Registration
Register for all three workshops with the following link.
Topic Overview
Log analysis is the process of reviewing, interpreting, and understanding computer-generated records called logs. Logs provide visibility into an application and infrastructure stack's health and performance, enabling development teams and system administrators to diagnose and rectify issues quickly.
Data visualization is the graphical representation of information and data. Using visual elements like charts, graphs, and maps, data visualization tools provide an accessible way to see and understand trends, outliers, and data patterns.
Workshop Overview
In this three-part AWS Logs Visualization with Kibana workshop, the workshop will present you with ways to effectively analyze log data to gain visibility into an application's health and performance, AWS services infrastructure stack via an operational reference architecture and application. The reference architecture and application include networking services, load balancer, database, cache, Docker containers, Lambda functions, etc.
The workshop will provide you a lab kit with step-by-step instructions on how to ingest data from the different layers of an AWS infrastructure, including the application logs and how to visualize and correlate these events with Kibana to obtain a clear picture of one’s AWS infrastructure.
Workshop Objectives
Learn how to ship and analyze logs of applications running on Docker containers, AWS Lambda functions, etc.
How to ship and analyze and infrastructure log from ELB, CloudTrail, VPC, S3, CloudFront access logs, AWS WAF logs, API Gateway Access Logs, Amazon GuardDuty findings, etc.
Stream CloudWatch log events to Elasticsearch
Create Kibana visualizations and dashboards to monitor the state of your AWS infrastructure
Prerequisite
We recommend that attendees have the following prerequisites:
Good working knowledge of the AWS platform and general understanding of audit and access logs.
Familiarity with the Linux operating system and command-line interface.