Centralized Logging and Monitoring with Kubernetes (Udemy.com)

Hands-on guide to logging and monitoring containers at scale

Created by: Packt Publishing

Produced in 2020

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What you will learn

  • Discover what Elasticsearch, Fluentd, and Kibana are (aka the EFK stack)
  • See how to implement a centralized monitoring and logging platform with these technologies
  • Discover what Kubernetes is and how to create a Kubernetes cluster in GCP for modern, containerized applications
  • Deploy applications from Kubernetes to the cloud
  • Scale the number of applications running in Kubernetes
  • Install and configure monitoring and logging agents on the Kubernetes nodes
  • Create powerful visualizations for metrics stored Kibana
  • Effectively and efficiently analyze logs stored in Kibana

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Quality Score

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Overall Score : 74 / 100

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Course Description

Kubernetes is an open source platform designed to automate deployment, scaling, and operation of application containers. Kubernetes automates various aspects of application development, which is extremely beneficial for enterprises. Centralized logging is crucial for any production-grade infrastructure, especially in a containerized architecture. Since Kubernetes is dynamic and does not store change logs except the recent changes, logging and monitoring is highly imperative for saving pod logs.
In this course, you'll learn to analyze and locate critical pod log files in your Kubernetes clusters. You'll create a centralized logging system with a configured EFK (Elasticsearch, Fluentd, and Kibana) stack for Kubernetes. Using a hands-on approach, you'll follow the entire logging and monitoring process, which actually goes hand-in-hand. In your Kubernetes cluster, you'll find out that your clusters are working with too many containers and it's difficult to keep track of each of them.
You'll learn how to build your centralized logging and send data for monitoring. To set up centralized logging, you'll establish one logging agent per Kubernetes node to collect all logs of all running containers from disk and transmit them to Elasticsearch. You'll search for log data, monitor the containers, and also collect metrics using Kibana. You'll decide how your final log data will be presented. By the end of the course, you'll be able to use centralized logging and monitoring techniques for debugging purposes to find out reasons for crashes, and trigger alerts if there is a spike in error messages (which can be more efficient than a system health check).
About the Author
Walter Dolce is a Software and Platform Engineer based in London, United Kingdom. He has worked for both small and medium-sized businesses as well as large enterprises such as the BBC and Just Eat. Over the course of the years, he has developed a deep knowledge of various areas of Software Engineering concepts and practices such as test-driven development, behavior-driven development, SOLID principles, design patterns, and more. He later transitioned to the DevOps/Platform Engineering space where he used that knowledge to implement highly available, resilient systems and platforms running on today's major Cloud providers such as Amazon Web Services, Google Cloud Platform, and Microsoft Azure.Who this course is for:
  • This course is for DevOps engineers, developers, testers, sysadmins, and IT professionals who want to log and monitor containers in their Kubernetes clusters for debugging and other purposes.

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Instructor Details

Packt Publishing

Packt has been committed to developer learning since 2004. A lot has changed in software since then - but Packt has remained responsive to these changes, continuing to look forward at the trends and tools defining the way we work and live. And how to put them to work.
With an extensive library of content - more than 4000 books and video courses -Packt's mission is to help developers stay relevant in a rapidly changing world. From new web frameworks and programming languages, to cutting edge data analytics, and DevOps, Packt takes software professionals in every field to what's important to them now.
From skills that will help you to develop and future proof your career to immediate solutions to every day tech challenges, Packt is a go-to resource to make you a better, smarter developer.

Packt Udemy courses continue this tradition, bringing you comprehensive yet concise video courses straight from the experts.



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Reviews

3.7

7 total reviews

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Was a bit fast, but overall quite good.

it has verify basic information, how to analyse or trouble shoot if fluentd is down or elastic is not reachable what kind of trouble shooting steps we need to run or what is the behaviour of Elastic stack if any of one component is down. what happens to the data if any of one component is not reachable. how does the shards and replicas works in elastic and what is kibana query language like this many topics need to be covered like we might not need to maintain huge data in elastic how do we cleanup and rotate them how does we recover the data in case of file system failure. fluentd is memory based and file-system based what are required tuning parameters to be done at memory level what kind of disks we have to use where does logs stored on a file system etc many questions in mind i cant fill all of them hereBut for absolute beginners, this is a very good course and very help full

I was expecting to see Elasticsearch and Kibana deployed in Kubernetes cluster. However, the course install them in VMs. Only FluentD is configured in the K8s cluster. Moreover, the author did not justified its choice: why not configuring EK in kubernetes? Finally, I missed the good practices of configuring EFK in Kubernetes.Regardless of the issues aforementioned, I think it is a good course for intermediate / advanced students. The course is fast paced, goes straight to the point and help you with FluentD configuration.

The only downside for this course is that the pace is a little bit fast. It seem that the instructor is on the rush to finish fast this course. But i was able to follow anyway the instructor and to understand the general concepts presented in this video (ELK). Now, i know more about ELK (Elasticsearch, Fluentd and Kibana) after watching this video and i will try to apply ELK on our Kubernetes Cluster here at work.

It is an excellent course. However, I feel that there is a possibility to increase the course content.

The only downside for this course is that the pace is a little bit fast. It seem that the instructor is on the rush to finish fast this course. But i was able to follow anyway the instructor and to understand the general concepts presented in this video (ELK). Now, i know more about ELK (Elasticsearch, Fluentd and Kibana) after watching this video and i will try to apply ELK on our Kubernetes Cluster here at work.

It is an excellent course. However, I feel that there is a possibility to increase the course content.