Spring Boot Integration

Overview

Strengths

Use Cases

Concepts

Use Limits

Features

Service Regions

Product Introduction

Billing Overview

Pay-as-You-Go Description

Billing Rules for Free Metrics Exceeding Free Storage Period

Pay-as-You-Go (Postpaid)

Free Trial Introduction

Managed Collector Billing Introduction

Purchase Methods

Payment Overdue

Free Metrics in Pay-as-You-Go Mode

Pay-as-You-Go — Unit Price for One-Year/Two-Year Data Storage

Purchase Guide

Getting Started

Scrape Configuration Description

Custom Monitoring

EMR Metric Collection Component of Prometheus

EMR Integration

JVM Integration

Java Application Integration

Go Application Integration

Elasticsearch Exporter Integration

Kafka Exporter Integration

MongoDB Exporter Integration

PostgreSQL Exporter Integration

Nginx Exporter Integration

Redis Exporter Integration

MySQL Exporter Integration

Consul Exporter Integration

Memcached Exporter Integration

Integration with Other Exporters

CVM Node Exporter

Apache Exporter Integration

Exporter Integration

Health Check

Instructions for Installing Components in the TKE Cluster

Cloud Monitoring

Read Cloud-Hosted Prometheus Instance Data via Remote Read

Agent Self-Service Access

Pushgateway Integration

Security Group Open Description

Integration Guide

Creating Instance

Searching for Instance

Renaming Instance

Terminating Instance

Rebooting Instance

Modifying Storage Period

Viewing Instance's Basic Information

Instance

Integration with TKE

Integration Center

Data Multi-Write

Rule Management

List of Default Recording Rules

Recording Rule

Alerting Rule Description

Creating Alerting Rule

Disabling Alerting Rule

Rule Type Description(old)

Notification Template

Alarm Suppression

Alerting Rule

Examples

Using Tag

Editing Tag

Setting Policy

Granting Policy

Description of Role Permissions Related to Service Authorization

Access Control

Grafana

Writing Data

Querying Monitoring Data

API Guide

Instance Diagnosis

Recommended Common Metrics for TKE

Container Monitoring Chart Metrics

Data Collection Configuration

Configuring Necessary Monitoring Metrics

Adjusting Collection IntervalAdjusting Collection Interval

TKE Metrics

Resource Usage and Billing Overview

Operation Guide

Migration from Self-Built Prometheus

Custom Integration with CVM

TKE Monitoring

Enabling Public Network Access for TKE Serverless Cluster

Connecting TMP to Local Grafana

Enabling Public Network Access for Prometheus Instances

Configuring a Public Network Address for a Prometheus Instance

Practical Tutorial

Terraform Overview

Managing Prometheus Instances Using Terraform

Managing the Integration Center of Prometheus Instances Using Terraform

Collecting Container Monitoring Data Using Terraform

Configuring Alarm Policies Using Terraform

Terraform

Basic Questions

Integration with TKE Cluster

Product Consulting

Use and Technology

FAQs

Service Level Agreement

Privacy Policy

Data Processing And Security Agreement

TMP Policy

TencentCloud Managed Service for Prometheus

When using Spring Boot as the development framework, you need to monitor the status of applications such as JVM and Spring MVC. TMP collects data such as JVM data based on the Spring Boot Actuator mechanism. With the Grafana dashboard that comes with TMP, you can conveniently monitor the status of Spring Boot applications.

This document uses deploying a Spring Boot application in TKE as an example to describe how to use TMP to monitor the application status.

https://intl.cloud.tencent.com/document/product/457/30637

Use a private image repository to manage application images

https://intl.cloud.tencent.com/document/product/457/9117

The image is developed based on the Spring Boot framework.

Spring Boot provides the Actuator component to monitor applications, which reduces the development costs. Therefore, Actuator is directly used in this document to track Spring Boot metrics. You should use Spring Boot v2.0 or above in the following steps, as lower versions may have different configurations.


If you use Spring Boot v1.5 for integration, the integration process will differ from that for v2.0, and you should note the following:

 is different from that for v2.0. On v1.5, the default address is 

If error 401 is reported, it indicates no permissions (Whitelabel Error Page). On v1.5, security control is enabled for the 

 is used to configure parameters in the project, modifying 

 in it will not work, which should be modified in 

 due to the Spring Boot start and load sequence.

 through YML; instead, you can add it only by adding a 

Modifying application dependencies and configuration

 is already imported in this project, add the 

  <groupId>org.springframework.boot</groupId>

  <artifactId>spring-boot-starter-actuator</artifactId>

  <artifactId>micrometer-registry-prometheus</artifactId>

 configuration to expose the metric data in the Prometheus protocol.

        include: prometheus  # Web access path for opening Prometheus

    # We recommend you enable the following options to monitor P99 and P95 latencies of HTTP requests. You can set the specific time distribution based on the actual conditions

            requests: 1ms,5ms,10ms,50ms,100ms,200ms,500ms,1s,5s

      # You must add the corresponding application name, as the corresponding monitoring information needs to be viewed by application

In the current directory of the project, run 

. If you can access the metric data of the Prometheus protocol through 

http://localhost:8080/actuator/prometheus

, the relevant dependency configuration is correct.

The default configurations of the port and path are used in the same, which should be replaced with those in your actual project.

Step 1. Configure a Docker image environment locally

If you have already configured a Docker image environment locally, proceed to the next step; otherwise, configure one as instructed in 

 in the root directory of the project. You can add it by referring to the following sample code and modify 

ADD target/spring-boot-demo-*.jar /spring-boot-demo/spring-boot-demo.jar

CMD ["java","-jar","spring-boot-demo.jar"]

Package the image by running the following command in the project root directory. You need to replace 

docker build . -t ccr.ccs.tencentyun.com/[namespace]/[ImageName]:[image tag]

docker push ccr.ccs.tencentyun.com/[namespace]/[ImageName]:[image tag]

docker build . -t ccr.ccs.tencentyun.com/prom_spring_demo/spring-boot-demo:latest

docker push ccr.ccs.tencentyun.com/prom_spring_demo/spring-boot-demo:latest

https://console.tencentcloud.com/tke2/cluster?rid=1

 and select the container cluster for deployment.

 to enter the Deployment management page and select the corresponding namespace to deploy the service. Here, a workload is created in the console, and Service access is also enabled. You can also create one on the command line.


Add K8s labels to the corresponding Service. If the workload is created on the command line, you can directly add labels. Here, the configuration is adjusted in the TKE console. Select the TKE cluster that needs to be adjusted.
Click 

 to enter the Service management page. Select the corresponding namespace to adjust the Service YAML configuration as shown below:


  labels: # Add the corresponding labels based on the actual conditions

  - name: 8080-8080-tcp  # Corresponding `port` value in the ServiceMonitor scrape task

https://console.tencentcloud.com/monitor/prometheus

 and select the target TMP instance to enter the management page.

, add a ServiceMonitor. Currently, TMP supports discovering the corresponding target instance address through labels; therefore, you can add some specific K8s labels to some services, which will be automatically identified by TMP after configuration, eliminating your need to add scrape tasks for all services one by one. The configuration information for the above sample is as follows:

 value in the Service YAML configuration file.

    name: spring-mvc-demo # Enter a unique name

    namespace: cm-prometheus # The namespace is fixed. Do not change it

      port: 8080-8080-tcp # Enter the name of the corresponding port of the Prometheus exporter in the Service YAML configuration file

      path: /actuator/prometheus  # Enter the value of the corresponding path of the Prometheus exporter. If it is not specified, it will be `/metrics` by default

    namespaceSelector:  # Select the namespace where the Service to be monitored resides

    selector: # Enter the label value of the Service to be monitored to locate the target Service

Access the Grafana address of your TMP instance to view the application monitoring dashboard in 

Spring MVC application: monitoring data of MVC status, such as the request latency, number of requests, success rate, and exception distribution.

Spring MVC API: API-level monitoring data, which supports multiple APIs to help you locate faulty APIs.

Tomcat: monitoring dashboard of internal Tomcat status, such as thread usage.

Application JVM: monitoring data of the status of all instances under an application. If you find a faulty instance, you can view its monitoring information at any time.

Instance JVM: detailed monitoring data of a single instance JVM.

tencent cloud