students will learn to design a Site Recovery Strategy, design for High Availability, design a disaster recovery strategy for individual workloads and design a Data Archiving Strategy.
In this course the student will learn how to design a data management strategy, design a data protection strategy, design and document data flows, and design a monitoring strategy for the data platform.
In the course the student will learn about designing a storage strategy, networking strategy, compute strategy, and monitoring strategy for infrastructure.
This is course five of the exam prep for AZ-301: Microsoft Azure Architect Design. Students will learn how to design deployments, design migrations and design API integration strategy in Microsoft Azure.
This is course two of the exam prep for AZ-301: Microsoft Azure Architect Design.The Design for Identity and Security course teaches design identity management, design authentication, design authorization, design for risk prevention and identity, and how to design a monitoring strategy for identity and security.
In this module, attendees will learn how to develop IoT solutions using solutions and services in Microsoft Azure. Topics will include device specific protocols, IoT Hub and data ingestion strategies.Design for IoT
In this module, attendees will learn how to develop media/video based solutions and services in Microsoft Azure. This will include Azure Media Services, video indexer, video API, computer vision API, and other media related services.
In this module, attendees will learn how to build loosely coupled applications using message based architectures using technologies such as Event Grid, Storage Queues and Service Bus Queues and Topics.
In this course, you will learn the ins-and-outs of using Azure Functions to design highly scalable solutions using a serverless design. This course will teach you how to deploy your code as well as how to monitor it once it is in production along with general best practices for writing solutions with Azure Functions.
This is course one of the exam prep for AZ-301: Microsoft Azure Architect Design. This course covers a range of topics, including the gathering of information and workload requirements, how to optimize a consumption strategy, and how to design an auditing and monitoring strategy.
This course will expose the student to developing solutions that use Cosmos DB storage, developing solutions that use a relational database, configuring a message-based integration architecture, and how to develop for autoscaling.This course is part of the AZ 300 learning path for Microsoft Azure Architect Technologies.
In this course, you will build on concepts introduced in Architecting on AWS. You will learn how to build complex solutions that incorporate data services, governance, and security on the AWS platform. You will also learn about specialized AWS services, including AWS Direct Connect and AWS Storage Gateway, that support hybrid architecture, and you will learn about best practices for building scalable, elastic, secure, and highly available applications on AWS.This course will prepare for: AWS Certified Solutions Architect – Professional
The Azure IaaS and Hybrid Architect workshop is designed to prepare the architect to design solutions with Microsoft Azure. This workshop is focused on designing solutions using Infrastructure as a Service (IaaS) and other technologies to enable hybrid solutions such as data center connectivity, hybrid applications, and other hybrid use cases such as business continuity with backup and high availability. Individual case studies will focus on specific real-world problems that represent common IaaS and Hybrid scenarios and practices. Students will also experience several hands-on labs to introduce them to some of the key services available.
The Architecting Azure Big Data and Analytics course is designed to give students a clear architectural understanding of the application of big data patterns in Azure. Students will participate in team based architectural planning and hands-on implementation sessions. Students will be taught basic Lambda architecture patterns in Azure, leveraging the scalability and elasticity of Azure in Big Data and IoT solutions as well as an introduction to cognitive services, machine learning, and artificial intelligence (AI).An introduction to data science techniques in Azure will also be covered. Individual case studies will focus on specific real-world problems that represent common big data patterns and practices. Students will also experience several hands-on labs to introduce them to some of the key services available.
The Azure Modern Apps and IoT Architect workshop is designed to prepare the architect to design solutions with Microsoft Azure. This workshop is focused on designing solutions using Platform as a Service (PaaS) and Serverless Services in Azure to build new web, solutions as well as highly scalable and globally available applications. This workshop will also focus on architecting IoT based solutions with real-time data ingestion and processing in Azure. Students will also experience several hands- on labs to introduce them to some of the key services available.
This course covers the fundamentals of building IT infrastructure on the AWS platform. Students learn how to optimize the AWS Cloud by understanding how AWS services fit into cloud-based solutions. In addition, students explore AWS Cloud best practices and design patterns for architecting optimal IT solutions on AWS, and build a variety of infrastructures in guided, hands-on activities. The course also covers how to create fledgling architectures and build them into robust and adaptive solutions.This course will prepare for: AWS Certified Solutions Architect - Associate
The SAP on Azure workshop is designed to prepare the architect to design SAP solutions on Microsoft Azure. This workshop is focused on designing solutions using Infrastructure as a Service (IaaS) and other technologies to enable SAP on Azure solutions. Individual case studies will focus on specific real-world problems that represent common IaaS and Hybrid scenarios and practices. Students will also experience several hands-on labs to introduce them to some of the key services available.
This two-day instructor-led class equips you to build highly reliable and efficient solutions on Google Cloud Platform. It is a continuation of the Architecting with Google Cloud Platform: Infrastructure course and assumes hands-on experience with the technologies covered in that course. Through a combination of presentations, demos, and hands-on labs, you will learn to design GCP deployments that are highly reliable and secure as well as how to operate GCP deployments in a highly available and cost-effective manner.
This three-day instructor-led class introduces you to the comprehensive and flexible infrastructure and platform services provided by Google Cloud Platform. Through a combination of presentations, demos, and hands-on labs, you will explore and deploy solution elements, including infrastructure components such as networks, systems and applications services. This course also covers deploying practical solutions including securely interconnecting networks, customer-supplied encryption keys, security and access management, quotas and billing, and resource monitoring.
Master the skills needed to design solutions that run on Azure. A Microsoft Azure solution architect must have expertise in compute, network, storage, and security.
In this course, you will learn about cloud-based Big Data solutions such as Amazon EMR, Amazon Redshift, Amazon Kinesis, and the rest of the AWS Big Data platform. We will show you how to use Amazon EMR to process data using the broad ecosystem of Hadoop tools like Hive and Hue. We will also teach you how to create Big Data environments, work with Amazon DynamoDB, Amazon Redshift, Amazon QuickSight, Amazon Athena, and Amazon Kinesis, and leverage best practices to design Big Data environments for security and cost-effectiveness.This course will prepare for: AWS Certified Big Data - Specialty
Learn what Google Cloud technology makes possible through three distinct lenses: technology, economics, and security. A fourth lens helps you rethink optimization by leading a people-first culture of innovation. While working in groups, explore machine learning use cases to define a concrete transformation vision for your business. This vision will take into account all cloud adoption phases so that you can mobilize your teams to work in tandem toward business acceleration while reducing costs.
This four-day instructor-led class provides you with a hands-on introduction to designing and building data processing systems on Google Cloud Platform. Through a combination of presentations, demos, and hand-on labs, you will learn how to design data processing systems, build end-to-end data pipelines, analyze data and carry out machine learning. The course covers structured, unstructured, and streaming data.
This two-day, instructor-led course teaches participants how to derive insights through data analysis and visualization using the Google Cloud Platform. The course features interactive scenarios and hands-on labs where participants explore, mine, load, visualize, and extract insights from diverse Google BigQuery datasets. The course covers data loading, querying, schema modeling, optimizing performance, query pricing, and data visualization.
In this course, application developers learn how to design, develop, and deploy applications that seamlessly integrate components from the Google Cloud ecosystem. Through a combination of presentations, demos, and hands-on labs, participants learn how to use GCP services and pre-trained machine learning APIs to build secure, scalable, and intelligent cloud-native applications.
In this course, you will learn how to use the AWS SDK to develop secure and scalable cloud applications. We will explore how to interact with AWS using code and discuss key concepts, best practices, and troubleshooting tips.This course will prepare for: AWS Certified Developer - Associate
In this course, you will learn the most common DevOps patterns to develop, deploy, and maintain applications on the AWS platform. We will explore the core principles of the DevOps methodology and examine a number of use cases applicable to startup, small- to medium-sized business, and enterprise development scenarios.This course will prepare for: AWS Certified DevOps Engineer - Professional
Learn to containerize workloads in Docker containers, deploy them to Kubernetes clusters provided by Google Container Engine, and scale those workloads to handle increased traffic. You also learn how to continuously deploy new code in a Kubernetes cluster to provide application updates.
This one-day instructor-led course introduces participants to the big data capabilities of Google Cloud Platform. Through a combination of presentations, demos, and hands-on labs, you will get an overview of the Google Cloud platform and a detailed view of the data processing and machine learning capabilities. This course showcases the ease, flexibility, and power of big data solutions on Google Cloud Platform.
This one-day instructor-led class provides an overview of Google Cloud Platform products and services. Through a combination of presentations, demos, and hands-on labs, you will learn the value of Google Cloud Platform and how to incorporate cloud-based solutions into business strategies.
This course demonstrates how to efficiently use AWS security services to stay secure in the AWS Cloud. The course focuses on the security practices that AWS recommends for enhancing the security of your data and systems in the cloud. The course highlights the security features of AWS key services including compute, storage, networking, and database services. You will also learn how to leverage AWS services and tools for automation, continuous monitoring and logging, and responding to security incidents.
In this course, you will learn how to create automatable and repeatable deployments of networks and systems on the AWS platform. We will explore the AWS features and tools related to configuration and deployment and best practices for configuring and deploying systems.This course will prepare for:AWS Certified SysOps Administrator - Associate
Learn how to Implement authentication in applications (certificates, Azure AD, Azure AD Connect, token-based), implement secure data (SSL and TLS), and manage cryptographic keys in Azure Key Vault.This course is part of the AZ 300 learning path for Microsoft Azure Architect Technologies.
Students will learn how to migrate servers to Azure, configure serverless computing, implement application load balancing, integrate on-premises network with Azure virtual network, manage role-based access control (RBAC) and implement Multi-Factor Authentication (MFA).This course is part of the AZ 300 learning path for Microsoft Azure Architect Technologies.
This course covers the contents to the learning plan as well as how it is organized. It also introduces you to the AWS Certification and its requirements.
This course explores the NoSQL storage options available within the Microsoft Azure Cosmos DB database service. Formerly DocumentDB, Azure Cosmos DB is no longer just a Document-based NoSQL store, and it includes support for all 4 primary NoSQL data models (Document, Graph, Key/Value, Column). In addition to learning about NoSQL with Cosmos DB, students will also learn about the cloud-native features that make Cosmos DB a great NoSQL database-as-a-service in the Microsoft Azure cloud.
This course provides a high-level introduction to the AWS platform, available components and services. Included is a brief description for each service to get you acquainted to the offerings.
In this module, attendees will learn how to use services in Azure to monitor their services and solutions and to compose solutions that will effectively alert and trigger actions based on the established parameters. This module will discuss using the following services and solutions:Monitoring - Azure Monitor, Health, Log Analytics, Security Center, Application Insights, Network Watcher Automation - Chef, Puppet, PowerShell DSC, Logic Apps, Event Grid
The Real-Time Ingestion and Processing in Azure course covers information about implementing real-time event stream ingestion and processing within Microsoft Azure. The course starts with an overview of the Lambda Architecture and what a Message Broker is used for. The course continues to cover the Azure Event Hubs and Azure IoT Hub services used for event stream ingestion, and Azure Stream Analytics and HDInsight for integrating real-time event processing. Finally, the course finishes with an overview of a few example architectures to give a better perspective on architecting Real-Time Ingestion and Processing solutions within the Microsoft Azure cloud. This course should help in preparation for the 70-534 exam, Architecting Microsoft Azure Solutions.
In this lab, you will create a new Azure Function that exposes an HTTP endpoint to enable the function to be triggered on-demand. The HTTP endpoint accepts two query string parameters from the HTTP request. The function outputs a calculated value based on the input parameters.
In this hands-on lab, you will implement many of the Azure Security Center features to secure their cloud-based Azure infrastructure (IaaS) and applications (PaaS). Specifically, you will ensure that any internet exposed resources have been properly secured and any non-required internet access disabled. Additionally, you will implement a “jump machine” for admins with Application Security enabled to prevent admins from installing non-approved software and potentially exposing cloud resources. You will then utilize custom alerts to monitor for TCP/IP Port Scans and then fire alerts and run books based on those attacks.
In this workshop, you will deploy a web app using Machine Learning Services to predict travel delays given flight delay data and weather conditions. Plan a bulk data import operation, followed by preparation, such as cleaning and manipulating the data for testing, and training your machine learning model.At the end of this workshop, you will be better able to build a complete machine learning model in Azure Databricks for predicting if an upcoming flight will experience delays. In addition, you will learn to store the trained model in Azure Machine Learning Model Management, then deploy to Docker containers for scalable on-demand predictions, use Azure Data Factory (ADF) for data movement and operationalizing ML scoring, summarize data with Azure Databricks and Spark SQL, and visualize batch predictions on a map using Power BI.
Contoso has asked you to deploy their infrastructure in a resilient manner to insure their infrastructure will be available for their users and gain an SLA from Microsoft. In this hands-on lab, you will take an existing deployment in Azure and re-architect it for resiliency.
This hands-on lab is designed to guide you through the process of building and deploying Docker images to the Kubernetes platform hosted on Azure Kubernetes Services (AKS), in addition to learning how to work with dynamic service discovery, service scale-out, and high-availability.At the end of this lab you will be better able to build and deploy containerized applications to Azure Kubernetes Service and perform common DevOps procedures.
In this hands-on lab, you will learn how to implement a solution with a combination of Azure Resource Manager templates and Azure DevOps to enable continuous delivery with several Azure PaaS services.
Woodgrove Bank, who provides payment processing services for commerce, is looking to design and implement a proof-of-concept (PoC) of an innovative fraud detection solution. They want to provide new services to their merchant customers, helping them save costs by applying machine learning and advanced analytics to detect fraudulent transactions. Their customers are around the world, and the right solutions for them would minimize any latencies experienced using their service by distributing as much of the solution as possible, as closely as possible, to the regions in which their customers use the service.
World Wide Importers (WWI) has experienced significant growth in the last few years. In addition to predictable growth, they’ve had a substantial amount of growth in the data they store in their data warehouse. Their data warehouse is starting to show its age; slowing down during extract, transform, and load (ETL) operations and during critical queries. It was built on SQL Server 2008 R2 Standard Edition.The WWI CIO has recently read about new performance enhancements of Azure SQL Database and SQL Server 2017. She is excited about the potential performance improvements related to clustered ColumnStore indexes. She is also hoping that table compression will improve performance and backup times.WWI is concerned about upgrading their database to Azure SQL Database or SQL Server 2017. The data warehouse has been successful for a long time. As it has grown, it has filled with data, stored procedures, views, and security. WWI wants assurance that if it moves its data store, it won’t run into any incompatibilities with the storage engine of Azure SQL Database or SQL Server 2017.WWI’s CIO would like a POC of a data warehouse move and proof that the new technology will help ETL and query performance.Note: This lab provisions infrastructure and takes approximately 20 minutes to start.
In this hands-on lab, you are working with Trey Research to setup some best practices regarding policies, permissions, and remote access to their network. Tasks include creating scripts that Enterprise IT will use to automatically set policy and delegate permissions when a new subscription is created. You will help them solve a critical problem for on-boarding new developers and controlling access to what they can access on the network. At the end of this hands-on lab, you will know how to provide cost tracking by business unit, environment and project, provide for a distributed administration model, put a service catalog in place to prevent deployment of unsupported Azure services, and put controls in place to allow deployment of services only in specific regions.This Real Time Lab requires your own Azure subscription where you have Owner and Global Administrator rights.
In this lab, you will use the Azure Migrate service to migrate the SmartHotel app which is currently hosted on an on-premises infrastructure hosted in Hyper-V to Azure Virtual Machines. During the lab, you will migrate this entire application stack to Azure using the Azure Migrate Service. Note: this lab takes up to 60 minutes to fully deploy.
In this hands-on lab you will migrate an existing on-premises enterprise data warehouse to the cloud. You will investigate the current data warehouse to identify any incompatibilities, export the data from the on-premises data warehouse, and transfer it to an Azure Blob Storage. You will then load the data into the warehouse using Polybase. Finally, you will integrate the warehouse by migrating ETL to Azure Data Factory and supporting ad-hoc access by implementing Azure Analysis Services.
In this lab, you will build and deploy an end-to-end e-commerce site that provides order processing and receipt generation capabilities using modern PaaS services from Azure. This lab will explore Azure App Services, SQL Database, Azure Functions and Logic Apps.
In this hand-on lab, you will be challenged to implement an end-to-end scenario using a supplied sample that is based on Microsoft Azure Functions, Azure Cosmos DB, Event Grid, and related services. The scenario will include implementing compute, storage, workflows, and monitoring, using various components of Microsoft Azure. The hands-on lab can be implemented on your own, but it is highly recommended to pair up with other members at the lab to model a real-world experience and to allow each member to share their expertise for the overall solution.At the end of the hands-on-lab, you will have confidence in designing, developing, and monitoring a serverless solution that is resilient, scalable, and cost-effective.
In this hands-on lab, you will build a disaster recovery site for an on-premises environment. You will enhance the existing database solution to support a hybrid cloud-based disaster recovery solution, implement an archiving strategy and a backup/restore strategy designed to protect data.
This hands-on lab is designed to provide exposure to many of Microsoft's transformative line of business applications built using Microsoft advanced analytics. The goal is to show an end-to-end solution, leveraging many of these technologies, but not necessarily doing work in every component possible.By the end of the hands-on lab, you will be more confident in the various services and technologies provided by Azure, and how they can be combined to build a real-time chat solution that is enhanced by Cognitive Services.
In this advanced hands-on lab, you will determine the appropriate hosting tiers for the Contoso Financial application and estimate the total cost savings on a monthly and annual basis. You will implement and integrate Azure Traffic Manager, then migrate the Web, API and Background App Tiers of the application to the Azure App Service. Next, you will then de-commission the old application infrastructure, and setup geo-replication for the Azure SQL Database in preparation for the next step, which is deploying a European instance of the Web App Tier. Finally, you will add an endpoint for this new Web App Tier to the Azure Traffic Manager.
In this lab you will create an Azure SQL Database using the Azure Portal and connect to it using SQL Server Management Studio. You will then migrate a SQL Server database hosted on a virtual machine to an Azure SQL Database.
In this lab, you will create a Windows virtual machine running in Azure, and connect to it using Remote Desktop. You will then delete the virtual machine, and clean up associated resources.
Today, data is being collected in ever-increasing amounts, at ever-increasing velocities, and in an ever-expanding variety of formats. This explosion of data is colloquially known as the Big Data phenomenon.In order to gain actionable insights into big-data sources, new tools need to be leveraged that allow the data to be cleaned, analyzed, and visualized quickly and efficiently. Azure HDInsight provides a solution to this problem by making it exceedingly simple to create high-performance computing clusters provisioned with Apache Spark and members of the Spark ecosystem. Rather than spend time deploying hardware and installing, configuring, and maintaining software, you can focus on your research and apply your expertise to the data rather than the resources required to analyze that data.Apache Spark is an open-source parallel-processing platform that excels at running large-scale data analytics jobs. Spark’s combined use of in-memory and disk data storage delivers performance improvements that allow it to process some tasks up to 100 times faster than Hadoop. With Microsoft Azure, deploying Apache Spark clusters becomes significantly simpler and gets you working on your data analysis that much sooner.In this lab, you will experience HD Insight with Spark first-hand. After provisioning a Spark cluster, you will use the Microsoft Azure Storage Explorer to upload several Jupyter notebooks to the cluster. You will then use these notebooks to explore, visualize, and build a machine-learning model from food-inspection data — more than 100,000 rows of it — collected by the city of Chicago. The goal is to learn how to create and utilize your own Spark clusters, experience the ease with which they are provisioned in Azure, and, if you're new to Spark, get a working introduction to Spark data analytics.
In this lab, you will learn to build, monitor, manage and troubleshoot data pipelines with Azure Data Factory V2. You will learn to use the Copy Data wizard to build pipeline with no coding. You will build a custom pipeline to copy data from Blob storage to a table in Azure SQL Database. You will build a tumbling window pipeline to pick up data on a daily basis. Finally, you will learn to use the Management Monitoring tools to troubleshoot pipeline failures.
In this lab, an AKS cluster is deployed using the Azure CLI. A multi-container application consisting of web front end and a Redis instance is then run on the cluster. Once completed, the application is accessible over the internet.
In this hands-on lab, you will deploy an app to an Azure Web App (Linux) and Azure Database for MySQL from a repository in GitHub. From there, you will deploy a Jenkins server and setup continuous integration, delivery and deployment with the newly deployed web app.
In this lab, an Azure Virtual Machine disk will be encrypted using the following steps:Deploy a VM into Azure that is not encryptedObtain and run the Azure Disk Encryption Prerequisites Azure PowerShell scriptEncrypt your virtual machines
In this lab, you will create a virtual network that will allow the virtual machines you create to securely connect with each other. You will then create two virtual machines and specify the virtual network configuration and the availability set configuration along with storage for the virtual machine.
In this lab, you will create an Azure Web App and a SQL Database and configure the popular content management system (CMS) Orchard CMS. You will then configure the web app to automatically scale based on actual CPU usage.
This lab is designed to help you become familiar with several features of Microsoft Azure Log Analytics. You will learn how to setup a Log Analytics workspace and install the agent on several VMs. From there, you will configure data sources from Azure as well as diagnostic data from the VMs and learn the fundamentals of querying data and events using the Log Analytics query language.
In this lab, you learn about the deploying A Test VM and configuring Azure Monitor on that VM by applying some condition and action items. If the VM reaches the defined thresholds, Azure Monitor will generate alerts.
In this lab, you will configure Azure Site Recovery to protect a sample n-tier application by configuring replication from the source Azure region to a target Azure region. Once the initial replication has completed and the application is protected, you will perform a test fail over and validate application functionality. Finally, you will accomplish the cleanup of the test failover resources.Note: This lab pre-deploys several resources and will take 15-20 minutes to start.
In this lab, you will be introduced to basic concepts for developing with Azure Storage using Visual Studio 2017 and C#.
In this lab, the student will learn the basics of messaging patterns between software systems and how to use the Azure Service Bus as a messaging solution.
In this lab, you will use Visual Studio and ASP.NET to learn how to use Cosmos DB as a backend for an MVC application. You will learn how to programmatically read and write data, create and call a user-defined functions as well as understand management capabilities such as users and permissions, monitoring and scalability options.
In this lab, you will learn how to configure and manage an Azure Cosmos DB Account (formerly Azure DocumentDB), including how to query and manage JSON documents within a Collection. Among the topics covered are using SQL language syntax to perform document queries that return JSON results, and implementing and testing global data replication and fail over.
In this lab you will learn how to migrate an traditional three-tier web application (web, business logic, and data) from on-premises to Azure using Azure Site Recovery and Azure Database Migration Service.Note: This lab pre-deploys several resources and will take 20-30 minutes to start.
In this lab, you learn how to configure virtual networking peering.Virtual network peering enables you to seemlessly connect two Azure virtual networks. Once peered, the virtual networks appear as one, for connectivity purposes. The traffic between virtual machines in the peered virtual networks is routed through the Microsoft backbone infrastructure, much like traffic is routed between virtual machines in the same virtual network, through private IP addresses only.Note 1: This lab will connect two virtual networks within the same region. Peering across regions is currently in preview.Note 2: If you want a more in-depth view of virtual network connectivity (including site-to-site and point-to-site) try the Introduction to Virtual Network Connectivity lab.
In this lab, you will use Java to write a back-end console application and register it with Azure Active Directory. You will then create a Key for the Registered app, and write code to generate an Access Token for the application to use when calling the Azure AD Graph API. Code will also be written to call the Azure AD Graph REST API from within Java using the Access Token for authentication.
In this hands-on lab, you will first deploy a simple web application and database to Azure IaaS VMs, using a resource manager template and Azure Automation DSC. You will then configure a range of infrastructure management capabilities on this deployment, including Update Management, Security Center, Service Map, Change Tracking and Application Insights. You will use Azure Monitor to configure application alerts and send, via both email and mobile application notifications. You will also learn how to further investigate infrastructure status using Log Analytics queries. In doing so, you will learn both how to deploy these solutions and be introduced to their capabilities.