Official link here

Description

Linux is the #1 operating system for web servers, cloud computing, smart phones and consumer electronics. Due to its high adoption rates and continued growth, there’s a shortage of Linux system administrators. This Linux System Administration Essentials course will teach you the skills and processes you need to work as a professional Linux systems administrator.

Who Is It For

The course is ideal for those new to IT, or those who have worked with operating systems other than Linux and want to move into a career administering Linux systems. Aspiring cloud professionals will also benefit from understanding Linux administration as it serves as the basis of most cloud instances.

What You’ll Learn

In this course you will learn how to administer, configure and upgrade Linux systems running one of the major Linux distribution families: Debian/Ubuntu and Red Hat/CentOS/Fedora, how to master the tools and concepts you’ll need to efficiently build and manage an enterprise Linux infrastructure, how to work with Git and perform essential collaborative tasks, how to use state-of-the-art system administration techniques in real-life scenarios via practical labs, and more.

What It Prepares You For

The course, along with real-world experience and study, will provide the skills and knowledge also tested by the Linux Foundation Certified Systems Administrator (LFCS) exam.

Course Outline

Chapter 1. Introduction
Chapter 2. Linux Filesystem Tree Layout
Chapter 3. User Environment
Chapter 4. User Account Management
Chapter 5. Group Management
Chapter 6. File Permissions and Ownership
Chapter 7. Package Management Systems
Chapter 8. dpkg
Chapter 9. APT
Chapter 10. RPM
Chapter 11. dnf and yum
Chapter 12. zypper
Chapter 13. GIT Fundamentals
Chapter 14. Processes
Chapter 15. Process Monitoring
Chapter 16. Memory Monitoring, Usage and Configuring Swap
Chapter 17. I/O Monitoring
Chapter 18. Containers Overview
Chapter 19. Linux Filesystems and the VFS
Chapter 20. Disk Partitioning
Chapter 21. Filesystem Features: Attributes, Creating, Checking, Usage, Mounting
Chapter 22. The EXT4 Filesystem
Chapter 23. Logical Volume Management (LVM)
Chapter 24. Kernel Services and Configuration
Chapter 25. Kernel Modules
Chapter 26. Devices and udev
Chapter 27. Network Addresses
Chapter 28. Network Devices and Configuration
Chapter 29. LDAP
Chapter 30. Firewalls
Chapter 31. System Init: systemd History and Customization
Chapter 32. Backup and Recovery Methods
Chapter 33. Linux Security Modules
Chapter 34. System Rescue

Official link here

Description

Who Is It For

What You’ll Learn

What It Prepares You For

Course Outline

Official link here

Description

This course provides the skills and knowledge on a broad range of best practices for securing container-based applications and Kubernetes platforms during build, deployment and runtime.

Who Is It For

This course is ideal for anyone holding a CKA certification and interested in or responsible for cloud security.

What You’ll Learn

This course exposes you to knowledge and skills needed to maintain security in dynamic, multi-project environments. This course addresses security concerns for cloud production environments and covers topics related to the security container supply chain, discussing topics from before a cluster has been configured through deployment, and ongoing, as well as agile use, including where to find ongoing security and vulnerability information. The course includes hands-on labs to build and secure a Kubernetes cluster, as well as monitor and log security events.

What It Prepares You For

The course, along with real-world experience and study, will provide the skills and knowledge also tested by the Kubernetes Security Specialist (CKS) exam.

Course Outline

Chapter 1. Course Introduction
Chapter 2. Cloud Security Overview
Chapter 3. Preparing to Install
Chapter 4. Installing the Cluster
Chapter 5. Securing the kube-apiserver
Chapter 6. Networking
Chapter 7. Workload Considerations
Chapter 8. Issue Detection
Chapter 9. Domain Review

Official link here

Description

DevSecOps practices are an extension to standard DevOps practices, focusing on automating security and incorporating it as part of the process, which includes Continuous Delivery, Infrastructure-as-Code (IaC), and observability. Use of DevSecOps results not only in delivering safer code faster, but also facilitates early feedback to developers, helping them build more reliable software. This course explores implementing DevSecOps practices into the software delivery pipeline using open source software.

Who Is It For

This course is designed for software developers, site reliability engineers, and DevOps practitioners looking to speed up delivery of more secure code. To make the most of this course, learners must have working knowledge of Linux operating systems and the command line interface, Git, Docker, and Kubernetes. They must also know how to build CI/CD pipelines, write Infrastructure-as-Code (IaC), run Ansible Playbooks, and understand observability concepts such as log management and monitoring

What You’ll Learn

This course begins by laying the foundation of DevSecOps, explaining the principles, practices, cultural aspects and tooling landscape. It then goes on to show you how to incorporate various practices into the Continuous Delivery pipeline: perform Software Composition Analysis (SCA) and add it to the Continuous Integration pipeline, perform static code analysis and project gating using SAST tools, implement security best practices while writing Dockerfiles to build images, scan container images for vulnerability, perform Dynamic Application Software Testing (DAST) on a live environment, set up a centralized vulnerability management system to provide visibility and alerting, and build a cloud native DevSecOps pipeline. You will also use IaC effectively to enforce compliance, collect logs, analyze events to provide detection and monitoring of security issues, and learn to address cloud and container related risks. In order to make adoption of DevSecOps practices frictionless, this course focuses on usage of mostly open source software, at the same time providing enough flexibility to plug in a commercial alternative to match the implementation environment.

What It Prepares You For

This course prepares you with real life professional skills to implement DevSecOps practices into the software development and delivery processes.

Course Outline

Chapter 1. Course Introduction
Chapter 2. What Is DevSecOps?
Chapter 3. Setting Up the Lab Environment
Chapter 4. Building a DevOps Pipeline
Chapter 5. Securing the Supply Chain with SCA
Chapter 6. Static Application Security Testing (SAST)
Chapter 7. Auditing Container Images
Chapter 8. Secure Deployment and Dynamic Application Security Testing (DAST)
Chapter 9. System Security Auditing with IAC
Chapter 10. Securing Kubernetes Deployments
Chapter 11. Secrets Management with Vault
Chapter 12. Runtime Security Monitoring and Remediation

Official link here

Description

Empower yourself with the essential skills to fortify digital architectures against contemporary and emerging threats.

Who Is It For

This course is designed for developers aiming to deepen their understanding of infrastructure security and management. It is ideal for those who wish to enhance their knowledge in network penetration testing and infrastructure security skills.

What You’ll Learn

Explore the fundamental elements needed to establish and maintain a secure infrastructure configuration and the principles and techniques of network penetration testing to identify potential security vulnerabilities.

What It Prepares You For

By the end of this course, you should be able to fortify digital architectures against contemporary and emerging threats as well as navigate the intricate landscape of infrastructure security.

Course Outline

Chapter 1. Course Introduction
Chapter 2. Introduction to Infrastructure & Ops Security
Chapter 3. Phases of Hacking
Chapter 4. Reconnaissance - The First Step of Hacking
Chapter 5. Scanning, Identifying Vulnerabilities, and Mapping the Network
Chapter 6. Gaining Access: The Art of Exploitation
Chapter 7. Mapping and Information Gathering
Chapter 8. Service Enumeration and Subdomain Takeover
Chapter 9. Default Pages, Backup Files, and Application Versions
Chapter 10. Command Injection Attacks
Chapter 11. Privilege Escalation - Linux
Chapter 12. Privilege Escalation - Windows
Chapter 13. Security, TLS, and Configuration
Chapter 14. Labs - Basic to Advanced

Official link here

Description

Learn to implement and enforce security policies with Kyverno to manage Kubernetes resources effectively.

Who Is It For

This course is for Kubernetes engineers, cluster operators, and security professionals whose focus is regulatory compliance, standardization, and security within Kubernetes clusters using Kyverno.

What You’ll Learn

Learn to create, apply and manage Kyverno policies and reporting tools that help identify potential violations in real-time and proactively address security and compliance in Kubernetes clusters.

What It Prepares You For

The course empowers you to become proficient in Kubernetes policy management and reporting, enhancing skills for roles including Kubernetes security specialists, DevSecOps engineers, or Kubernetes administrators.

Course Outline

Chapter 1. Course Introduction
Chapter 2. Overview of Kubernetes Policies
Chapter 3. Kyverno Introduction and Installation
Chapter 4. Writing Policies
Chapter 5. Enforcing Policies
Chapter 6. Mutation Policies
Chapter 7. Policy Validation and Testing
Chapter 8. Monitoring and Troubleshooting
Chapter 9. Reporting in Kyverno
Chapter 10. Securing Kyverno
Chapter 11. Integration and Extensibility
Chapter 12. Multi-Cluster Policy Management
Chapter 13. Contributing to the Kyverno Project

Official link here

Description

Who Is It For

What You’ll Learn

What It Prepares You For

Course Outline

Official link here

Description

Who Is It For

What You’ll Learn

What It Prepares You For

Course Outline

Official link here

Description

Who Is It For

What You’ll Learn

What It Prepares You For

Course Outline

Official link here

Description

Introduction to Cloud Infrastructure Technologies (LFS151) is a broad, entry-level course designed to provide a comprehensive overview of the technologies, concepts, and architectural patterns that underpin modern cloud computing. It is intended for system administrators, developers, and architects who are new to the cloud and need a structured framework to understand the rapidly evolving cloud-native landscape and evaluate which technologies best align with their organizational needs. The course introduces the fundamental service models—Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Container as a Service (CaaS)—and explains how virtualization, containers, and orchestration technologies enable scalable and flexible infrastructure. Learners gain hands-on exposure to container fundamentals using Docker, along with conceptual grounding in microservices, container orchestration, and emerging execution models such as unikernels and serverless computing.
Beyond compute, the course explores software-defined networking and software-defined storage, highlighting how networking, storage, and observability are reimagined in cloud-native systems. It also covers essential DevOps practices and tooling, including CI/CD, configuration management, image building, logging, monitoring, distributed tracing, and service meshes, providing a holistic view of how modern cloud platforms are built and operated. Finally, the course addresses advanced and forward-looking topics such as IoT integration and operational best practices, helping learners understand both the opportunities and challenges of cloud adoption.
By the end of the course, participants develop a solid foundational understanding of cloud infrastructure and open-source cloud technologies, enabling them to make informed decisions, collaborate effectively across development and operations teams, and prepare for more specialized cloud and platform engineering paths.

Who Is It For

This class is designed for people who have little or no prior experience with cloud technologies. System administrators, developers, and architects new to the cloud can all benefit from the content covered in this class, especially if they are looking to evaluate which cloud technologies might be the best fit for their organization.

What You’ll Learn

In this course you will receive an overview of common cloud technologies, an introduction to Iaas, PaaS, CaaS, and learn about basic operations with containers and images using Docker command, software-defined networking and software-defined storage solutions, the skill sets needed to deliver next generation cloud, and the challenges of cloud technologies.

What It Prepares You For

You will walk away from this course with an understanding of cloud computing and the use of open source software to maximize development and operations.

Course Outline

Chapter 1. Virtualization Chapter 2. Infrastructure as a Service (IaaS) Chapter 3. Platform as a Service (PaaS) Chapter 4. Containers Chapter 5. Containers: Micro OSes for Containers Chapter 6. Containers: Container Orchestration Chapter 7. Unikernels Chapter 8. Microservices Chapter 9. Software-Defined Networking and Networking for Containers Chapter 10. Software-Defined Storage and Storage Management for Containers Chapter 11. DevOps and CI/CD Chapter 12. Tools for Cloud Infrastructure: Configuration Management Chapter 13. Tools for Cloud Infrastructure: Build & Release Chapter 14. Tools for Cloud Infrastructure: Key-Value Pair Store Chapter 15. Tools for Cloud Infrastructure: Image Building Chapter 16. Tools for Cloud Infrastructure: Debugging, Logging, and Monitoring for Containerized Applications Chapter 17. Service Mesh Chapter 18. Internet of Things (IoT) Chapter 19. Serverless Computing Chapter 20. Distributed Tracing Chapter 21. How To Be Successful in the Cloud

Official link here

Description

Introduction to DevOps and Site Reliability Engineering (LFS162) is a foundational course that provides a structured introduction to the principles, practices, and cultural shifts that underpin modern software delivery and reliable system operations. It is designed both for managers seeking guidance on how to initiate and lead organizational transformation, and for engineers who aspire to build a career in DevOps and Site Reliability Engineering (SRE).
The course explains how DevOps practices have reshaped software development and operations by breaking down silos, accelerating delivery cycles, and improving collaboration. It explores the role of cloud computing and container technologies, with Kubernetes as a central platform, in enabling scalable, resilient, and repeatable application deployments. Learners are introduced to the motivations and practical implementation of Infrastructure as Code, highlighting how infrastructure automation improves consistency, traceability, and operational confidence.
In addition, the course covers CI/CD pipelines and their role in delivering software safely and continuously, as well as the fundamentals of observability, including what to monitor, why it matters, and how observability supports system reliability. The final sections introduce Site Reliability Engineering, presenting SRE as a disciplined engineering approach to balancing feature velocity with system stability and reliability.
By the end of the course, participants gain a solid understanding of DevOps and SRE foundations, equipping them with the conceptual and practical knowledge needed to deploy and operate software systems with speed, resilience, and high reliability in modern cloud-native environments.

Who Is It For

If you are a manager looking for guidelines on how to start transforming organizations, and understand where to start, this course is for you. If you aspire to make a career in the world of DevOps and Site Reliability Engineering, this course is your starting point.

What You’ll Learn

In this course you will learn how DevOps is influencing software delivery, how cloud computing has enabled organizations to rapidly build and deploy products and expand capacity, how the open container ecosystem, with Kubernetes in the lead, is truly revolutionizing software delivery, and the why, what and how of writing Infrastructure as Code. The course also covers Continuous Deployment and Continuous Delivery (CI/CD), as well as the role played by observability systems, what to observe and why.

What It Prepares You For

Upon completion, you should have a good understanding of the foundation, principles, and practices of DevOps and Site Reliability Engineering, and have gained the knowledge and skills to understand how to deploy software with confidence, agility and high reliability using modern DevOps and SRE practices.

Course Outline

Chapter 1. Welcome! Chapter 2. Introduction to DevOps and Site Reliability Engineering Chapter 3. Introduction to Cloud Chapter 4. Introduction to Containers Chapter 5. Infrastructure as Code Chapter 6. Continuous Integration/Continuous Delivery Chapter 7. Introduction to Observability Chapter 8. Site Reliability Engineering

This course will help you build a solid foundation on container technologies. Once you have learned the basics with the course, you will be able to take on more advanced topics, like Docker Swarm and Kubernetes, with ease. Official link here

Who Is It For

It has become extremely important for countless job roles in the technology industry to learn about containers, be they developers, quality assurance, operations, or DevOps.

What You’ll Learn

This Containers Fundamentals course will help you build a solid foundation on container technologies. After completing this course, you should be able to perform container and image operations with different container runtimes, manage network and storage (volumes) with containers, build and run multi-container applications with Docker, Docker APIs, etc.

What It Prepares You For

This course prepares you to work with containers to bundle an application with all its dependencies and deploy it on the platform of our choice, be it Bare-Metal, VM, Cloud, etc. Once you have learned the basics with the course, you will be able to take on more advanced topics, like Docker Swarm and Kubernetes, with ease.

Course Outline

Chapter 1. Course Introduction
Chapter 2. Virtualization Fundamentals
Chapter 3. Virtualization Mechanisms
Chapter 4. Container Standards and Runtimes
Chapter 5. Image Operations
Chapter 6. Container Operations
Chapter 7. Building Container Images
Chapter 8. Container Networking
Chapter 9. Container Storage
Chapter 10. Runtime and Containers Security

Official link here

Who Is It For

This course is ideal for those wishing to manage a containerized application infrastructure. This includes existing IT administrators, as well as those looking to start a cloud career.

What You’ll Learn

The Kubernetes Fundamentals course will teach you how to use the container management platform used by companies like Google to manage their application infrastructure. You will learn how to install and configure a production-grade Kubernetes cluster, from network configuration to upgrades to making deployments available via services. The course also distills key principles, such as pods, deployments, replicasets, and services, and will give you enough information so that you can start using Kubernetes on your own.

What It Prepares You For

The course, along with real-world experience and study, will provide the skills and knowledge also tested by the Kubernetes Certified Administrator (CKA) exam.

Course Outline

Chapter 1. Course Introduction,
Chapter 2. Basics of Kubernetes,
Chapter 3. Installation and Configuration,
Chapter 4. Kubernetes Architecture,
Chapter 5. APIs and Access,
Chapter 6. API Objects,
Chapter 7. Managing State with Deployments,
Chapter 8. Helm and Kustomize,
Chapter 9. Volumes and Data,
Chapter 10. Services,
Chapter 11. Ingress,
Chapter 12. Scheduling,
Chapter 13. Logging and Troubleshooting,
Chapter 14. Custom Resource Definitions,
Chapter 15. Security,
Chapter 16. High Availability,
Chapter 17. Exam Domain Review

Official link here

In short

With the growth of microservices and Kubernetes production environments, there is an increasing need to improve resilience, observability, and security for cloud native apps. This course explains the principles behind service mesh and explores the use of Envoy Proxy, Linkerd, Istio, Consul, and the Service Mesh Interface (SMI).

Description

The Service Mesh Fundamentals (LFS243) course provides a compact but complete introduction to modern cloud-native traffic management, covering the challenges of microservices, the need for resilience patterns (timeouts, retries, deadlines, circuit breakers, client-side and proxy-side load balancing), and the role of sidecar-based data planes built on technologies like Envoy, Linkerd-proxy, and Consul Connect. It explains how control planes such as Linkerd, Istio, and Consul manage service discovery, security, and configuration, and how ingress controllers integrate with meshes to handle north–south traffic. The course also introduces SMI (Service Mesh Interface) and its key APIs—TrafficSpecs, TrafficSplit, TrafficAccessControl, and TrafficMetrics—as vendor-agnostic standards. Tools like Linkerd viz, tap, routes, debug containers, Telepresence, and distributed tracing/metrics pipelines are explored for troubleshooting and observability, along with security mechanisms such as mutual TLS (mTLS) and certificate rotation. Overall, it gives a solid foundation for working with service mesh technologies across Kubernetes environments.

Who Is It For

This course is designed for DevOps engineers, site reliability engineers, and platform engineers adopting microservice architectures.

What You’ll Learn

The course introduces the challenges of distributed systems, strategies for managing these challenges, and the architecture of service meshes. It also covers key concepts such as data plane vs. control plane and the evolution of ingress.

What It Prepares You For

After completing this course, you will be prepared to roll out and manage microservice architectures and distributed systems.

Course Outline

Chapter 1. Course Introduction,
Chapter 2. Cloud Native Apps,
Chapter 3. Resilience for Distributed Systems,
Chapter 4. Service Mesh Data Planes and Control Planes,
Chapter 5. Service Mesh Fundamentals,
Chapter 6. Service Mesh Standards,
Chapter 7. Using Service Mesh to Debug and Mitigate App Failures

Official link here

In short

This course leads new Prometheus users through many of its major features, best practices, and use cases. Course participants are expected to have basic experience with Linux/Unix system administration, as well as some development experience in Go and/or Python.

Description

The Monitoring Systems and Services with Prometheus (LFS241) course provides a structured and in-depth introduction to cloud-native observability, focusing on monitoring modern distributed systems and Kubernetes workloads. It covers the Prometheus data model, pull-based scraping, time-series storage internals (WAL, blocks, compaction), and metric types (counters, gauges, histograms, summaries), together with PromQL for querying, aggregation, and alert evaluation. The course explains integration with Kubernetes service discovery, labeling and relabeling pipelines, and exporters such as Node Exporter, cAdvisor, blackbox exporter, and Pushgateway, as well as custom instrumentation in Go and Python. It explores alerting architectures using Alertmanager, including grouping, routing, deduplication, and high availability via gossip protocols. Practical laboratories include remote storage integrations using SeaweedFS and MinIO (S3-compatible object storage) together with Thanos for long-term storage, query federation, and globally scalable Prometheus architectures. Overall, the course provides hands-on experience operating scalable, highly available observability stacks in production and edge-oriented environments.

Who Is It For

The LFS241 course is built for DevOps engineers, SREs, and system admins ready to level up observability skills and get Prometheus-ready for high-impact roles in modern, cloud-native environments. The PCA is a pre-professional certification designed for an engineer or application developer with special interests in observability and monitoring.

What You’ll Learn

Walk away knowing how to monitor real-world systems with Prometheus—track containers, catch issues early, use service discovery, and build production-grade observability into your Kubernetes stack.

What It Prepares You For

Prepare for real-world observability challenges—whether you're deploying at scale, building dashboards, or setting alerts. This course, along with real-world experience and study, will provide the skills and knowledge also tested by the Prometheus Certified Associate (PCA) exam

Course Outline

Chapter 1. Course Introduction
Chapter 2. Introduction to Observability,
Chapter 3. Introduction to Prometheus,
Chapter 4. Installing and Setting Up Prometheus,
Chapter 5. Basic Querying,
Chapter 6. Dashboarding,
Chapter 7. Monitoring Host Metrics,
Chapter 8. Monitoring Container Metrics,
Chapter 9. Instrumenting Code,
Chapter 10. Building Exporters,
Chapter 11. Advanced Querying,
Chapter 12. Relabeling,
Chapter 13. Service Discovery,
Chapter 14. Blackbox Monitoring,
Chapter 15. Pushing Data,
Chapter 16. Alerting,
Chapter 17. Making Prometheus Highly Available,
Chapter 18. Recording Rules,
Chapter 19. Scaling Prometheus Deployments
Chapter 20. Local Storage,
Chapter 21. Remote Storage Integrations,
Chapter 22. Transitioning From and Integration with Other Monitoring Systems,
Chapter 23. Monitoring and Debugging Prometheus,
Chapter 24. Prometheus and Kubernetes

Official link here

In short

Helm is an emerging technology that enables packaging and running applications on Kubernetes in a simple, efficient way. This course is a deep dive into Helm, and how it's used in real-world scenarios to manage the lifecycle of applications on Kubernetes

Description

The course provides a system-level understanding of Helm architecture, chart design, and release management, enabling repeatable, versioned, and production-safe deployments. It covers building production-ready Helm charts, managing installations, upgrades, rollbacks, and working with chart repositories and dependencies. Helm is treated as a control abstraction layer between application intent, Kubernetes primitives, and CI/CD or GitOps workflows, similar to a shipping container that standardizes application delivery across environments. Real-world operational risks such as misconfigured charts, release state drift, and centralized deployment models are analyzed. Misconfiguration can impact service availability but is mitigated through linting, validation, and staged rollouts. Release drift is addressed through GitOps reconciliation and strict ownership of resources. In edge computing scenarios, centralized Helm usage may become a single point of failure, mitigated by pre-rendered manifests and decentralized deployment pipelines. Overall, the course strengthens production reliability, operational scalability, and lifecycle control for Kubernetes workloads.

Who Is It For

Recommended for system administrators, DevOps engineers, SREs, and other software professionals, this course is for any person who wishes to enhance their operational experience running containerized workloads on the Kubernetes platform.

What You’ll Learn

This course covers the history of the Helm project and its architecture, how to properly install the Helm client, the various components of a Helm chart and how to create one, the command-line actions used for managing an application’s lifecycle, and much more.

What It Prepares You For

This course provides a full-featured deep dive into the Helm client, Helm charts, and how Helm can prepare you for real-world scenarios managing the full lifecycle of applications on Kubernetes.

Course Outline

Chapter 1. Course Introduction
Chapter 2. Helm Basics
Chapter 3. Helm Setup and Initial Usage
Chapter 4. Helm Charts
Chapter 5. Application Lifecycle
Chapter 6. Chart Repositories and Other Topics

Official link here

In short

This course introduces the Fluentd and Fluent Bit log forwarding and aggregation tool for use in cloud native logging. Both tools provide fast and efficient log transformation and enrichment, as well as aggregation and forwarding. These capabilities enable both Fluentd and Fluent Bit to realize the concept of a “unified logging layer”, that helps users consume log data collected from all parts of a large scale, distributed system

Description

The Cloud Native Logging with Fluentd and Fluent Bit (LFS242) course provides a compact but practical introduction to cloud-native logging architectures, focusing on how Fluentd and Fluent Bit can be used to collect, parse, filter, enrich, aggregate, and forward logs across distributed systems. It explains the concept of a unified logging layer, showing how logs from different services and infrastructure components can be normalized and routed through flexible pipelines for downstream analysis and observability. The course covers core data flow concepts such as inputs, filters, parsers, formatters, outputs, and multi-stage pipeline design, together with deployment models ranging from native processes to containerized environments and multi-instance setups. It also introduces monitoring of the logging layer itself, along with key practices for debugging, performance tuning, and securing Fluent ecosystem deployments. Overall, it gives a solid foundation for designing and operating production-ready logging pipelines with Fluentd and Fluent Bit in modern cloud-native environments.

Who Is It For

This course is designed for individuals with a technical background including sysadmins and developers who need to utilize cloud native logging tools.

What You’ll Learn

In this course, you will explore the full range of Fluentd and Fluent Bit operations and features, from installing the tools as native processes to running Fluentd and Fluent Bit in container. The course also examines using Fluentd and Fluent Bit as simple log forwarders, as well as using the tools as sophisticated log aggregators and processors. Upon completion, you will have the skills necessary to deploy the Fluent tools in a wide range of production settings.

What It Prepares You For

Upon completion of this course, you will have the skills necessary to deploy Fluentd and Fluent Bit in a wide range of production settings.

Course Outline

Chapter 1. Course Introduction
Chapter 2. Fluent Ecosystem and Unified Logging
Chapter 3. Log Input and Output
Chapter 4. Filtering Data and Creating Pipelines
Chapter 5. Parsing and Formatting Data
Chapter 6. Multi-instance Deployments with the Fluent Ecosystem
Chapter 7. Monitoring the Unified Logging Layer
Chapter 8. Optimizing and Debugging Fluent Ecosystem Configurations
Chapter 9. Securing Fluent Ecosystem Deployments
Chapter 10. Debugging, Tuning, and Securing Fluentd Configurations
Chapter 11. Introduction to Fluent Bit

Programmazione con Python — Winter Camp 2025

Material for 7 hours of theoretical study

Python Programming (Winter Camp 2025) is an introductory, hands-on training program designed to build solid foundations in Python software development through a structured combination of theory, guided practice, and practical exercises. The objective is to enable learners to master Python syntax and core programming constructs, applying them immediately to concrete problems, while progressively introducing modern AI-assisted coding tools.
The course starts with the fundamentals of the language, focusing on variables and data types. Topics include arithmetic operations, correct handling of divisions, powers and modulo operations, variable swapping techniques, as well as type casting and string formatting. These concepts are reinforced through a set of targeted exercises.

The program then introduces data collections, covering structures used to organize and manipulate data. Practical activities are applied to realistic scenarios, such as managing school report data, to demonstrate how data structures are used in real-world contexts.
The module on conditional statements addresses control-flow logic using if/else constructs and proper decision branching. This is followed by a dedicated section on loops, aimed at developing the ability to automate repetitive tasks and iterative logic through exercises involving powers, ranking logic (“second place”), register management, and palindrome detection.

The course subsequently covers procedural programming, with a focus on problem decomposition into functions, code reuse, and logical organization of programs. Exercises include geometric calculations (circle area) and rule-based logic (leap year detection), reinforcing functional structuring and program clarity.

To complete the curriculum, a dedicated module explores key AI tools supporting software development. This section covers AI-assisted code generation and development workflows using widely adopted platforms and tools such as Google Colab, ChatGPT, Cursor, and GitHub Copilot in Visual Studio Code. It also introduces AI programming techniques, including vibe coding and engineered approaches, aimed at improving productivity, prototyping speed, and code quality through controlled prompting and iterative refinement.

Material for 7 hours of hands-on study
This course provides a theoretical and applied overview of modern Artificial Intelligence systems, with a primary focus on Large Language Models (LLMs), Agentic AI, and Transformer-based architectures. It is structured to integrate foundational theory with guided laboratory activities, ensuring a clear connection between underlying concepts and their practical implementation.

The program examines the training and operational principles of LLMs, including prompt engineering methodologies and Retrieval-Augmented Generation (RAG). Practical sessions address the design and implementation of RAG pipelines using established frameworks such as LangChain and LlamaIndex. The course further introduces Agentic AI, covering the architectural components and development patterns of autonomous AI agents, supported by hands-on laboratories in Python and the use of modern agent frameworks including LangGraph, CrewAI, and AutoGen, applied to representative real-world scenarios.

The final modules are dedicated to Transformer architectures and the Hugging Face ecosystem, providing theoretical insight into self-attention mechanisms, encoder–decoder models, and sequence-to-sequence paradigms. These concepts are reinforced through applied laboratories focused on fine-tuning transformer models for Natural Language Processing tasks, including text classification, Named Entity Recognition (NER), translation, and summarization.

01 Fine-Tuning and Deployment of a Large Language Model (LLM) 2 hours .

Date: 26/06/2025 Duration: 2 hours
A two-hour masterclass titled "Fine-Tuning and Deployment of a Large Language Model (LLM)", aimed at providing a practical, end-to-end overview of adapting and serving transformer-based models.
The session focused on fine-tuning pre-trained models using the Hugging Face Transformers library and executing training workflows in Google Colab. We covered dataset formatting, tokenization, training loop configuration, evaluation, and checkpoint management.
In the second part, we explored deployment strategies using Hugging Face Spaces, with emphasis on reproducibility, interface integration (via Gradio), and model versioning.
This hands-on session was designed for engineers, data scientists, and applied researchers seeking to operationalize custom LLMs efficiently using open-source tools and cloud-based resources.

click here for more information and certificate

02 AI engineering: From model to service, how to serve a model through a REST API 3 hours .

In this three-hour workshop, we explored how to transform a trained machine learning model into a functioning service accessible through a REST API. Using Flask as the lightweight web framework and Uvicorn as the ASGI server, we learned how to expose the model so that clients can send validated inputs and receive predicted outputs in real time.
The session emphasized understanding the complete data flow: from input validation, through the model’s learned patterns, to the generation of outputs. Special attention was given to data control and consistency, ensuring that every request handled by the API maintains accuracy, transparency, and security.
Stack: Python · Flask · Uvicorn · REST API Architecture

click here for more information and certificate

03 AI development: An expense management agent with Telegram 3 hours .

duration: 3 h
Developed an AI-driven expense and cash-flow management bot leveraging Telegram Bot API and n8n for workflow orchestration. The session focused on agent-based AI architecture, API integration, and event-driven automation pipelines, demonstrating how to design and deploy intelligent financial assistants using low-code and AI orchestration tools.

click here for more information and certificate

New energy production technologies · advanced renewables · energy storage innovation · smart-grid architectures.
Innovation principles: problem exploration · research framing · structured ideation.
User validation, assumption testing, solution refinement, pitch development.

The technical skills required and developed in the context of the Clean Tech Academy concern mastering emerging technologies in the clean and deep tech sector, with a focus on the ecological and digital transition.

Ability to apply knowledge of Clean Technologies: Participants will gain a solid understanding of key emerging technologies in the area of sustainability and decarbonisation.

Anlysis of Sustainability Challenges and Identification of Technology Solutions: The programme focuses on the ability to identify problems and propose solutions based on innovative technologies, with a particular focus on industrial contexts.

Use of Digital Learning and Collaboration Tools: The integrated online platform will allow participants to develop skills in the use of digital tools for training, knowledge sharing and project management.

In addition to technical skills, the Clean Tech Academy programme aims to develop a series of fundamental transversal skills to address deep tech challenges and promote collaboration among stakeholders.

Problem Solving and Critical Thinking: Ability to address complex problems and find innovative solutions, in particular to sustainability and digitalisation challenges.

Adaptability and Flexibility: Being able to work in an ever-changing technological and regulatory environment, anticipating change and adapting operational strategies.

Teamwork and Collaboration: Developing the ability to work in multidisciplinary and multicultural teams to deliver innovative projects.

Leadership and Entrepreneurial Spirit: Promoting proactive thinking and the ability to lead projects and teams in the context of the ecological and digital transition.

Effective Communication: Ability to present technology projects to different stakeholders, including investors, businesses and public institutions.

Time and Priority Management: Ability to work autonomously and organise tasks efficiently to meet deadlines and targets.

Creativity and Innovative Thinking: Developing an innovative mindset to turn ideas into real, scalable solutions.

Final Project — Utopic Network: A Blockchain Edge-of-Things application for the Internet of Energy.

Study case integrating edge orchestration systems (KubeEdge / k3s / EdgeX) with blockchain at the edge (Hyperledger Fabric / Bevel) to support secure, low-latency SCADA-like energy operations.

Official link here

Description

Introduction to Jenkins (LFS167) is a foundational course designed to provide a structured and practical understanding of Jenkins as a CI/CD automation platform within modern software development workflows. The course explains the role of continuous integration and continuous delivery in the software development lifecycle and positions Jenkins as a central orchestration component that connects source control, build systems, testing frameworks, and deployment targets.
Participants learn how to install, configure, and operate the Jenkins automation server, navigate and use the Jenkins dashboard, and create different types of jobs, including freestyle and pipeline-based projects. The course also covers plugin management, showing how Jenkins can be extended and integrated with third-party tools, as well as security and scalability concepts, including distributed build architectures using agents.
By the end of the course, learners gain a solid operational understanding of Jenkins, enabling them to design, implement, and maintain reliable CI/CD pipelines. The course also prepares participants to progress toward more advanced CI/CD topics, such as pipeline optimization, infrastructure scaling, and enterprise-grade Jenkins deployments.

Who Is It For

This course is for teams considering using Jenkins as a CI/CD tool and looking to automate their software delivery process, as well as those who need guidelines on how to set up a CI/CD workflow using the Jenkins automation server.

What You’ll Learn

In this course you will learn the role of Jenkins in software development lifecycle, how to set up and access the Jenkins automation server, how to build your software by configuring and running various types of Jenkins projects, how to install and manage plugins, how to scale and secure Jenkins, and more.

What It Prepares You For

Upon completion, you will have a solid understanding of the role that Jenkins plays in the software development lifecycle, how to install a Jenkins server, how to build software for it, how to manage third party integrations/plugins and how to scale and secure Jenkins. Finally, you will get a glimpse of what you can do to further enhance your CI/CD skills.

Course Outline

Chapter 1. CI/CD Overview Chapter 2. Jenkins Installation Basics Chapter 3. Jenkins Dashboard Chapter 4. Jenkins Plugins Chapter 5. Jenkins Security Chapter 6. Jenkins Projects Chapter 7. Freestyle Project Chapter 8. Pipeline Project Chapter 9. Distributed Builds Architecture Chapter 10. What’s Next?

Official link here

Description

Introduction to Kubernetes (LFS158) is a foundational course designed to provide a clear and structured introduction to Kubernetes and cloud-native application orchestration. It is aimed at teams and individuals who are starting to adopt Kubernetes and need practical guidance on how to transition from traditional application architectures toward microservices and container-based platforms.
The course introduces the origins, motivations, and architectural principles behind Kubernetes, explaining how it addresses the challenges of deploying, scaling, and operating distributed applications. Learners gain an understanding of the core Kubernetes components and control-plane concepts, as well as the fundamental building blocks used to run applications, such as Pods, Services, volumes, ConfigMaps, and Secrets.
Through hands-on examples using Minikube, the course demonstrates how to install a local Kubernetes cluster, deploy and access applications, and interact with the cluster using standard tooling. It also covers essential operational topics such as authentication, authorization, admission control, networking, storage, and ingress, providing a realistic view of how Kubernetes is used in practice. Finally, the course highlights the importance of the Kubernetes community and ecosystem, encouraging participation as part of a long-term cloud-native journey.
By the end of the course, participants develop a solid conceptual and practical foundation in Kubernetes, enabling them to confidently begin experimenting with cloud-native patterns and prepare for more advanced Kubernetes and platform engineering topics.

Who Is It For

This course is for teams considering or beginning to use Kubernetes for container orchestration who need guidelines on how to start transforming their organization with Kubernetes and cloud native patterns. Some knowledge of Linux system administration is helpful but not required.

What You’ll Learn

This course will teach you about the origin, architecture, primary components, and building blocks of Kubernetes. It covers how to set up and access a Kubernetes cluster using Minikube, ways to run applications on the deployed Kubernetes environment and access the deployed applications, the usefulness of Kubernetes communities, how you can participate, and more.

What It Prepares You For

Upon completion, you will have a solid understanding of the origin, architecture and building blocks for Kubernetes, and will be able to begin testing the new cloud native pattern to begin the cloud native journey.

Course Outline

Chapter 1. Course Introduction Chapter 2. From Monolith to Microservices Chapter 3. Container Orchestration Chapter 4. Kubernetes Chapter 5. Kubernetes Architecture Chapter 6. Installing Kubernetes Chapter 7. Minikube: Installing Local Kubernetes Clusters Chapter 8. Accessing Minikube Chapter 9. Kubernetes Building Blocks Chapter 10. Authentication, Authorization, Admission Control Chapter 11. Services Chapter 12. Deploying a Standalone Application Chapter 13. Kubernetes Volume Management Chapter 14. ConfigMaps and Secrets Chapter 15. Ingress Chapter 16. Advanced Topics Chapter 17. Kubernetes Community

Official link here

Description

Introduction to Cloud Infrastructure Technologies (LFS151) is a broad, entry-level course designed to provide a comprehensive overview of the technologies, concepts, and architectural patterns that underpin modern cloud computing. It is intended for system administrators, developers, and architects who are new to the cloud and need a structured framework to understand the rapidly evolving cloud-native landscape and evaluate which technologies best align with their organizational needs. The course introduces the fundamental service models—Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Container as a Service (CaaS)—and explains how virtualization, containers, and orchestration technologies enable scalable and flexible infrastructure. Learners gain hands-on exposure to container fundamentals using Docker, along with conceptual grounding in microservices, container orchestration, and emerging execution models such as unikernels and serverless computing.
Beyond compute, the course explores software-defined networking and software-defined storage, highlighting how networking, storage, and observability are reimagined in cloud-native systems. It also covers essential DevOps practices and tooling, including CI/CD, configuration management, image building, logging, monitoring, distributed tracing, and service meshes, providing a holistic view of how modern cloud platforms are built and operated. Finally, the course addresses advanced and forward-looking topics such as IoT integration and operational best practices, helping learners understand both the opportunities and challenges of cloud adoption.
By the end of the course, participants develop a solid foundational understanding of cloud infrastructure and open-source cloud technologies, enabling them to make informed decisions, collaborate effectively across development and operations teams, and prepare for more specialized cloud and platform engineering paths.

Who Is It For

This class is designed for people who have little or no prior experience with cloud technologies. System administrators, developers, and architects new to the cloud can all benefit from the content covered in this class, especially if they are looking to evaluate which cloud technologies might be the best fit for their organization.

What You’ll Learn

In this course you will receive an overview of common cloud technologies, an introduction to Iaas, PaaS, CaaS, and learn about basic operations with containers and images using Docker command, software-defined networking and software-defined storage solutions, the skill sets needed to deliver next generation cloud, and the challenges of cloud technologies.

What It Prepares You For

You will walk away from this course with an understanding of cloud computing and the use of open source software to maximize development and operations.

Course Outline

Chapter 1. Virtualization Chapter 2. Infrastructure as a Service (IaaS) Chapter 3. Platform as a Service (PaaS) Chapter 4. Containers Chapter 5. Containers: Micro OSes for Containers Chapter 6. Containers: Container Orchestration Chapter 7. Unikernels Chapter 8. Microservices Chapter 9. Software-Defined Networking and Networking for Containers Chapter 10. Software-Defined Storage and Storage Management for Containers Chapter 11. DevOps and CI/CD Chapter 12. Tools for Cloud Infrastructure: Configuration Management Chapter 13. Tools for Cloud Infrastructure: Build & Release Chapter 14. Tools for Cloud Infrastructure: Key-Value Pair Store Chapter 15. Tools for Cloud Infrastructure: Image Building Chapter 16. Tools for Cloud Infrastructure: Debugging, Logging, and Monitoring for Containerized Applications Chapter 17. Service Mesh Chapter 18. Internet of Things (IoT) Chapter 19. Serverless Computing Chapter 20. Distributed Tracing Chapter 21. How To Be Successful in the Cloud

Official link here

Description

Introduction to DevOps and Site Reliability Engineering (LFS162) is a foundational course that provides a structured introduction to the principles, practices, and cultural shifts that underpin modern software delivery and reliable system operations. It is designed both for managers seeking guidance on how to initiate and lead organizational transformation, and for engineers who aspire to build a career in DevOps and Site Reliability Engineering (SRE).
The course explains how DevOps practices have reshaped software development and operations by breaking down silos, accelerating delivery cycles, and improving collaboration. It explores the role of cloud computing and container technologies, with Kubernetes as a central platform, in enabling scalable, resilient, and repeatable application deployments. Learners are introduced to the motivations and practical implementation of Infrastructure as Code, highlighting how infrastructure automation improves consistency, traceability, and operational confidence.
In addition, the course covers CI/CD pipelines and their role in delivering software safely and continuously, as well as the fundamentals of observability, including what to monitor, why it matters, and how observability supports system reliability. The final sections introduce Site Reliability Engineering, presenting SRE as a disciplined engineering approach to balancing feature velocity with system stability and reliability.
By the end of the course, participants gain a solid understanding of DevOps and SRE foundations, equipping them with the conceptual and practical knowledge needed to deploy and operate software systems with speed, resilience, and high reliability in modern cloud-native environments.

Who Is It For

If you are a manager looking for guidelines on how to start transforming organizations, and understand where to start, this course is for you. If you aspire to make a career in the world of DevOps and Site Reliability Engineering, this course is your starting point.

What You’ll Learn

In this course you will learn how DevOps is influencing software delivery, how cloud computing has enabled organizations to rapidly build and deploy products and expand capacity, how the open container ecosystem, with Kubernetes in the lead, is truly revolutionizing software delivery, and the why, what and how of writing Infrastructure as Code. The course also covers Continuous Deployment and Continuous Delivery (CI/CD), as well as the role played by observability systems, what to observe and why.

What It Prepares You For

Upon completion, you should have a good understanding of the foundation, principles, and practices of DevOps and Site Reliability Engineering, and have gained the knowledge and skills to understand how to deploy software with confidence, agility and high reliability using modern DevOps and SRE practices.

Course Outline

Chapter 1. Welcome! Chapter 2. Introduction to DevOps and Site Reliability Engineering Chapter 3. Introduction to Cloud Chapter 4. Introduction to Containers Chapter 5. Infrastructure as Code Chapter 6. Continuous Integration/Continuous Delivery Chapter 7. Introduction to Observability Chapter 8. Site Reliability Engineering