DevSecOps with AI: Automating Security in the Pipeline Training Course

AI-driven deployment orchestration leverages machine learning and automation to direct rollout 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 seeking to optimize their deployment pipelines through AI-powered decision-making and enhanced resilience.

Upon completing this training, participants will be able to:

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

Course Format

• Instructor-led demonstrations combined with technical deep dives.
• Hands-on scenarios focusing 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.

AI for DevOps represents the application of artificial intelligence to enhance continuous integration, testing, deployment, and delivery processes through intelligent automation and optimization techniques.

This instructor-led live training (available online or onsite) targets intermediate-level DevOps professionals seeking to incorporate AI and machine learning into their CI/CD pipelines to boost speed, accuracy, and quality.

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

• Integrate AI tools into CI/CD workflows to enable intelligent automation.
• Apply AI-based testing, code analysis, and change impact detection.
• Optimize build and deployment strategies using predictive insights.
• Implement traceability and continuous improvement using AI-enhanced feedback loops.

Format of the Course

• Interactive lecture and discussion.
• 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.

AI-driven rollout control utilizes machine learning, pattern analysis, and adaptive decision-making models to optimize feature flag operations and canary testing workflows.

This instructor-led live training (available online or onsite) targets intermediate engineers and technical leads seeking to enhance release reliability and refine feature exposure decisions through AI-driven insights.

After completing this course, participants will be able to:

• Leverage AI-based decision models to evaluate the risks associated with new feature exposure.
• Automate canary analysis by utilizing performance, behavioral, and operational metrics.
• Incorporate intelligent scoring mechanisms into existing feature flag platforms.
• Develop rollout strategies that dynamically adapt to real-time data insights.

Course Format

• Facilitated discussions enriched with real-world case studies.
• Practical exercises focused on AI-enhanced rollout methodologies.
• Hands-on implementation within a simulated feature flag and canary testing environment.

Customization Options

• For tailored content or integration of your organization's specific tools, please contact us.

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 offers a comprehensive introduction to the concepts, technologies, and practices related to the use of artificial intelligence in IT operations.

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

The training concludes with an exam. Passing it grants the globally recognized AIOps Foundation certification, 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 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 methodology that leverages machine learning and advanced analytics to automate and optimize IT operations, with a specific focus on monitoring, detecting incidents, and responding to them.

This instructor-led live training, available online or onsite, targets intermediate IT operations professionals eager to apply AIOps techniques. Participants will learn to correlate metrics and logs, minimize alert noise, and enhance observability via intelligent automation.

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

• Grasp the core principles and architecture of AIOps platforms.
• Correlate data from logs, metrics, and traces to pinpoint root causes.
• Alleviate alert fatigue through intelligent filtering and noise suppression.
• Utilize both open-source and commercial tools to monitor and automate incident responses.

Course Format

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

Customization Options

• To arrange a customized training session for this course, please get in touch with us.

Developing an AIOps pipeline entirely with open-source technologies enables teams to create flexible, cost-efficient solutions for observability, anomaly detection, and smart alerting within production environments.

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

Upon completing this training, participants will be capable of:

• Designing an AIOps architecture composed exclusively of open-source components.
• Collecting and standardizing data from logs, metrics, and traces.
• Implementing 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 sessions.
• Hands-on implementation in a live laboratory environment.

Customization Options

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

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

This instructor-led live training, available both online and on-site, is designed for advanced-level professionals who aim to apply AI techniques to automatically generate tests and identify areas of 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 detect potential coverage blind spots.
• Integrate AI-based test generation into CI/CD workflows.
• Optimize test strategies based on predictive failure analytics.

Course Format

• Guided technical lectures supplemented 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.

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

This instructor-led live training, available online or onsite, targets intermediate-level QA and DevOps professionals eager 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 managing tests through AI-driven automation platforms.
• Embedding intelligent QA gates into CI/CD pipelines to mitigate regressions.
• Leveraging AI for exploratory testing, predicting defects, and analyzing test flakiness.
• Optimizing testing duration and coverage in fast-paced agile environments.

Course Format

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

Customization Options

• For customized training requests, please contact us to arrange.

AI-driven compliance monitoring is a discipline 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) targets intermediate-level professionals who want to integrate AI-driven compliance controls into their CI/CD pipelines.

Upon completing this training, attendees will be able to:

• Utilize 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.

Course Format

• Instructor-guided presentations supported 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 tailored compliance integrations, please contact us to arrange.

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

This instructor-led training, available online or onsite, is designed for intermediate professionals seeking to automate end-to-end AI model delivery workflows using Docker and CI/CD platforms.

Upon completing the training, participants will be capable of:

• Establishing automated pipelines for constructing and testing AI model containers.
• Enforcing version control and reproducibility throughout model lifecycles.
• Integrating automated deployment strategies for AI services.
• Applying 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

• Should your organization require customized pipeline workflows or platform integrations, please contact us to tailor this course to your needs.

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

This instructor-led training session, available both online and onsite, is tailored for beginner to intermediate-level professionals who want to leverage GitHub Copilot to streamline 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.
• Leverage AI-powered 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.

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

This instructor-led live training (available online or on-site) is designed for intermediate-level enterprise IT teams seeking to integrate AIOps tools into their current observability stacks and operational processes.

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

• Configure and integrate Splunk, Moogsoft, and Dynatrace into a cohesive AIOps architecture.
• Correlate metrics, logs, and events across distributed systems using AI-driven analysis.
• Automate incident detection, prioritization, and response through built-in and custom workflows.
• Enhance performance, reduce MTTR, and improve operational efficiency at an enterprise scale.

Course Format

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

Course Customization Options

• To request 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 the way DevOps teams automate processes like change tracking, test generation, and alert triage by emulating human-like collaboration and decision-making capabilities.

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

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

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

Course Format

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

Customization Options

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