DevOps Training in Maia

This instructor-led, live training in Maia (online or onsite) is aimed at intermediate-level to advanced-level DevOps engineers and IT operations staff who wish to leverage n8n for automating, monitoring, and optimizing CI/CD workflows.

By the end of this training, participants will be able to:

• Set up and configure n8n for DevOps automation.
• Integrate n8n with CI/CD tools like Jenkins, GitLab, and GitHub Actions.
• Automate build, test, and deployment workflows using n8n.
• Monitor and troubleshoot CI/CD pipelines with n8n dashboards.
• Enhance DevOps workflows with custom n8n nodes and scripts.

This instructor-led, live training in Maia (online or onsite) is aimed at advanced-level AI/ML engineers, data scientists, and tech innovators who wish to integrate AI capabilities into Make workflows to optimize and automate processes.

By the end of this training, participants will be able to:

• Understand AI and machine learning capabilities in automation.
• Integrate AI/ML models into Make workflows using APIs.
• Implement sentiment analysis, predictive modeling, and data-driven decision-making.
• Optimize and scale AI-driven automation workflows.

This instructor-led, live training in Maia (online or onsite) is designed for intermediate-level software developers, system administrators, and IT project managers who wish to enhance their skills in building and managing automated, scalable, and collaborative IT environments.

Upon completing this training, participants will be able to:

• Grasp the fundamental principles and advantages of DevOps and Platform Engineering.
• Implement Infrastructure as Code (IaC) and automate the provisioning of IT infrastructure.
• Construct and maintain Continuous Integration and Continuous Delivery (CI/CD) pipelines.
• Deploy and manage microservices using containerization tools such as Docker and Kubernetes.
• Embed security practices into the software development lifecycle through DevSecOps.
• Apply observability techniques to monitor and enhance system reliability.

Delivered as an instructor-led, live training session in Maia (online or onsite), this programme is designed for advanced developers and technical consultants aiming to craft tailored automation solutions and extend n8n’s capabilities to meet specific organisational requirements.

Upon completion, participants will be capable of:

• Configuring a development environment for building custom nodes within n8n.
• Creating custom nodes to address distinct business use cases.
• Testing and debugging custom nodes within a controlled setting.
• Deploying and maintaining custom nodes for production environments.

This instructor-led, live training in Maia (online or onsite) is aimed at advanced-level professionals who wish to deploy fine-tuned models reliably and efficiently.

By the end of this training, participants will be able to:

• Understand the challenges of deploying fine-tuned models into production.
• Containerize and deploy models using tools like Docker and Kubernetes.
• Implement monitoring and logging for deployed models.
• Optimize models for latency and scalability in real-world scenarios.

This instructor-led live training in Maia (online or onsite) targets advanced-level DevOps teams and IT architects who wish to utilise Kubiya AI to automate and optimise enterprise-level DevOps operations.

By the conclusion of this training, participants will be able to:

• Customize Kubiya AI for specific enterprise DevOps environments.
• Integrate Kubiya AI with CI/CD tools used in enterprise DevOps.
• Enhance DevOps automation with AI-driven workflows.
• Ensure security and compliance within AI-driven DevOps processes.

This instructor-led, live training in Maia (online or onsite) is aimed at intermediate-level e-commerce professionals who wish to automate order processing, payments, and customer support using Zapier.

By the end of this training, participants will be able to:

• Automate order processing and fulfillment.
• Sync payment data with accounting systems.
• Enhance customer support through automation.
• Optimise marketing and sales workflows.

This instructor-led, live training in Maia (online or onsite) is designed for intermediate DevOps professionals seeking to integrate security into their practices, with a focus on automating security checks and processes within a CI/CD pipeline.

Upon completion of this training, participants will be capable of:

• Understanding the core principles of integrating security into the DevOps workflow.
• Automating security checks using Jenkins and integrating tools such as SonarQube for code analysis and vulnerability scanning.
• Deploying secure applications using Kubernetes.
• Ensuring secure communication between microservices via RabbitMQ, PostgreSQL, and MongoDB.
• Establishing continuous monitoring and auditing to guarantee compliance and security across all deployments.

This instructor-led, live training in Maia (online or onsite) is aimed at developers and IT professionals of all skill levels who wish to automate tasks and processes using AI without writing extensive code.

By the end of this training, participants will be able to:

• Design and implement complex workflows using n8n's visual programming interface.
• Integrate AI capabilities into workflows using LangChain.
• Build custom chatbots and virtual assistants for various use cases.
• Perform advanced data analysis and processing with AI agents.

This instructor-led, live training in Maia (online or onsite) is targeted at intermediate-level DevOps engineers and CI/CD managers who wish to enhance their pipelines with AI automation using Kubiya AI.

By the conclusion of this training, participants will be able to:

• Understand the fundamentals of integrating AI into DevOps pipelines.
• Implement Kubiya AI within popular CI/CD tools such as Jenkins and GitLab CI.
• Automate CI/CD pipeline tasks with Kubiya AI.
• Monitor and manage CI/CD pipelines using AI for proactive problem detection.

This instructor-led live training in Maia (online or onsite) is designed for intermediate-level marketing professionals seeking to automate repetitive tasks, effectively nurture leads, and enhance customer engagement through workflow automation.

Upon completion of this training, participants will be able to:

• Utilize Make to automate marketing campaigns and lead nurturing workflows.
• Develop personalized customer journey maps via integrated platforms.
• Synchronize data across marketing tools such as Mailchimp, HubSpot, and social media platforms.
• Monitor and analyze automated workflows to optimize campaign performance.
• Implement best practices for scalable marketing automation strategies.

This instructor-led live training in Maia (online or onsite) is aimed at advanced-level DevOps engineers and automation specialists who wish to deepen their understanding of Kubiya AI and leverage its full capabilities for large-scale operations.

By the end of this training, participants will be able to:

• Automate complex workflows using Kubiya AI.
• Customize AI responses and actions.
• Scale DevOps operations with Kubiya AI.
• Troubleshoot and optimize Kubiya AI implementations.
• Understand and implement security and compliance measures.
• Integrate Kubiya AI with advanced CI/CD tools and additional cloud services.
• Set up performance monitoring and create custom reports.

This instructor-led, live training in Maia (online or onsite) is aimed at intermediate-level participants who wish to explore workflow automation with Google AI Studio, leveraging its tools to create, optimize, and manage efficient automated processes.

By the end of this training, participants will be able to:

• Understand the core features of Google AI Studio for workflow automation.
• Set up and integrate Google AI Studio with other tools.
• Design and execute AI-driven workflows.
• Implement conditional logic for smarter automation.
• Monitor and optimize automated workflows for efficiency.

This instructor-led, live training in Maia (online or onsite) is aimed at intermediate-level participants who wish to optimize workflow performance, handle complex dependencies, and scale Apache Airflow deployments for larger datasets and enterprise use cases.

By the end of this training, participants will be able to:

• Optimize Apache Airflow workflows for better performance and reliability.
• Manage and troubleshoot complex workflow dependencies.
• Leverage advanced Airflow features, including custom operators and sensors.
• Scale Apache Airflow for handling larger data sets and distributed systems.
• Implement best practices for monitoring, logging, and security in Airflow environments.

This instructor-led live training in Maia (online or onsite) targets intermediate-level IT professionals and automation engineers who wish to master Make’s advanced features, optimize complex workflows, and handle error management effectively.

Upon completion of this training, participants will be able to:

• Leverage advanced Make features for workflow automation.
• Optimize workflows through conditional logic, iterators, and error handling.
• Integrate multiple applications to achieve seamless automation.
• Monitor and troubleshoot workflows to ensure maximum efficiency.
• Apply best practices for scaling workflow automation solutions.

Apache Airflow is an open-source platform designed for authoring, scheduling, and monitoring workflows. With the release of Airflow 2.x, organizations can orchestrate large-scale data pipelines, integrate seamlessly with cloud services, and ensure robust observability and security within production environments.

This instructor-led live training, available online or onsite, is tailored for beginner to intermediate data and DevOps professionals aiming to leverage Apache Airflow to build, automate, and scale end-to-end data pipelines.

Upon completion of this training, participants will be capable of:

• Installing and configuring Apache Airflow across various environments.
• Authoring, scheduling, and monitoring DAGs using the TaskFlow API.
• Integrating Airflow with data sources, cloud services, and machine learning workflows.
• Managing ETL pipelines while ensuring data reliability.
• Securing and scaling Airflow through the use of executors, queues, and Kubernetes.
• Implementing observability and adhering to best practices for production deployments.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practical practice sessions.
• Hands-on implementation within a live-lab environment.

Course Customization Options

• To request a customized training session for this course, please contact us to make arrangements.

This instructor-led, live training in Maia (online or onsite) is tailored for DevOps practitioners and IT managers at the beginner level who wish to investigate the capabilities of Kubiya AI and incorporate it into their existing toolsets.

Upon completion of this training, participants will be able to:

• Comprehend the features and advantages of Kubiya AI.
• Deploy and configure Kubiya AI within their operational environment.
• Execute fundamental use cases for Kubiya AI within DevOps contexts.
• Connect Kubiya AI with current DevOps infrastructure.

SonarQube is a platform dedicated to the continuous inspection of code quality and security via static analysis and reporting tailored for developers.

This instructor-led live training, available either online or onsite, targets intermediate-level developers, DevOps engineers, and security professionals aiming to implement static code analysis, integrate SonarQube into Azure DevOps pipelines, and reinforce secure development practices.

Upon completing this training, participants will be capable of:

• Explaining SonarQube’s architecture, core features, and security-centric rule sets.
• Configuring SonarScanner alongside common build tools such as Maven, Gradle, and Ant.
• Integrating SonarQube into Azure DevOps pipelines and importing Azure Repos for continuous analysis.
• Defining and adjusting analysis parameters, adding custom rules via the SonarQube API, and interpreting security reports.
• Implementing improvements to secure development methodologies and mapping responsibilities within the CI/CD process.
• Conducting hands-on analyses across sample repositories (Java + Quarkus and Angular) and addressing identified issues.

Format of the Course

• Interactive lectures and discussions.
• Guided, practical hands-on labs utilizing real repositories.
• Live configuration, testing, and troubleshooting within an Azure DevOps and SonarQube environment.

Course Customization Options

• To request a customized version of this training (such as different language stacks, deeper DevOps integration, or expanded labs), please contact us to arrange.

The SRE Practitioner Certification Preparation programme is a thorough training initiative designed to cover advanced Site Reliability Engineering practices, fully aligned with the official DevOps Institute syllabus, ensuring participants are well-prepared for certification success.

This instructor-led, live training (available online or onsite) is tailored for experienced DevOps and SRE professionals who aim to master advanced SRE practices and prepare for the DevOps Institute SRE Practitioner certification exam.

Upon completion of this training, participants will be able to:

• Identify and address common SRE anti-patterns.
• Define and manage SLIs, SLOs, and error budgets effectively.
• Design systems that are secure, fault-tolerant, and highly reliable.
• Implement advanced strategies for observability, automation, and incident response.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practical application.
• Hands-on implementation in a live-lab environment.

Customisation Options

• To arrange a customised training session for this course, please contact us.

This instructor-led, live training in Maia (online or onsite) is aimed at engineering and design professors who wish to understand, apply, and teach modern software development practices relevant to systems engineering, civil engineering, design, and architecture disciplines.

This instructor-led, live training in Maia (online or onsite) is aimed at DevOps engineers, developers, and SysOps administrators who wish to maximize the tools and features made available through the Ansible project for the advancement of organizational IT infrastructures and processes.

Simultaneously, they can utilize the opportunity to carry out complex Ansible implementations for large-scale applications while employing its open-sourced tower for optimized DevOps management and collaboration functions.

By the end of this training, participants will be able to:

• Install and configure Ansible along with other open-source tools and resources.
• Establish a centralized system for DevOps management using Ansible project features.
• Operate automation tools and advanced resources of Ansible to achieve CI/CD approach.
• Execute better SysOps methods using Ansible's collaborative features for management of larger teams.
• Enhance DevOps tasks execution within the organization and optimize existing ones.
• Integrate Ansible with external platforms and leverage other Ansible tools for the organization's advantage.

This intensive 7-day programme offers a thorough, practical exploration of designing, deploying, and managing cloud-native applications through contemporary DevOps methodologies.

Attendees will investigate techniques for architecting scalable microservices infrastructures, refining container environments, and handling production workloads via Kubernetes. The curriculum encompasses sophisticated deployment tactics, GitOps-driven automation, and observability strategies to guarantee system dependability and efficiency.

Significant emphasis is placed on addressing practical operational difficulties, such as incident handling, failure simulation, and root cause analysis. The programme finishes by integrating AI-powered tools to facilitate troubleshooting and expedite operational decision-making.

Upon completion, participants will possess a robust comprehension of how to construct, deploy, monitor, and sustain resilient distributed systems within a Kubernetes ecosystem.

In this instructor-led, live course in Maia, participants will learn how to formulate an effective security strategy to address the challenges of DevOps security.

This premier, state-of-the-art, practical workshop places participants directly into the critical realities of securing modern CI/CD pipelines. Tailored for security specialists, DevOps engineers, and developers keen to master advanced breach defense, the training combines live attack simulations with industry-leading tools and practical defensive strategies.

This instructor-led, live training in Maia (online or onsite) is aimed at DevOps engineers and infrastructure architects who wish to automate the provisioning, monitoring, and lifecycle management of private AI clusters built on EXO.

This instructor-led, live training in Maia (online or onsite) is aimed at engineers who wish to use Jenkins 2 to build pipelines that automate the process of moving an application from development to production.

By the end of this training, participants will be able to:

• Install and configure Jenkins 2.
• Adopt a script approach to automating every step of the software deployment process.
• Automatically generate application builds when software is checked into a version control system.
• Automatically kick off the compiling, testing, and packaging of a software application.
• Quickly respond to notifications and reports when things go wrong.
• Install additional plugins to extend Jenkins.

This instructor-led, live training in Maia (online or onsite) is designed for engineers looking to evaluate current approaches and tools. The course helps participants make informed decisions about adopting MLOps within their organizations.

Upon completion, participants will be able to:

• Install and configure various MLOps frameworks and tools.
• Build a skilled team capable of constructing and supporting an MLOps system.
• Prepare, validate, and version data for consumption by ML models.
• Understand the components of an ML Pipeline and the necessary tools to construct one.
• Experiment with different machine learning frameworks and servers for production deployment.
• Operationalize the entire Machine Learning lifecycle to ensure it is reproducible and maintainable.

This management-oriented DevOps course offers a thorough grasp of contemporary software delivery practices, integrating DevOps culture, processes, tools, and business strategy. Through a mix of presentations, demonstrations, hands-on labs, and workshops, participants examine the entire DevOps lifecycle, ranging from version control and CI/CD pipelines to containers, infrastructure automation, security integration, and reliability engineering.

Moving beyond mere technical concepts, the programme emphasizes the managerial dimensions of DevOps adoption, such as organizational change, maturity assessment, performance measurement, and the creation of business value. Participants engage with real-world scenarios and their own projects to pinpoint areas for improvement, evaluate current delivery practices, and develop actionable plans for implementing DevOps within their organizations.

This instructor-led, live training in Maia (online or onsite) is aimed at DevOps engineers and developers who wish to use SonarQube to run code reviews that are fully-integrated into development tool chains, such as Jenkins, GitHub, Azure DevOps, etc.

By the end of this training, participants will be able to:

• Set up the necessary development environment to start running automatic code reviews.
• Integrate SonarQube with continuous integration tools, such as Jenkins, Azure DevOps, etc.
• Run continuous code inspections to eliminate bugs and security vulnerabilities.
• Collect and analyze data to drive improvements for code cleanup, maintenance, and security.

This capstone course teaches participants to design, deploy, and operate a complete sovereign digital infrastructure stack from the ground up. By the end of the course, students will have built a functioning mini-organization using only self-hosted, open-source tools: identity, communication, productivity, development, security, AI, and monitoring - all without reliance on Google, Microsoft, AWS, or proprietary SaaS.