Master Elastic Observability: Build a Full‑Stack Monitoring Platform in Half a Day
This workshop guides participants from installing a single‑node Elastic Stack to deploying a cloud‑native observability platform for a multi‑tier pet‑store application, covering health checks, metrics, logs, APM tracing, SLO/SLI setup, and custom dashboards across local, AWS, and Tencent Cloud environments.
Introduction
Elastic Observability is a one‑stop solution built on the Elastic Stack that provides logging, metrics, APM, and uptime monitoring for large‑scale cloud‑native environments, enabling Service Level Objective (SLO) management. The workshop uses a multi‑layer pet‑store demo application to demonstrate end‑to‑end observability setup.
Learning Objectives
Deploy a single‑node Elasticsearch service and configure Kibana.
Understand core observability concepts and implementation steps.
Set up service health‑check probes with Heartbeat.
Collect operating‑system performance metrics using Metricbeat.
Configure OS log collection and analysis with Filebeat.
Deploy backend services for APM tracing.
Run the multi‑tier pet‑store app and instrument each service with APM.
Configure a unified service‑quality monitoring dashboard.
Demo Application Overview
Multi‑tier pet‑store application.
All components run on a single virtual machine.
Includes front‑end, back‑end, and an embedded database.
Technologies: JavaScript, Node.js, Java Spring.
Elastic Stack Details
Version 7.9.3.
Components: Elasticsearch, Kibana, APM, Filebeat, Metricbeat, Heartbeat.
Experiment Environments
Local virtual machine with pre‑packaged software and demo app.
AWS China regions: Beijing AMI ami-0e1382088b62cb38d, Ningxia AMI ami-0e5a0e294902966af.
Tencent Cloud using managed Elasticsearch service (VM to be released on Cloud Marketplace).
Alibaba Cloud (in development).
Four‑Step Observability Construction
STEP0 – Use Heartbeat for lightweight service health checks.
STEP1 – Use Metricbeat for comprehensive metric collection.
STEP2 – Use Filebeat for high‑dimensional log collection.
STEP3 – Use APM for full‑stack distributed tracing.
These steps create a unified operations platform that supports continuous SRE‑driven monitoring. By selecting immediate SLI collection points from Elastic Stack data, teams can iteratively refine alerts and provide feedback to developers.
Custom SLO Dashboard
Canvas is used to build a visual SLO monitoring screen showing real‑time service health, latency, error rates, and resource usage.
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