Understanding PromQL Course Overview

To ensure a successful learning experience in the Understanding PromQL course, participants should come equipped with the following prerequisites:

• Basic understanding of monitoring and alerting concepts in IT environments.
• Familiarity with the fundamentals of time-series data.
• Experience with using command-line interfaces and basic Linux commands.
• Some exposure to database querying languages (like SQL) is beneficial, though not mandatory.
• Prior knowledge of Prometheus, including its installation and basic configuration, is highly recommended.
• General comprehension of IT infrastructure components such as servers, networking, and applications.
• Willingness to learn and explore new technical concepts related to monitoring and querying metrics.

Please note that while these prerequisites are aimed at ensuring a smooth learning curve, individuals with a strong desire to learn and a commitment to understanding the material can succeed in this course.

Target Audience for Understanding PromQL

Understanding PromQL course offers in-depth knowledge of Prometheus Query Language for effective monitoring and alerting in IT systems.

• DevOps Engineers
• System Administrators
• Site Reliability Engineers (SREs)
• Network Administrators
• Data Analysts focusing on systems and network performance
• Infrastructure Architects
• Software Developers with a focus on DevOps practices
• IT Professionals involved in cloud-native applications
• Monitoring and Observability Engineers
• Technical Operations team members
• Performance Engineers

Learning Objectives - What you will Learn in this Understanding PromQL?

Course Learning Outcomes Introduction

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.

Learning Objectives and Outcomes

• Comprehend PromQL and Its Role in Prometheus: Understand what PromQL is and how it executes within Prometheus to facilitate effective monitoring.
• Master the Time Series Data Model: Get familiar with the structure of time-series data and Prometheus metric types for accurate data representation.
• Execute Basic PromQL Queries: Learn to use the Expression Browser and PromLens to select series, calculate rates, perform aggregation, and basic arithmetic operations.
• Grasp the Underlying Language Theory: Recognize PromQL's nested structure, result and node types, and the importance of query types and evaluation timing.
• Perform Advanced Query Functions: Acquire skills to work with histograms, set operations, and timestamp metrics for in-depth data analysis.
• Implement Anomaly Detection: Learn to compare current data with historical data to detect anomalies and maintain system health.
• Monitor Scrape Health: Gain the ability to inspect scrape intervals and outcomes to ensure reliable data collection.
• Handle Absent Series: Detect and manage issues with absent time-series data, preventing potential gaps in monitoring.
• Aggregate Data Over Time: Understand how to aggregate metrics over various time intervals to observe trends and patterns.
• Construct and Utilize Subqueries: Develop expertise in formulating subqueries for more sophisticated data analysis and visualization.