I recommend this lecture to anyone who wants to gain insight into a hot topic in the DevOps field called Observability, which is based on log analysis and inter-service correlation analysis on microservices.
Log Analysis
OpenTelemetry
Observability
Collect Kubernetes logs
System correlation analysis
Application Performance Monitoring
A must-have for DevOps engineers.
Observability that works in practice!
1️⃣
After changing the system structure to MSA, which is the latest trend, has it become more difficult to identify and resolve the cause of errors ?
2️⃣
Are you curious about how to bring together log analysis and inter-service relationships in microservices?
3️⃣
Do you want to know the theoretical basis and practical implementation method of Observability, one of the latest DevOps trends?
As many companies begin to use Cloud-Native and container technologies, tracking events occurring in distributed systems such as microservices has become important. Observability, which expresses this importance, is also emerging as a hot topic in the Microservice and DevOps fields. However, there are few documents or materials that organize how this concept is formed and how to implement it.
• • •
When changing the system structure based on microservices, an integrated analysis solution is required that can comprehensively analyze issues such as correlation between systems and exceptions that occur.
OpenTelemetry provides a foundation for tracking and analyzing correlations and events between each Microservice according to the flow of Request calls through the concepts of Trace ID and Span ID.
This course will teach you practical ways to apply OpenTelemetry and Log, Trace, and Metrics to your applications based on Java with Spring, Node.js, and Python.
In addition, you will learn how to analyze the correlation between systems using open source-based APM and analyze which part of the system you manage is causing delays.
I am a Digital Nomad IT Engineer who has been working as a Full-stack Developer, DevOps Engineer/Consultant in Korea, Australia, and the UK for about 15 years. I am constantly studying new topics to optimize the operation of IT organizations , and I have a dream of living as an Engineer until I retire. Currently, I am working as a DevOps in the Developer Experience team of a bank in Melbourne, Australia.
Q. You show implementation examples using three languages . What level of understanding of each language is required?
The basic microservice implementation has already been done, and only the part for applying OpenTelemetry requires some programming knowledge. Accordingly, an introductory level of programming is required that can understand the basics of how the code works.
Q. What level of understanding of Kubernetes is required?
You need to have a certain level of understanding of kubectl to be able to execute commands, and since the entire process of creating a Kubernetes Template is explained along the way, there is no problem taking the course even if you have no prior knowledge of Kubernetes.
Q. Do I have to take “ DevOps Essentials ” and “ ProjectSet #1 ” to take this course?
If you take the first two lectures and then this lecture, you will understand the material faster, but you can still take this lecture without taking the first two lectures. If you need to have prior knowledge of the first two lectures, I will give a summary of those and proceed with the lecture.
💾 Things to note before taking the class
The following PC specifications and service versions are required for the training:
Who is this course right for?
For those who are new to log analysis on microservices
Organizations that have difficulty debugging applications on microservices
Anyone who needs basic knowledge of Observability
Need to know before starting?
Kubernetes
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Courses
한국/호주/영국에서 Full-stack developer, DevOps Engineer/Consultant로 15년 정도 일을 하고 있는 Digital Nomad IT Engineer 입니다. IT 조직 운영의 최적화를 위해 끊임 없이 새로운 주제에 대해서 공부를 하고 있으며, 은퇴할 때까지 Engineer로 생활하고 싶다는 꿈을 가지고 있습니다. 현재는 호주 Melbourne에 있는 한 은행의 Developer Experience 팀에서 DevOps로 활동하고 있습니다.
All
14 lectures ∙ (5hr 15min)