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We're here to help you find itThe Elastic Certified Observability Engineer course is designed to equip learners with expertise in the Elastic Stack, focusing on how to implement observability with Elasticsearch, Kibana, Beats, and Elastic APM. It covers essential skills for monitoring, searching, and analyzing real-time logs, metrics, and application performance management data to derive actionable insights.
Module 1: Uptime
Lessons cover configuring Beats for Uptime monitoring and creating Uptime app visualizations.
Module 2: Metrics
Lessons focus on collecting, analyzing, and visualizing Infrastructure metrics.
Module 3: Logging
Lessons delve into Log data ingestion, analysis, and visualization.
Module 4: APM
Lessons on configuring Elastic APM agents and servers, and visualizing application performance data.
Module 5: Structuring and Processing Data
Lessons on structuring data for optimal use in the Elastic Stack.
Module 6: Working with Observability Data
Lessons on advanced techniques for Searching and correlating observability data.
Through this course, learners aspiring to become an Elastic Observability Engineer will gain practical skills and knowledge, enabling them to implement and manage a comprehensive observability strategy within their organizations.
Successfully delivered 4 sessions for over 8 professionals
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♱ Excluding VAT/GST
Classroom Training price is on request
You can request classroom training in any city on any date by Requesting More Information
Certainly! Below are the minimum required prerequisites for students interested in undertaking the Elastic Certified Observability Engineer course:
Please note that while prior experience with the Elastic Stack is beneficial, the course is designed to guide students through the necessary concepts and tools to become proficient Elastic Certified Observability Engineers.
The Elastic Certified Observability Engineer course is designed for IT professionals focusing on monitoring, logging, and application performance management (APM).
Target Audience Job Roles:
The Elastic Certified Observability Engineer course equips students with the expertise to monitor systems' uptime, collect metrics, manage logs, utilize APM, and process observability data effectively.
Learning Objectives and Outcomes:
Elasticsearch is a powerful search and analytics engine designed for handling large volumes of data quickly and efficiently. It's part of the Elastic Stack which helps find information, analyze trends over time, and monitor system performance in real time. Given its ability to manage complex data structures and provide insights in milliseconds, Elasticsearch is often used in various applications like e-commerce product searches, logging systems, and data exploration. It works by indexing data in a structured format which makes it searchable in nearly real-time, optimizing performance for both small businesses and large enterprises.
Kibana is a data visualization tool that integrates with Elasticsearch to help users efficiently analyze their data in real-time. It allows you to create customizable dashboards to display information in various formats—from charts to maps—making it easier to discern complex patterns, trends, and insights. Kibana is widely used in diverse fields for monitoring, analyzing, and understanding voluminous data, enabling better decision-making processes. It is particularly effective for use in the field of observability, helping professionals manage and evaluate the performance and health of their systems.
Beats are lightweight data shippers used for single-purpose data collection in the Elastic Stack. They capture different types of data from sources and then send it directly to Elasticsearch or Logstash for indexing. Various types of Beats—such as Filebeat, Metricbeat, and Packetbeat—specialize in gathering specific forms of data like logs, metrics, or network packets, respectively. Beats simplify data processing, making it easier for professionals like Elastic Certified Observability Engineers to monitor, analyze, and visualize data in real-time, enhancing the observability and operational intelligence of systems.
Uptime monitoring is a process used to check if a website or internet service is continuously available and functioning properly over a period. It helps ensure that users can access the service without interruptions. This monitoring records any downtime episodes, allowing IT teams and elastic observability engineers to respond swiftly to resolve any issues and maintain optimal service performance. Regular reports from uptime monitoring can help improve service reliability and user satisfaction by minimizing disruption times and ensuring consistent accessibility. This is crucial for businesses relying on online services to keep operations running smoothly.
Log data ingestion is the process of collecting, importing, and processing log files from various sources into a central system for analysis and monitoring. This involves capturing data generated by applications, servers, or network devices to enable real-time analytics and insights. Effective log data ingestion allows professionals, such as an Elastic Certified Observability Engineer, to better understand system behaviors, diagnose problems, ensure security, and optimize performance, all by analyzing the aggregated data in a structured and efficient manner.
Infrastructure metrics are data points and measurements that help track the performance, health, and efficiency of IT infrastructure components such as servers, network devices, and storage systems. These metrics are crucial for monitoring system availability, optimizing resource utilization, and ensuring that the infrastructure can support the operational needs of the organization. Effective tracking of infrastructure metrics aids in proactive maintenance, preventing downtimes, and enhancing overall service delivery, making it essential for IT management and operational strategies. This plays a role in achieving optimal system performance and user satisfaction.
Searching and correlating observability data involves collecting, analyzing, and linking data from various sources within a system to understand its behavior and performance. This process helps in identifying issues, understanding trends, and making informed decisions to improve system reliability and efficiency. By integrating tools and practices of an elastic certified observability engineer, professionals can efficiently manage the scale and complexity of modern systems, ensuring consistent monitoring and quick problem resolution. This holistic view is crucial for maintaining operational transparency and optimizing performance across all parts of a system.
Data structuring for Elastic Stack involves organizing data in a way that optimizes the performance of the Elastic Stack, a set of tools for searching, analyzing, and visualizing data in real-time. This structuring typically includes defining efficient schemas for data ingestion, indexing patterns that enhance search capabilities, and designing data storage that facilitates easy access and analysis. The goal is to ensure the data is in a format that the Elastic Stack can process effectively, enabling quick retrieval, reliable monitoring, and comprehensive observability of data trends and system health. Proper structuring is crucial for maximizing the potential of Elastic Stack applications.
Elastic Stack is a group of open-source software products designed to help users search, analyze, and visualize data in real-time. It primarily includes Elasticsearch, Logstash, and Kibana. Elasticsearch is a search and analytics engine. Logstash is used for processing incoming data and enriching it before indexing. Kibana lets users visualize data with charts and graphs. This stack efficiently handles large volumes of data, making it ideal for observing and monitoring complex systems, providing insights that support decision-making and operational intelligence. It's widely used in various industries for logging, security, and application performance monitoring.
Elastic APM (Application Performance Monitoring) is a tool designed to monitor software applications in real time. It helps developers understand how their applications are performing and quickly pinpoint where any issues may be occurring. By gathering data on application behavior, response times, and system health, Elastic APM assists in optimizing performance and improving user experience. It's part of the broader Elastic Stack, which provides comprehensive insights into both the technical aspects and the operational health of applications, enhancing overall system observability and troubleshooting capabilities.
The Elastic Certified Observability Engineer course is designed for IT professionals focusing on monitoring, logging, and application performance management (APM).
Target Audience Job Roles:
The Elastic Certified Observability Engineer course equips students with the expertise to monitor systems' uptime, collect metrics, manage logs, utilize APM, and process observability data effectively.
Learning Objectives and Outcomes:
