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

AI-driven deployment orchestration leverages machine learning and automation to guide rollout strategies, detect anomalies, and trigger automatic rollback when necessary.

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

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

• Implement AI-assisted rollout strategies for safer deployments.
• Predict deployment risk using machine learning–driven insights.
• Integrate automated rollback workflows based on anomaly detection.
• Enhance observability to support intelligent orchestration.

Format of the Course

• Instructor-led demonstrations with technical deep dives.
• 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.

AI-driven rollout control leverages machine learning, pattern analysis, and adaptive decision-making models to enhance feature flag operations and canary testing processes.

This instructor-led training, available both online and onsite, is designed for intermediate-level engineers and technical leads looking to improve release reliability and optimize feature exposure through AI-powered analysis.

After completing this course, participants will be able to:

• Utilize AI-based decision models to evaluate the risk associated with exposing new features.
• Automate canary analysis by leveraging performance, behavioral, and operational metrics.
• Incorporate intelligent scoring mechanisms into existing feature flag platforms.
• Develop rollout strategies that dynamically adjust in response to real-time data.

Course Format

• Facilitated discussions grounded in real-world scenarios.
• Practical exercises focused on AI-enhanced rollout strategies.
• Hands-on implementation within a simulated feature flag and canary testing environment.

Customization Options

• For customized content or integration with organization-specific tools, please get in touch.

AIOps represents a rapidly advancing discipline designed to meet the demands of contemporary, intricate IT ecosystems, especially those built on cloud infrastructure. The AIOps Foundation course provides a thorough introduction to the fundamental concepts, technologies, and best practices associated with applying artificial intelligence within IT operations.

The curriculum explores the historical context of AIOps, its foundational principles, essential tools, and the organizational hurdles IT teams encounter when adopting these methodologies.

The training program concludes with an examination. Successful completion awards the globally recognized AIOps Foundation certification, which remains valid for three years.

Target Audience

This course is tailored for professionals and managers engaged 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 used to predict incidents before they occur and automate root cause analysis (RCA) to minimize downtime and accelerate resolution.

This instructor-led, live training (online or onsite) is aimed at advanced-level IT professionals who wish 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:

• Build and train ML models to detect patterns leading to system failures.
• Automate RCA workflows based on multi-source log and metric correlation.
• Integrate alerting and remediation processes into existing platforms.
• Deploy and scale intelligent AIOps pipelines in production environments.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• 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 onsite) targets intermediate-level IT operations professionals looking to apply 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 identify root causes.
• Reduce alert fatigue through intelligent filtering and noise suppression.
• Use open-source or commercial tools to monitor and respond to incidents automatically.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• 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 developed entirely with open-source technologies enables teams to create cost-efficient and adaptable solutions for observability, anomaly detection, and intelligent alerting within production environments.

This instructor-led, live training (available online or onsite) targets advanced engineers seeking to design and deploy a comprehensive AIOps pipeline utilizing tools such as Prometheus, ELK, Grafana, and custom machine learning models.

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

• Architecting an AIOps system utilizing only open-source components.
• Gathering and standardizing data from logs, metrics, and traces.
• Employing ML models to identify anomalies and forecast incidents.
• Automating alerting and remediation processes using open tooling.

Course Format

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

Course Customization Options

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

AI-driven test generation encompasses a range of techniques and tools that automate the creation of test cases and predict testing gaps through machine learning.

This instructor-led, live training (available online or onsite) targets advanced-level professionals aiming to apply AI techniques to automatically generate tests and identify areas with insufficient coverage.

Upon completion of 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 detect potential blind spots in coverage.
• Integrate AI-based test generation into CI/CD workflows.
• Optimize test strategies by leveraging predictive failure analytics.

Course Format

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

Customization Options

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

AI-driven QA automation elevates conventional testing methods by creating intelligent test cases, refining regression coverage, and embedding smart quality checkpoints into CI/CD pipelines to ensure scalable and dependable software delivery.

This instructor-led live training (available online or onsite) targets intermediate QA and DevOps professionals seeking to leverage AI tools to automate and expand quality assurance within continuous integration and deployment workflows.

Upon completing this training, participants will be capable of:

• Creating, prioritizing, and maintaining tests using AI-powered automation platforms.
• Incorporating intelligent QA checkpoints into CI/CD pipelines to prevent regressions.
• Utilizing AI for exploratory testing, defect prediction, and analyzing test flakiness.
• Optimizing testing duration and coverage for rapidly evolving agile projects.

Course Format

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

Course Customization Options

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

AI-assisted compliance monitoring is a specialized 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 onsite) is designed for intermediate-level professionals looking to incorporate AI-driven compliance controls into their CI/CD pipelines.

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

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

Course Format

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

Customization Options

• For organizations requiring tailored compliance integrations, please contact us to arrange a custom solution.

CI/CD for AI offers a structured methodology for automating the packaging, testing, containerization, and deployment of models through continuous integration and delivery pipelines.

This instructor-led live training, available online or on-site, targets intermediate-level professionals seeking to automate end-to-end AI model delivery workflows using Docker and CI/CD platforms.

Upon completing the training, participants will be able to:

• Establish automated pipelines for building and testing AI model containers.
• Implement version control and reproducibility standards for model lifecycles.
• Integrate automated deployment strategies for AI services.
• Apply CI/CD best practices specifically tailored to machine learning operations.

Course Format

• Instructor-guided presentations and technical discussions.
• Practical labs and hands-on implementation exercises.
• Realistic CI/CD workflow simulations conducted in a controlled environment.

Course Customization Options

• If your organization requires customized pipeline workflows or platform integrations, please contact us to tailor this course.

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

This instructor-led live training (available online or onsite) targets beginner to intermediate professionals who want to use GitHub Copilot to streamline DevOps tasks, improve automation, and boost productivity.

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

• Use GitHub Copilot to assist with shell scripting, configuration, and CI/CD pipelines.
• Leverage AI code completion in YAML files and GitHub Actions.
• Accelerate testing, deployment, and automation workflows.
• Apply Copilot responsibly with an understanding of AI limitations and best practices.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on 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 workflows to proactively identify vulnerabilities, enforce security policies, and automate response mechanisms throughout the software development lifecycle.

This instructor-led training (available online or onsite) is designed for intermediate-level DevOps and security professionals looking to leverage AI-driven tools and methodologies to strengthen security automation within their development and deployment pipelines.

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

• Integrate AI-powered security tools into CI/CD pipelines.
• Utilize AI-enhanced static and dynamic analysis to identify issues at an earlier stage.
• Automate the detection of secrets, scanning for code vulnerabilities, and analyzing dependency risks.
• Implement proactive threat modeling and policy enforcement through intelligent techniques.

Course Format

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

Customization Options

• For tailored training on this subject, please contact us to make arrangements.

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

This instructor-led live training (available online or onsite) targets intermediate-level enterprise IT teams looking to integrate AIOps tools into their existing observability stack and operational workflows.

Upon completion 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 built-in and custom workflows.
• Optimize performance, reduce MTTR, and improve operational efficiency at enterprise scale.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• 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, while machine learning enhances these tools with predictive and intelligent insights to automate operations decisions.

This instructor-led, live training (online or onsite) is aimed at intermediate-level observability professionals who wish to modernize their monitoring infrastructure by integrating AIOps practices using Prometheus, Grafana, and ML techniques.

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

• Configure Prometheus and Grafana for observability across systems and services.
• Collect, store, and visualize high-quality time series data.
• Apply machine learning models for anomaly detection and forecasting.
• Build intelligent alerting rules based on predictive insights.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• 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 how DevOps teams automate routine tasks like change tracking, test generation, and alert triage by enabling human-like collaboration and decision-making processes.

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

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

• Integrate LLM-based agents into CI/CD workflows to enable intelligent automation.
• Automate processes such as test generation, commit analysis, and change summarization using agents.
• Coordinate multiple agents to triage alerts, generate responses, and provide DevOps recommendations.
• Develop secure and maintainable agent-powered workflows using open-source frameworks.

Course Format

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

Customization Options

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