AIOps Training in Turkey

Utilizing a fully open-source stack for an AIOps pipeline enables teams to develop cost-efficient and adaptable solutions for monitoring, identifying anomalies, and managing intelligent alerts within production environments.

This instructor-led live training (available online or in-person) targets advanced engineers looking to build and deploy a comprehensive AIOps pipeline employing tools such as Prometheus, ELK, Grafana, and custom machine learning models.

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

• Design an AIOps architecture utilizing exclusively open-source components.
• Gather and standardize data originating from logs, metrics, and traces.
• Implement ML models to identify anomalies and forecast incidents.
• Automate alerting and remediation processes using open tooling.

Course Format

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

Customization Options

• For those wishing to request a tailored training session for this course, please reach out to us to arrange details.

Enterprise-grade AIOps platforms such as Splunk, Moogsoft, and Dynatrace offer robust capabilities for identifying anomalies, correlating alerts, and automating responses within 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 current observability stacks and operational workflows.

Upon completing this training, participants will be capable of:

• Configuring and integrating Splunk, Moogsoft, and Dynatrace into a cohesive AIOps architecture.
• Correlating metrics, logs, and events across distributed systems using AI-driven analysis.
• Automating incident detection, prioritization, and response through both built-in and custom workflows.
• Enhancing performance, reducing MTTR, and boosting operational efficiency at an enterprise scale.

Course Format

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

Course Customization Options

• For customized training requests regarding this course, please contact us to make arrangements.

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.

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.

AIOps (Artificial Intelligence for IT Operations) involves leveraging machine learning and analytics to automate and enhance IT operations, with a focus on 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, minimize alert noise, and boost observability through intelligent automation.

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

• Grasp the principles and architecture of AIOps platforms.
• Correlate data from logs, metrics, and traces to identify root causes.
• Decrease alert fatigue by employing intelligent filtering and noise suppression.
• Utilize open-source or commercial tools to monitor and respond to incidents automatically.

Format of the Course

• Interactive lecture and discussion.
• Plenty 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 Turkey (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.

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

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

This instructor-led, live training in Turkey (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.