AI for DevOps: Integrating Intelligence into CI/CD Pipelines Training Course

AI-driven deployment orchestration is a method that leverages machine learning and automation to manage deployment strategies, identify anomalies, and initiate automatic rollbacks when necessary.

This instructor-led, live training (available online or on-site) is designed for intermediate-level professionals who want to enhance their deployment pipelines with AI-powered decision-making and resilience features.

Upon completing this training, participants will be able to:

• Implement AI-assisted deployment strategies for safer rollouts.
• Anticipate deployment risks using insights derived from machine learning.
• Incorporate automated rollback processes based on anomaly detection.
• Improve observability to support intelligent orchestration.

Format of the Course

• Instructor-led demonstrations with in-depth technical explanations.
• Hands-on scenarios focused on deployment experimentation.
• Practical labs simulating real-world orchestration challenges.

Course Customization Options

• Customized integrations, toolchain support, or workflow alignment can be arranged upon request.

AIOps is a rapidly evolving field that addresses the needs of modern, complex IT environments, especially those operating within cloud architectures. The AIOps Foundation course provides a comprehensive introduction to the concepts, technologies, and practices related to using artificial intelligence in IT operations.

The program delves into the background of AIOps, its core principles, tools, and the organizational challenges faced by IT teams when adopting these approaches.

The training concludes with an exam. Successfully passing it earns you the globally recognized AIOps Foundation certification, which remains valid for three years.

Who is it for?

This course is designed for professionals and managers involved in:

IT operations

DevOps and Site Reliability Engineering (SRE)

Cloud architecture

Data analysis and Data Science

Software development

IT security

Product and project management

AIOps (Artificial Intelligence for IT Operations) is increasingly being utilized to predict and prevent incidents before they occur, as well as to automate root cause analysis (RCA) in order to minimize downtime and speed up resolution.

This instructor-led, live training (available both online and onsite) is designed for advanced-level IT professionals who are interested in implementing predictive analytics, automating remediation processes, and designing intelligent RCA workflows using AIOps tools and machine learning models.

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

• Develop and train machine learning models to identify patterns that lead to system failures.
• Automate RCA workflows by correlating data from multiple log sources and metrics.
• Integrate alerting and remediation processes into existing platforms.
• Deploy and scale intelligent AIOps pipelines in production environments.

Format of the Course

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

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

AIOps (Artificial Intelligence for IT Operations) is a practice that leverages machine learning and analytics to automate and enhance IT operations, particularly in monitoring, incident detection, and response.

This instructor-led, live training (available online or on-site) is designed for intermediate-level IT operations professionals who want to implement AIOps techniques. The goal is to correlate metrics and logs, reduce alert noise, and improve observability through intelligent automation.

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

• Understand the principles and architecture of AIOps platforms.
• Correlate data from logs, metrics, and traces to identify root causes.
• Minimize alert fatigue through intelligent filtering and noise reduction.
• Use open-source or commercial tools to monitor and automatically respond to incidents.

Format of the Course

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

Course Customization Options

• For customized training for this course, please contact us to arrange.

An AIOps pipeline constructed entirely with open-source tools enables teams to develop cost-effective and flexible solutions for observability, anomaly detection, and intelligent alerting in production environments.

This instructor-led, live training (available online or on-site) is designed for advanced-level engineers who want to build and deploy a comprehensive AIOps pipeline using tools such as Prometheus, ELK, Grafana, and custom machine learning models.

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

• Design an AIOps architecture using only open-source components.
• Collect and normalize data from logs, metrics, and traces.
• Apply machine learning models to detect anomalies and predict incidents.
• Automate alerting and remediation processes using open tooling.

Format of the Course

• Interactive lectures and discussions.
• Numerous exercises and practice sessions.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

AI-driven test generation involves a range of techniques and tools designed to automate the creation of test cases and predict testing gaps using machine learning.

This instructor-led, live training (available online or on-site) is targeted at advanced-level professionals who aim to apply AI methods to automatically generate tests and identify areas with inadequate coverage.

Upon completing this workshop, participants will be equipped to:

• Utilize AI models to create effective unit, integration, and end-to-end test scenarios.
• Use machine learning to analyze codebases and identify potential coverage issues.
• Incorporate AI-based test generation into CI/CD workflows.
• Enhance test strategies using predictive failure analytics.

Format of the Course

• Guided technical lectures with expert insights.
• Practice sessions and hands-on exercises based on real scenarios.
• Practical experimentation in a controlled testing environment.

Course Customization Options

• If you require the training to be tailored to your specific toolchain or workflows, please contact us to arrange.

AI-powered QA automation enhances traditional testing methods by creating intelligent test cases, optimizing regression coverage, and integrating smart quality gates into CI/CD pipelines, ensuring scalable and reliable software delivery.

This instructor-led, live training (available both online and onsite) is designed for intermediate-level QA and DevOps professionals who want to leverage AI tools to automate and scale their quality assurance processes in continuous integration and deployment workflows.

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

• Generate, prioritize, and maintain tests using AI-driven automation platforms.
• Integrate intelligent QA gates into CI/CD pipelines to prevent regressions.
• Use AI for exploratory testing, defect prediction, and analyzing test flakiness.
• Optimize testing time and coverage in fast-paced agile projects.

Format of the Course

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

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

AI-supported compliance monitoring is a field that leverages intelligent automation to detect, enforce, and validate policy requirements throughout the software delivery lifecycle.

This instructor-led, live training (available online or on-site) is designed for intermediate-level professionals who want to integrate AI-driven compliance controls into their CI/CD pipelines.

After completing this training, participants will be able to:

• Use AI-based checks to identify compliance gaps during software builds.
• Utilize intelligent policy engines to enforce regulatory, security, and licensing standards.
• Automatically detect configuration drift and deviations.
• Integrate real-time compliance reporting into delivery workflows.

Format of the Course

• Instructor-guided presentations accompanied by practical examples.
• Hands-on exercises focused on real-world CI/CD compliance scenarios.
• Applied experimentation within a controlled DevSecOps lab environment.

Course Customization Options

• If your organization requires customized compliance integrations, please contact us to arrange.

GitHub Copilot is an AI-driven coding assistant designed to automate various development tasks, including DevOps operations such as writing YAML configurations, GitHub Actions, and deployment scripts.

This instructor-led, live training (available both online and onsite) is tailored for professionals at the beginner to intermediate level who are looking to leverage GitHub Copilot to streamline their DevOps tasks, enhance automation, and increase productivity.

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

• Utilize GitHub Copilot to assist with shell scripting, configuration management, and CI/CD pipelines.
• Take advantage of AI-driven code completion in YAML files and GitHub Actions.
• Speed up testing, deployment, and automation workflows.
• Use Copilot effectively while being aware of its limitations and best practices.

Format of the Course

• Interactive lectures and discussions.
• Numerous exercises and hands-on practice.
• Practical implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

DevSecOps with AI involves integrating artificial intelligence into DevOps pipelines to proactively identify vulnerabilities, enforce security policies, and automate response actions throughout the software delivery lifecycle.

This instructor-led, live training (available online or on-site) is designed for intermediate-level DevOps and security professionals who want to apply AI-based tools and practices to enhance security automation across development and deployment pipelines.

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

• Integrate AI-driven security tools into CI/CD pipelines.
• Utilize static and dynamic analysis powered by AI to detect issues at an earlier stage.
• Automate the detection of secrets, code vulnerability scanning, and dependency risk analysis.
• Implement proactive threat modeling and policy enforcement using intelligent techniques.

Format of the Course

• Interactive lecture and discussion sessions.
• Extensive exercises and practical activities.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Enterprise AIOps platforms such as Splunk, Moogsoft, and Dynatrace offer robust capabilities for detecting anomalies, correlating alerts, and automating responses in large-scale IT environments.

This instructor-led, live training (available online or on-site) is designed for intermediate-level enterprise IT teams who want to integrate AIOps tools into their existing observability stack and operational workflows.

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

• Configure and integrate Splunk, Moogsoft, and Dynatrace into a unified AIOps architecture.
• Correlate metrics, logs, and events across distributed systems using AI-driven analysis.
• Automate incident detection, prioritization, and response with both built-in and custom workflows.
• Optimize performance, reduce mean time to resolution (MTTR), and enhance operational efficiency at an enterprise level.

Format of the Course

• Interactive lectures and discussions.
• Numerous exercises and practice sessions.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Prometheus and Grafana are widely used tools for observability in modern infrastructure. Machine learning enhances these tools by providing predictive and intelligent insights, which help automate operational decisions.

This instructor-led, live training (available online or on-site) is designed for intermediate-level observability professionals who wish to modernize their monitoring systems by integrating AIOps practices using Prometheus, Grafana, and machine learning techniques.

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

• Configure Prometheus and Grafana for comprehensive observability across various systems and services.
• Collect, store, and visualize high-quality time series data effectively.
• Apply machine learning models to detect anomalies and make forecasts.
• Create intelligent alerting rules based on predictive insights.

Format of the Course

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

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Large language models (LLMs) and autonomous agent frameworks such as AutoGen and CrewAI are transforming the way DevOps teams automate tasks like change tracking, test generation, and alert triage by mimicking human-like collaboration and decision-making processes.

This instructor-led, live training (available online or on-site) is designed for advanced-level engineers who want to design and implement DevOps automation workflows using large language models (LLMs) and multi-agent systems.

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

• Integrate LLM-based agents into CI/CD workflows for intelligent automation.
• Automate test generation, commit analysis, and change summaries using these agents.
• Coordinate multiple agents for alert triaging, response generation, and DevOps recommendations.
• Create secure and maintainable agent-powered workflows using open-source frameworks.

Format of the Course

• Interactive lecture and discussion sessions.
• Ample exercises and practice opportunities.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Predictive build optimization involves using machine learning to analyze build behavior and enhance reliability, speed, and resource efficiency.

This instructor-led, live training (available online or onsite) is designed for intermediate-level engineering professionals who want to improve their build pipelines through automation, predictive analytics, and intelligent caching with the help of machine learning techniques.

Upon completing this course, participants will be able to:

• Use ML methods to evaluate build performance trends.
• Identify and forecast build failures by analyzing past build logs.
• Implement caching strategies driven by machine learning to shorten build times.
• Incorporate predictive analytics into existing CI/CD workflows.

Format of the Course

• Guided lectures and interactive discussions led by an instructor.
• Practical exercises focused on analyzing and modeling build data.
• Hands-on implementation within a simulated CI/CD environment.

Course Customization Options

• To tailor this training to specific toolchains or environments, please contact us to customize the program.

Self-healing automation involves the use of intelligent systems to detect pipeline failures, pinpoint root causes, and initiate real-time recovery actions.

This instructor-led, live training (available online or on-site) is designed for advanced-level professionals who aim to integrate AI-driven incident detection and automated remediation into their delivery pipelines.

Upon completing this course, participants will be able to:

• Monitor pipelines using AI-based anomaly detection models.
• Design automated recovery workflows to address failures immediately.
• Implement intelligent feedback loops to prevent recurring issues.
• Improve overall resilience and reliability in CI/CD systems.

Format of the Course

• Expert-led presentations with practical examples from real-world scenarios.
• Applied exercises focused on enhancing pipeline reliability.
• Hands-on development of automated resolution mechanisms in a laboratory setting.

Course Customization Options

• For content tailored to your organization’s workflows or incident-response needs, please contact us to arrange.