How to Synergize Your Self-managed APM with Alibaba Cloud Elasticsearch

This guide walks you through setting up a self-managed APM server, collecting valuable data, and optimizing your services for peak performance using Elasticsearch's powerful features.

In an era where applications are growing more complex, establishing robust observability platforms is paramount. Alibaba Cloud Elasticsearch provides a solid backbone for synthesizing your monitoring and operational intelligence. This hands-on article will show you how to meld a self-managed Application Performance Monitoring (APM) server with Alibaba Cloud Elasticsearch to sharpen your edge in service observability and application interaction.

Background Information

Observability isn't just about catching anomalies; it paves the way to root-cause analysis across distributed systems. It harmonizes logs, metrics, and APM – the trifecta of observability – facilitating a 360-degree view of your tech stack from development through to maintenance.

APM shines in scenarios such as user experience monitoring, runtime application architecture visualization, in-depth business transactions analysis, and granular component tracking. Beyond real-time insights, APM fosters team productivity and aids in crafting superior end-user experiences.

Prerequisites Before we Dive In

Make sure your Alibaba Cloud Elasticsearch V7.10 cluster is up and running (guide to create one).
Set up an Elastic Compute Service (ECS) instance on Linux (connection instructions).
Install the Go programming language on your ECS instance.

Integrating APM with Alibaba Cloud Elasticsearch

Step 1: Build an APM Server

Connect to your ECS Instance:

# Replace with your connection method here
ssh username@your-ecs-instance-ip

Download and Install the APM Server:

wget https://artifacts.elastic.co/downloads/apm-server/apm-server-7.10.2-linux-x86_64.tar.gz
tar -zxf apm-server-7.10.2-linux-x86_64.tar.gz
cd apm-server-7.10.2-linux-x86_64/

Modify the APM Server Configuration:

apm-server:
  host: "0.0.0.0:8200"
output.elasticsearch:
  hosts: ["es-cn-*****.elasticsearch.aliyuncs.com:9200"]
  username: "elastic"
  password: "your_password"

Start the APM Server:

nohup ./apm-server -e > apmserver.log 2>&1 &

Step 2: Configure an APM Agent in Go

Install APM Agent Packages:

go mod init demo
go get go.elastic.co/apm
go get go.elastic.co/apm/module/apmhttp

Set Environment Variables:

# Open the profile settings
vim ~/.bash_profile

# Add the following
export ELASTIC_APM_SERVICE_NAME=my-apm-service
export ELASTIC_APM_SERVER_URL=http://your-ecs-instance-ip:8200
export ELASTIC_APM_SECRET_TOKEN=mysecrettoken

# Source the profile to apply changes
source ~/.bash_profile

Sample Application for APM:

package main

import (
  "net/http"
  "go.elastic.co/apm/module/apmhttp"
)

func main() {
  mux := http.NewServeMux()
  http.ListenAndServe(":8080", apmhttp.Wrap(mux))
}

Run the application:

go run apm.go

Step 3: Visualization and Analysis on Kibana

Log in to the Kibana console of your Elasticsearch cluster and navigate to Dev Tools. Enable automatic index creation:

PUT _cluster/settings
{
  "persistent": {
    "action.auto_create_index":"+.*,+apm-7.10.2-onboarding-*,-*"
  }
}

Inspect the APM-monitored services and delve into the service data to unravel performance nuances.

Conclusion

Our journey through integrating a self-managed APM server with Alibaba Cloud Elasticsearch is punctuated by the clarity it brings to performance monitoring. It's straightforward, intuitive, and potent in delivering the insights necessary to elevate your application's health and user satisfaction.

Ready to start your journey with Elasticsearch on Alibaba Cloud? Explore our tailored Cloud solutions and services to take the first step towards transforming your data into a visual masterpiece.

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How to Synergize Your Self-managed APM with Alibaba Cloud Elasticsearch

Background Information

Prerequisites Before we Dive In

Integrating APM with Alibaba Cloud Elasticsearch

Step 1: Build an APM Server

Step 2: Configure an APM Agent in Go

Step 3: Visualization and Analysis on Kibana

Conclusion

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