Cloud & DevOps Training in Morocco

1. Overview of Azure machines

• Virtual machines (VMs): Overview and features.
• Planning considerations: Criteria to take into account for optimal VM management.

2. Creating virtual machines

• Overview of the creation process: Key steps to create a VM.
• Creation with different tools:
  • Azure portal.
  • PowerShell scripts.
  • ARM (Azure Resource Manager) templates.

3. Deploying virtual machine images

• Custom images: Deployment and management.
• Linux VMs: Specific configuration and deployment.

4. Configuring virtual machines

• Network configuration: Network connections and IP management.
• Storage configuration: Optimising resources for maximum performance.

5. Implementing high availability

• Availability and scalability: Setting up robust, scalable solutions.
• VM extensions: Integrating and managing Azure extensions.

6. Managing and monitoring virtual machines

• Introduction to virtual networks (VNet): Basic concepts.
• Creating and configuring Azure virtual networks:
  • IP addressing.
  • Routing.
• Azure DNS:
  • Overview of DNS services.
  • Implementation:
    • Domains.
    • DNS zones.
    • Record types.
    • Name resolution methods.

7. Connecting virtual networks

• Cross-site connectivity (VNet-to-VNet): Configuration and use cases.
• Virtual Network Peering: Creating links between networks for seamless connectivity.

8. Managing Azure Active Directory (Azure AD)

• Overview of Active Directory services: Concepts and features.
• Self-Service Password Reset: Configuration and use.
• Azure AD Identity Protection: Implementing security policies.
• SaaS application integration: Secure sign-in with Azure AD.

9. Managing Active Directory objects

• Domains: Creating and managing Azure domains.
• Azure users and groups: Organising and managing permissions.
• Azure roles: Assigning and customising roles.
• Device management: Adding and tracking connected devices.

10. Implementing and managing hybrid identities

• Integration options: Scenarios for connecting on-premises and cloud environments.
• Application Proxy: Configuration to enable secure access to on-premises applications.

This second day goes deeper into managing virtual machines, networks and identities in Azure, while exploring advanced concepts to ensure a high-performance, secure infrastructure.

Introduction to Spark

1. Introduction to Spark: Overview of Spark and its impact on Big Data.
2. Why do we need Spark?: The limits of existing technologies and the benefits Spark brings.
3. What is Spark?: Overview of its features and key concepts.

Spark components

1. Spark components: Exploring Spark's main modules (Core, SQL, Streaming, MLlib, GraphX).
2. Categories of Spark components: Distinguishing between essential and advanced components.

Spark architecture

1. Spark architecture: Understanding the inner workings, including the cluster manager, the driver and the executors.

RDD (Resilient Distributed Dataset)

1. What is an RDD?: Spark's fundamental concept for managing distributed data.
2. RDD characteristics: Immutability, fault tolerance, partitioning, etc.
3. RDD sources: Where the data used to create RDDs comes from.
4. Workflow and DAG (Directed Acyclic Graph): Explanation of the execution process in Spark.
5. How to create an RDD?: Techniques for creating RDDs from various data sources.

Transformations and actions in Spark

1. Transformations: Lazy operations on RDDs (map, filter, join, etc.).
2. Actions: Operations that trigger execution (count, collect, save, etc.).

Persistence management

1. Persistence: Mechanisms for optimising performance through in-memory or disk storage.

Limits and outlook for Spark

1. RDD limitations: Introduction to the improvements brought by DataFrames and Datasets.
2. Will Spark replace MapReduce?: Comparison between Spark and the older MapReduce paradigm.

Hands-on workshop: Building a Spark application with Python (PySpark)

1. Spark LAB:

• Setting up the PySpark environment on AWS.
• Developing a Spark application in Python.
• Running transformation and action operations on real data.

This third day is dedicated to an immersion in the world of Spark, with a particular focus on the basics, RDDs and concrete practice with PySpark, to understand and fully harness Spark's capabilities in an AWS environment.

1. Introduction to Spark SQL

• What is Spark SQL?: Overview of Spark SQL as an interface for structured data processing in Spark.
• Spark SQL architecture: Exploring how it works, including the Catalyst Optimizer and the Tungsten Execution Engine.

2. The evolution of data in Spark

• History of RDDs, DataFrames and Datasets: Understanding the transition and successive improvements in Spark for data processing.
• New Spark 2.0 API: Highlighting the advances introduced with Spark 2.0.

3. Key concepts

• RDD (recap): A review of RDD fundamentals.
• DataFrames:
  • Structure of tabular data in Spark.
  • Features and benefits for data manipulation.
• Datasets:
  • Combining the benefits of RDDs and DataFrames.
  • Strong typing for better optimisation and debugging.

4. Spark SQL hands-on labs

LAB 1: Creating DataFrames and Datasets with Spark 3.0 in Python

• Creating DataFrames from various sources.
• Converting DataFrames into Datasets.

LAB 2: Spark data sources (Spark DataSources) in Python

• Connecting to common data sources: JSON, CSV, Parquet, etc.
• Reading, writing and manipulating data.

LAB 3: Flight delay analysis with Spark SQL in Python

• Loading flight delay datasets.
• Exploring, cleaning and analyzing data with SQL queries.

LAB 4: Football match analysis (1872-2019) in Python

• Loading a historical file of football matches.
• Using Spark SQL to analyze trends and statistics in the data.

This fourth day places particular emphasis on Spark SQL and structured data analysis. Participants will master advanced Spark SQL concepts through a series of hands-on labs that use real-world examples to strengthen their understanding.

1. Creating and Configuring a Team Project

• Creating a team project: Introduction to project concepts in Azure DevOps and to team project configuration.
• Iterations and security: Setting up iterations and managing security aspects within the project.
• Configuring areas and iterations: Configure work areas and define iterations.
• Configuring users and security: Manage users, their roles and access rights within the project.

Hands-on labs:

• Creating and configuring a team project in Azure DevOps.
• Configuring iterations and security areas.

2. Source Control

• Overview of source control types: Introduction to the two main source control systems in Azure DevOps, TFVC (Team Foundation Version Control) and Git.
• Configuring source control: Setting up version control to manage the project's source code.
• Branching and merging concepts: Understand branch management and merging (branch/merging) in development projects.
• Managing pull requests: Overview and use of pull requests for code review.
• Managing shelving (Shelving): How to use the shelving feature to temporarily save changes without committing them.

Hands-on labs:

• Configuring source control for optimal code management.
• Creating and managing branches, pull requests and shelvesets.

3. Work Items and Test Plan

• Exploratory and planned testing: Introduction to exploratory and planned testing with a suitable methodology for full test coverage.
• Work Items: Overview of the different work item types, including Epic, Feature, User Story, Task and Bug.
• Backlog and reports: Viewing the backlog through reports (Excel, MS Project, Power BI) and managing the related work items.
• Notification system: Configuring notifications to track project changes.

Hands-on labs:

• Test planning and work item management in Azure DevOps.

4. Visual Management with Dashboards

• Setting up a Dashboard: How to create a dashboard in Azure DevOps for effective visual project tracking.
• Overview of widgets: Exploring the various widgets available to customize dashboards.
• Visual Studio Marketplace: Introduction to the Visual Studio Marketplace and how to use it to integrate additional tools.

Hands-on labs:

• Setting up and using a Dashboard for visual project tracking.
• Installing and managing widgets from the Visual Studio Marketplace.

This day is dedicated to hands-on learning of the essential Azure DevOps tools, focusing on project management, source code, testing and data visualization with dashboards. Participants will gain a complete understanding of Azure DevOps features to optimize their development and project management processes.

1. Understanding Testing in Azure DevOps

• Testing concepts: Understand the basics of testing in a DevOps context.
• Test plan (Test and Feedback): Learn how to define a test plan suited to the DevOps workflow.
• Test Driven Development (TDD): Introduction to test-driven development and its impact on code quality.
• Unit tests, integration tests, functional tests: The differences between the various types of tests and their role in the development cycle.

2. Continuous Integration (CI)

• Continuous integration concepts: Overview of the fundamental principles of continuous integration to ensure high-quality continuous delivery.
• Build services: Using Azure DevOps build services to automate code compilation and validation.
• Visual Studio Team Services (VSTS): Introduction to VSTS for managing builds and CI/CD pipelines.
• Types of build tasks: Exploring the different tasks in a build pipeline.
• Continuous integration use cases: Real-world scenarios for applying continuous integration in different development environments.

Hands-on labs:

• Using VSTS Build to automate and customize build processes.

3. Using Release Management

• Implementing automated deployment: Learn how to configure automated deployment pipelines in Azure DevOps.
• The task catalog: Introduction to the task catalog in Azure DevOps to customize the steps of the deployment pipeline.
• Environment challenges: Manage deployment environments (development, testing, production) and their specific configurations.
• Real-world examples of automated deployment: Practical case studies of automated deployment across different environments.

Hands-on labs:

• Implementing automated deployment through pipelines in Azure DevOps.

4. Customizing the Team Project

• Modifying the process: Introduction to modifying processes in Azure DevOps to meet the team's specific needs.
• Customizing the process: Using process templates to customize the project life cycle.
• Adding custom fields: Learn how to add custom fields to work items and other tracking elements.

Hands-on labs:

• Customizing a project in Azure DevOps to meet specific requirements.
• Modifying the process and adding custom fields to work items.

This day aims to deepen your use of Azure DevOps, with particular attention to continuous integration, test management and automated deployment. Participants will learn to configure CI/CD pipelines, customize their projects and automate processes to make development and deployment more efficient.

1. Introduction to the AWS Cloud

• Definition of the cloud: Understand what the cloud is and its advantages over traditional on-premises solutions.
• Comparison with on-premises solutions: Explore the differences between on-premises infrastructure and cloud services, as well as the benefits of cloud computing in terms of flexibility, scalability and efficiency.
• Benefits of the AWS cloud: Analyze the key benefits of AWS, such as lower costs, simplified management and resource elasticity.
• AWS service categories: Introduction to the main AWS services: compute, storage, databases, networking, security, etc.
• AWS physical architecture: Understand the underlying architecture of AWS, including data centers, regions, availability zones and points of presence (PoPs).

2. Getting Started with AWS

• First steps with the AWS cloud: Discover the AWS Management Console and learn to navigate the user interface to create and manage resources.
• Core AWS services: Introduction to the core services: Amazon EC2 (compute), Amazon S3 (storage), Amazon RDS (databases), etc.
• Building your infrastructure: Learn to deploy and configure resources in AWS to build a complete cloud infrastructure.
• Data storage: Understand the different AWS storage options, including EBS volumes, S3, Glacier and distributed file systems.
• Securing data: Learn to secure data in the cloud using AWS security services such as AWS IAM (Identity and Access Management), KMS (Key Management Service) and access controls.

3. Building in the Cloud

• Beyond servers and storage: Explore other AWS services such as AWS Lambda (serverless compute), AWS Elastic Beanstalk (platform as a service) and AWS Fargate (container management).
• Monitoring AWS resources: Learn to monitor and manage AWS resources using Amazon CloudWatch to collect metrics, logs and alarms.
• Managing demand efficiently: Discover tools such as AWS Auto Scaling to automatically adjust resources to demand.
• Deploying database services: Learn to deploy and manage databases in AWS, with Amazon RDS and DynamoDB, according to performance and scalability needs.
• Automating deployment: Introduction to AWS CloudFormation to automate the management and deployment of cloud infrastructure.
• Connecting and sharing data: Learn to use services such as Amazon VPC (Virtual Private Cloud) and AWS Direct Connect to secure and share data between resources.
• Faster content delivery: Use Amazon CloudFront, a content delivery network (CDN) service, to improve content distribution to end users with low latency.

This first introductory day on AWS Solution Architect focuses on setting up a robust and secure cloud infrastructure, while covering the fundamental concepts of AWS services. Participants will learn to manage resources in AWS, automate deployment and secure the infrastructure while ensuring optimal performance and scalability as needs evolve.

1. Security in AWS

• Securing your infrastructure: Explore best practices for securing an AWS infrastructure, including the management of resources, networks and sensitive data.
• Managing authentication and authorization: Learn to use AWS Identity and Access Management (IAM) to manage identities and permissions and control access to resources.
• Assessing your compliance and security: Use AWS tools such as AWS Config and AWS Security Hub to assess compliance with security standards and ensure data protection.
• Protection against denial-of-service (DDoS) attacks: Introduction to AWS services such as AWS Shield and AWS WAF to protect the infrastructure against denial-of-service attacks and other threats.
• Maintaining compliance: Understand the tools and processes for keeping data and infrastructure compliant, taking into account regulatory requirements such as GDPR and HIPAA.

2. Support and Pricing

• AWS pricing basics: Learn to understand the AWS pricing model and the different types of costs associated with AWS services. Understand the usage costs of EC2, S3, RDS and other services.
• Getting help with AWS: Discover the support resources offered by AWS, including AWS support plans, forums and assistance programs.
• AWS programs and technologies: Learn about the various AWS programs, such as AWS Activate for startups, and tools such as the AWS Cost Explorer cost analysis tool.

3. Architecture in AWS

• The AWS Well-Architected Framework: Learn to apply the five pillars of the AWS Well-Architected Framework to design secure, reliable, high-performing and cost-effective cloud architectures.
• Reference architectures: Discover AWS reference architectures, including examples for deploying highly available and scalable systems.
• The future of the cloud: A discussion on the evolution of cloud computing, with a focus on future trends and innovations in AWS, including edge computing, artificial intelligence and infrastructure automation.

Day summary

This day will focus on the security, support and pricing aspects of AWS services, while exploring architectural best practices in greater depth with the AWS Well-Architected Framework. Participants will learn to secure their cloud infrastructure, manage compliance and understand AWS support mechanisms and pricing. The module will close with a look at the future of the cloud, focusing on possible developments in AWS technologies.