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

AI-driven deployment orchestration is an approach that leverages machine learning and automation to guide deployment strategies, identify anomalies, and initiate automatic rollback when necessary.

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

Upon completing this training, participants will be able to:

• Implement AI-assisted rollout strategies to ensure safer deployments.
• Predict deployment risks using insights derived from machine learning.
• Integrate automated rollback processes based on anomaly detection.
• Improve observability to support intelligent orchestration.

Format of the Course

• Instructor-led demonstrations combined with in-depth technical discussions.
• Hands-on scenarios focused on deployment experimentation.
• Practical labs that simulate 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, particularly 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 as they adopt these approaches.

The training concludes with an exam. Successfully passing it awards the globally recognized AIOps Foundation certification, which is 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 incidents before they happen and automate root cause analysis (RCA) to reduce downtime and speed up resolution.

This instructor-led, live training (online or on-site) is designed for advanced-level IT professionals who want to implement predictive analytics, automate remediation, and design 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 logs and metrics from multiple sources.
• 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 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.

AIOps (Artificial Intelligence for IT Operations) is a practice that leverages machine learning and analytics to automate and enhance IT operations, particularly in the areas of 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 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 across logs, metrics, and traces to pinpoint root causes.
• Minimize alert fatigue through intelligent filtering and noise suppression.
• Utilize open-source or commercial tools for automatic monitoring and incident response.

Format of the Course

• Interactive lectures and discussions.
• Extensive 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.

An AIOps pipeline constructed entirely with open-source tools enables teams to create 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 aim to build and deploy a comprehensive AIOps pipeline using tools such as Prometheus, ELK, Grafana, and custom ML models.

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

• Design an AIOps architecture using exclusively 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-source tools.

Format of the Course

• Interactive lecture and discussion sessions.
• 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-driven test generation involves a set 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 aimed at advanced-level professionals who wish to apply AI methods to generate tests automatically and identify areas with insufficient coverage.

Upon completing this workshop, participants will be equipped to:

• Utilize AI models to create effective unit, integration, and end-to-end test scenarios.
• Analyze codebases using machine learning to identify potential coverage blind spots.
• Integrate AI-based test generation into CI/CD workflows.
• Refine test strategies based on predictive failure analytics.

Format of the Course

• Guided technical lectures complemented by expert insights.
• Scenario-based practice sessions and hands-on exercises.
• Applied experimentation within a controlled testing environment.

Course Customization Options

• If you require this 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 online or on-site) is designed for intermediate-level QA and DevOps professionals who want to leverage AI tools to automate and scale 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.
• Utilize AI for exploratory testing, defect prediction, and test flakiness analysis.
• Optimize testing time and coverage across fast-paced agile projects.

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-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 wish to integrate AI-driven compliance controls into their CI/CD pipelines.

After completing this training, participants will be equipped to:

• Use AI-based checks to identify compliance gaps during software builds.
• Employ 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 that helps automate various development tasks, including DevOps activities such as writing YAML configurations, setting up GitHub Actions, and creating deployment scripts.

This instructor-led, live training (available online or on-site) is designed for professionals at beginner to intermediate levels who want to leverage GitHub Copilot to streamline their DevOps processes, enhance automation, and increase productivity.

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

• Utilize GitHub Copilot for shell scripting, configuration management, and CI/CD pipeline development.
• Take advantage of AI-driven code suggestions in YAML files and GitHub Actions.
• Speed up testing, deployment, and automation workflows.
• Use Copilot responsibly, with an understanding of its limitations and best practices.

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.

DevSecOps with AI involves integrating artificial intelligence into DevOps workflows 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 leverage AI-based tools and practices to enhance security automation in their development and deployment processes.

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 assessment.
• Implement proactive threat modeling and policy enforcement using intelligent methods.

Format of the Course

• Interactive lectures and discussions.
• 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 features for identifying anomalies, correlating alerts, and automating responses in large-scale IT environments.

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

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

• Set up and integrate Splunk, Moogsoft, and Dynatrace into a cohesive AIOps architecture.
• Use AI-driven analysis to correlate metrics, logs, and events across distributed systems.
• Automate incident detection, prioritization, and response with both built-in and custom workflows.
• Enhance performance, reduce mean time to resolution (MTTR), and improve operational efficiency at the 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 adopted tools for observability in modern infrastructure. Machine learning enhances these tools by providing predictive and intelligent insights that can automate operational decisions.

This instructor-led, live training (online or onsite) is aimed at intermediate-level observability professionals who want to modernize their monitoring infrastructure 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 systems and services.
• Collect, store, and visualize high-quality time series data effectively.
• Apply machine learning models to detect anomalies and make forecasts.
• Develop intelligent alerting rules based on predictive insights.

Format of the Course

• Interactive lectures and discussions.
• Numerous exercises and practical 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.

Large language models (LLMs) and autonomous agent frameworks such as AutoGen and CrewAI are revolutionizing how 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 onsite) is designed for advanced-level engineers who want to design and implement DevOps automation workflows driven by 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 to achieve intelligent automation.
• Automate test generation, commit analysis, and change summaries using these agents.
• Coordinate multiple agents for tasks such as alert triage, response generation, and DevOps recommendations.
• Create secure and maintainable agent-powered workflows using open-source frameworks.

Format of the Course

• Interactive lectures and discussions.
• Plenty of 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.

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

This instructor-led, live training (available both online and on-site) is designed for intermediate-level engineering professionals who want to optimize their build pipelines through automation, predictive analytics, and intelligent caching techniques.

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

• Utilize machine learning 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 led by an instructor and interactive discussions.
• Practical exercises centered 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 for customized program options.

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 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 resolve failures immediately.
• Implement intelligent feedback loops to prevent recurring issues.
• Enhance the overall resilience and reliability of CI/CD systems.

Format of the Course

• Expert-led presentations with real-world examples.
• Applied exercises focused on pipeline reliability challenges.
• Hands-on development of automated resolution mechanisms in a lab environment.

Course Customization Options

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