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Infrastructure Monitoring with Amazon CloudWatch

Infrastructure Monitoring with Amazon CloudWatch

By : Diagboya
5 (8)
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Infrastructure Monitoring with Amazon CloudWatch

Infrastructure Monitoring with Amazon CloudWatch

5 (8)
By: Diagboya

Overview of this book

CloudWatch is Amazon’s monitoring and observability service, designed to help those in the IT industry who are interested in optimizing resource utilization, visualizing operational health, and eventually increasing infrastructure performance. This book helps IT administrators, DevOps engineers, network engineers, and solutions architects to make optimum use of this cloud service for effective infrastructure productivity. You’ll start with a brief introduction to monitoring and Amazon CloudWatch and its core functionalities. Next, you’ll get to grips with CloudWatch features and their usability. Once the book has helped you develop your foundational knowledge of CloudWatch, you’ll be able to build your practical skills in monitoring and alerting various Amazon Web Services, such as EC2, EBS, RDS, ECS, EKS, DynamoDB, AWS Lambda, and ELB, with the help of real-world use cases. As you progress, you'll also learn how to use CloudWatch to detect anomalous behavior, set alarms, visualize logs and metrics, define automated actions, and rapidly troubleshoot issues. Finally, the book will take you through monitoring AWS billing and costs. By the end of this book, you'll be capable of making decisions that enhance your infrastructure performance and maintain it at its peak.
Table of Contents (16 chapters)
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1
Section 1: Introduction to Monitoring and Amazon CloudWatch
5
Section 2: AWS Services and Amazon CloudWatch

Summary

The concept of big data is continually expanding in conjunction with data engineering. We have spent time explaining what big data is and the different aspects of big data, as well as how these aspects intertwine, from the role of a data engineer who helps to sanitize data and make it more friendly and usable by business intelligence experts, to that of data scientists, machine learning engineers, data analysts, and more. Understanding the process of making this data clean is important and monitoring plays a key role in that. We also explained the concept of ETL, which is one of the fundamental concepts of data engineering. Then, we talked about the AWS tools that are used for ETL work: Kinesis for extraction, Glue for transformation, and S3, where the data is stored or loaded.

Lastly, we introduced one important aspect of monitoring in the AWS ecosystem, which is AWS CloudTrail. We then moved on to explain the importance of CloudTrail, how to use the CloudTrail console...

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