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Community Blog Solutions and Tools for Docker Container Monitoring

Solutions and Tools for Docker Container Monitoring

In this tutorial, you will learn to deploy docker container cluster on cloud server to monitor and manage you application.

Orchestrating and managing containerized application environments with virtual management tools, such as Kubernetes and Docker Swarm, allows developers to manage and monitor enterprise production and development environments made up of multiple of containerized applications that have been built directly into the Alibaba Cloud Container Service.

In this tutorial, we will show you how to build a Kubernetes application environment which runs on Alibaba Cloud's Container Service for Kubernetes. Alibaba Cloud's Container Service for Kubernetes is made up of a Virtual Private Cloud (VPC) containing clusters of Alibaba Cloud Elastic Compute Service (ECS) instances on which Kubernetes orchestrates and manages industry scale containerized environments.

Before you can run Kubernetes containerized application environments on Alibaba Cloud's Container Service for Kubernetes, you need an Alibaba Cloud Container Service Kubernetes cluster.

What Is Alibaba Cloud's Container Service?

Alibaba Cloud's Container Service is a scalable and reliable, high-performance, container management service that allows you to orchestrate and manage containerized application lifecycles with either Kubernetes or Docker Swarm.

Alibaba Cloud's Container Service offers multiple application release methods, including continuous integration, and it also supports a microservices architecture. Container Service for Kubernetes provides enterprise-level performance and flexibility for the management of Kubernetes containerized applications at every stage of the development lifecycle.

Alibaba Cloud's Container Service for Kubernetes simplifies cluster creation, management, and allows for easy upscale too. It also auto-integrates with Alibaba Cloud's virtualization, storage, network, and security services which improve and simplify the overall running environment for Kubernetes containerized applications.

Alibaba Cloud's Container Service is one of the first cloud container services to have passed the Certified Kubernetes Conformance Program.

You can refer to Create a Containerized App on Alibaba Cloud Container Service for Kubernetes to learn more about What Is Kubernetes (K8s)?

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Monitor GPU Metrics of a Container Service Kubernetes Cluster

This article describes how to rapidly construct a GPU monitoring solution based on Prometheus and Grafana on Alibaba Cloud Container Service for Kubernetes.

Whenever you are training artificial intelligence (AI) models using an Alibaba Cloud Container Service for Kubernetes cluster constructed based on GPU ECS hosts, you need to know the GPU status of each pod. For example, you may need to know the video memory usage, GPU usage, and GPU temperature to ensure the stability of services. This document describes how to rapidly construct a GPU monitoring solution based on Prometheus and Grafana on Alibaba Cloud.

What Is Prometheus?
Prometheus is an open-source service monitoring system and a time series database. Since its inception in 2012 and open source placement on GitHub in 2015, Prometheus has attracted many companies and organizations. Prometheus joined the Cloud Native Computing Foundation (CNCF) in 2016 as the second hosted project, after Kubernetes. It graduated from the CNCF in August, 2018.

As a next-generation open-source solution, Prometheus has a lot of O&M ideas that happen to coincide with those of Google SRE.

Set Up Container Service for Kubernetes
Prerequisites: You have created a Kubernetes cluster consisting of GPU ECS hosts through Container Service.

Log on to the Container Service console and select Container Service - Kubernetes. Choose Application > Deployment and click Create by Template.

Select your GPU cluster and namespace. (For example, you can select the kube-system namespace.) Fill the YAML configuration template to deploy Prometheus and GPU-Exporter.

Technical Best Practices for Container Log Processing

This article describes some common methods and best practices for container log processing by taking Docker as an example.

Background

Docker, Inc. (formerly known as dotCloud, Inc) released Docker as an open source project in 2013. Then, container products represented by Docker quickly became popular around the world due to multiple features, such as their good isolation performance, high portability, low resource consumption, and rapid startup. The following figure shows the search trends for Docker and OpenStack starting from 2013.

The container technology brings about many conveniences, such as application deployment and delivery. It also brings about many challenges for log processing, such as:

  1. If you store logs inside containers, logs are gone when containers are removed. The lifecycle of containers is much shorter than that of virtual machines, because containers are frequently created and removed. Therefore, you need to find a way to store logs persistently.
  2. After entering the container era, you have more objects to manage than virtual machines and physical machines. Troubleshooting problems by logging on to the target containers will complicate the problems and increase the cost.
  3. The container technology allows you to implement microservices easier. It brings about more components when it decouples the system. You need a technology to help you comprehensively understand the running status of the system, quickly locate the problem, and accurately restore the context.

Log Processing

This article describes some common methods and best practices for container log processing by taking Docker as an example. Concluded by the Alibaba Cloud Log Service team through hard work in the log processing field for many years, these methods and practices are:

  1. Real-time collection of container logs
  2. Query analysis and visualization
  3. Context analysis of logs
  4. LiveTail - tail-f on the cloud

Real-time Collection of Container Logs

Container Log Types

To collect logs, you must first figure out where the logs are stored. This article shows you how to collect NGINX and Tomcat container logs.

Log files generated by NGINX are access.log and error.log. NGINX Dockerfile respectively redirect access.log and error.log to STDOUT and STDERR.

Tomcat generates multiple log files, including catalina.log, access.log, manager.log, and host-manager.log. tomcat Dockerfile does not redirect these logs to the standard output. Instead, they are stored inside the containers.

Cloud Monitor Log Generation from Sample Application

In this tutorial, we will see how Cloud Monitor can help us notified in case of an exception in an application.

Overview

Alibaba Cloud Monitor service allows monitoring of cloud resource usage and health of the application/resources by collecting various monitoring metrics. In this tutorial, we will see how Cloud Monitor can help us notified in case of an exception in an application. Sample application, which is used here to demonstrate the cloud monitor use case, is a simple web application for uploading file into OSS bucket.

This application will write error logs into Alibaba Log Service and logs are being pulled into Cloud Monitor to monitor sample application exceptions.

There are few more use cases possible using the same idea.

  1. Measure throughput or performance of the application from log entry timings.
  2. Use Cloud Monitor Dashboard to monitor application health in real time

Architecture

In this below design, I have implemented a scenario where system administrator is notified by email if there is any failure while using file upload web application. The failure could be loss of connection between OSS and application or any other OSS technical/permission issue.

File upload web application is designed to write the error log message into "Log Service". Cloud Monitor monitors the log message written into Log Service. If Log Monitor identified number of error log exceeds the threshold count, then it will automatically send email alert to the system administrator stating that web application encountered an error.

Prerequisite

This tutorial can easily be understood and followed if you are familiar with the below technologies and concepts,

  1. Alibaba Cloud Environment
    If you do not have access, get 1 year free access with $10 credit using the below link
  2. Alibaba Cloud Free Account
    Alibaba Log Service

Click here to know basics of Cloud Message service

  1. Alibaba Cloud Monitor
    Click here to know about Batch Compute product

Python Programing Knowledge and Flask Web Framework

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This course is designed to help IT companies that want to containerize business applications, as well as cloud computing engineers and operations & maintenance engineers who want to understand and learn how to diagnose problems and monitor the containerized application. By learning this course, you can fully understand what the problem diagnosis of containerized applications is, the common problems of containerized applications, the basic workflow of diagnosing problems, the monitoring scheme and common tools of containerized applications, and the visual monitoring scheme based on Alibaba Cloud Container Service.

Alibaba Cloud Monitoring & Management

This course helps you quickly master Alibaba Cloud Monitoring & Management related services, so that you can efficiently and quickly manage resources on the Alibaba Cloud. This course mainly explains the functions and basic usage of two services:Alibaba Cloud ActionTrail and Cloud Monitor, and impresses you by demonstrating the operation.

Performance Testing and Optimizing of Containerized Applications

This course is designed to help IT companies who want to containerize business applications, as well as cloud computing engineers and operations & maintenance engineers who want to understand and learn about performance testing and optimizing of containerized applications. By learning this course, you can fully understand what the performance testing and optimizing are, the main object of performance testing and optimizing, the common methods, basic procedures, and common tools of performance testing and optimizing for containerized applications, and how to realize performance testing based on Alibaba Cloud Container Service.

Related Documentation

Monitor resources - Container Service for Kubernetes

Resource monitoring is the most common monitoring operation in Container Service for Kubernetes. You can conveniently monitor the usage of resources such as CPU, memory, and network. Container Service has integrated CloudMonitor for resource monitoring. By default, CloudMonitor is installed and integrated for all newly created clusters.

Procedure

  1. Log on to the Container Service console.
  2. In the left-side navigation pane under Container Service - Kubernetes, choose Applications > Deployments. The Deployments page appears.
  3. Find the required deployment and click Monitor in the Actions column. Alternatively, click Monitor for the deployment in the Kubernetes dashboard.

Monitor events - Container Service for Kubernetes

Event monitoring is another monitoring method in Kubernetes. It makes up for the disadvantages of resource monitoring in timeliness, accuracy, and scenarios. The core design concept of Kubernetes is state machine. The transitions between different states generate corresponding events. Specifically, there will be Normal events when the state machine changes to a desired state and Warning events when the state machine changes to an unexpected state. Developers can obtain events to diagnose cluster exceptions and problems in real time.

Background information

Maintained by Alibaba Cloud Container Service, kube-eventer is an open-source event emitter that sends Kubernetes events to systems such as DingTalk and Log Service. It also provides filter conditions of different levels to realize real-time event collection, targeted alerting, and asynchronous archiving. For more information, see kube-eventer.

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