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We're here to help you find itUnderstanding PromQL Course Overview
The "Understanding PromQL" course is designed to provide a comprehensive exploration of Prometheus Query Language (PromQL), equipping learners with the knowledge to effectively query and analyze time-series data within Prometheus. The course begins with an Introduction to PromQL, outlining its significance and how it integrates with Prometheus. It then dives into the Big Picture of PromQL, discussing its execution, Use Cases, and practical applications.
A Data Model Refresher module revisits the time-series data model and metric types to ensure a strong foundational understanding. Basic Querying covers hands-on querying techniques, including rate calculations, aggregation, and using tools like PromLens. An Interlude delves into language theory, providing insights into PromQL's structure and various expression types.
Advanced Querying techniques are then explored, teaching learners to work with histograms, set operations, and perform more complex tasks like anomaly detection and inspecting scrape health. Overall, the course is tailored to enhance the proficiency of users in leveraging PromQL for monitoring and alerting, thereby improving system observability and reliability.
Successfully delivered 1 sessions for over 15 professionals
Purchase This Course
USD
View Fees Breakdown
Flexi Video | 16,449 |
Official E-coursebook | |
Exam Voucher (optional) | |
Hands-On-Labs2 | 4,159 |
+ GST 18% | 4,259 |
Total Fees (without exam & Labs) |
22,359 (INR) |
Total Fees (with exam & Labs) |
28,359 (INR) |
♱ Excluding VAT/GST
You can request classroom training in any city on any date by Requesting More Information
♱ Excluding VAT/GST
You can request classroom training in any city on any date by Requesting More Information
Understanding PromQL course offers in-depth knowledge of Prometheus Query Language for effective monitoring and alerting in IT systems.
Gain proficiency in PromQL to leverage the full potential of Prometheus for monitoring and alerting. Understand time-series data, complex querying, and anomaly detection to optimize observability.