LLMs and Agents in DevOps Workflows Training Course

Google Antigravity is an agentic development environment designed to build autonomous agents capable of planning, reasoning, coding, and acting through Gemini 3's multimodal capabilities.

This instructor-led, live training (online or onsite) is aimed at advanced-level technical professionals who wish to design, build, and deploy autonomous agents using Gemini 3 and the Antigravity environment.

Upon finishing this training, participants will be prepared to:

• Build autonomous workflows that use Gemini 3 for reasoning, planning, and execution.
• Develop agents in Antigravity that can analyze tasks, write code, and interact with tools.
• Integrate Gemini-driven agents with enterprise systems and APIs.
• Optimize agent behavior, safety, and reliability in complex environments.

Format of the Course

• Expert demonstrations combined with interactive discussions.
• Hands-on experimentation with autonomous agent development.
• Practical implementation using Antigravity, Gemini 3, and supporting cloud tools.

Course Customization Options

• If your team requires domain-specific agent behaviors or custom integrations, please contact us to tailor the program.

Google Antigravity is an advanced framework designed for experimenting with long-lived agents and emergent interactive behaviors.

This instructor-led, live training (available online or on-site) targets advanced-level professionals who aim to design, analyse, and optimise agents capable of retaining memories, improving through feedback, and evolving over extended operational periods.

Upon completing this course, participants will gain the skills to:

• Design long-term memory structures to ensure agent persistence.
• Implement effective feedback loops to shape agent behaviour.
• Evaluate learning trajectories and monitor model drift.
• Integrate memory mechanisms into complex multi-agent ecosystems.

Course Format

• Expert-led discussions complemented by technical demonstrations.
• Hands-on exploration through structured design challenges.
• Practical application of concepts within simulated agent environments.

Course Customisation Options

• If your organisation requires tailored content or case-specific examples, please contact us to customise this training.

This instructor-led, live training in Uzbekistan (online or onsite) is aimed at observability and SRE engineers who want to integrate LLMs and AI into their monitoring, alerting, and incident analysis workflows.

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 practice that applies machine learning and analytics to automate and improve IT operations, particularly in the areas of monitoring, incident detection, and response.

This instructor-led, live training (online or onsite) is aimed at intermediate-level IT operations professionals who wish 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 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 built entirely with open-source tools allows teams to design cost-effective and flexible solutions for observability, anomaly detection, and intelligent alerting in production environments.

This instructor-led, live training (online or onsite) is aimed at advanced-level engineers who wish to build and deploy an end-to-end AIOps pipeline using tools like Prometheus, ELK, Grafana, and custom ML models.

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

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

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customisation Options

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

Antigravity is a development platform designed to build AI-driven, agent-first applications.

This instructor-led, live training (online or onsite) is aimed at intermediate-level developers who wish to create real-world applications using autonomous AI agents within the Antigravity environment.

After completing this training, participants will be equipped to:

• Develop applications that rely on autonomous and coordinated AI agents.
• Use the Antigravity IDE, editor, terminal, and browser for end-to-end development.
• Manage multi-agent workflows with the Agent Manager.
• Integrate agent capabilities into production-grade software systems.

Format of the Course

• Blended presentations with in-depth demonstrations.
• Extensive hands-on practice and guided exercises.
• Real implementation work inside the Antigravity live environment.

Course Customization Options

• For tailored content aligned with your development stack, please contact us to arrange a customized version of this training.

Google Antigravity is an agent-first development environment designed to streamline engineering workflows through intelligent automation.

This instructor-led, live training (online or onsite) is aimed at beginner-level practitioners who wish to explore the fundamentals of Antigravity and understand how agent-driven coding environments enhance productivity.

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

• Install and configure Google Antigravity.
• Navigate and understand both the Editor View and Manager View.
• Work effectively with agents to automate simple development tasks.
• Use Antigravity to generate, refine, and manage project files.

Format of the Course

• Instructor explanations supported by real-time demonstrations.
• Guided exercises focused on hands-on use of agents.
• Practical exploration of core Antigravity features in a controlled lab environment.

Course Customization Options

• If you require a tailored version of this training, please contact us to arrange a customized program.

Google Antigravity serves as a comprehensive platform designed for constructing agents that can effectively interact with web applications, browser environments, and multi-surface workflows.

This instructor-led, live training session—available both online and onsite—is tailored for intermediate-level professionals aiming to build, automate, and test browser-based workflows using Google Antigravity.

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

• Develop agents capable of interacting with web applications through browser interfaces.
• Automate end-to-end workflows across various browser contexts.
• Validate and troubleshoot agent behavior within UI-driven environments.
• Deploy cross-surface automation strategies utilizing Antigravity.

Training Format

• Guided instruction complemented by live demonstrations.
• Practical, hands-on activities and scenario-based exercises.
• Implementation of agent workflows within an interactive lab environment.

Customization Options

• For tailored training needs, please reach out to us to customize the course content to align with your specific goals.

This instructor-led, live training in Uzbekistan (online or onsite) is aimed at SRE and DevOps engineers who want to design, build, and safely deploy AI agents for autonomous IT operations.

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

This instructor-led, live training (available online or on-site) is designed for intermediate-level enterprise IT teams aiming 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, prioritisation, and response using both built-in and custom workflows.
• Optimise performance, reduce MTTR, and enhance operational efficiency at enterprise scale.

Course Format

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

Course Customisation Options

• To request a customised training session 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.

This instructor-led, live training in Uzbekistan (available online or onsite) targets ML engineers and platform teams who need to build robust operational pipelines for LLM-powered applications at scale.

This instructor-led, live training in Uzbekistan (online or onsite) is aimed at security and ML engineers who need to identify, test, and defend against attacks on ML models and LLM-powered applications.