You're reading from AWS for Solutions Architects The definitive guide to AWS Solutions Architecture for migrating to, building, scaling, and succeeding in the cloud

Product type Paperback

Published in Apr 2023

Publisher Packt

ISBN-13 9781803238951

Length 692 pages

Edition 2nd Edition

Tools

AWS

Concepts

Cloud Computing

Authors (4):

Neelanjali Srivastav

Saurabh Shrivastava

Alberto Artasanchez

Imtiaz Sayed

View More author details

Table of Contents (19) Chapters

AWS for Solutions Architects, Second Edition: Design your cloud infrastructure by implementing DevOps, containers, and Amazon Web Services

1 Understanding AWS Principles and Key Characteristics FREE CHAPTER

2 Understanding AWS Well-Architected Framework and Getting Certified

3 Leveraging the Cloud for Digital Transformation

4 Networking in AWS

5 Storage in AWS – Choosing the Right Tool for the Job

6 Harnessing the Power of Cloud Computing

7 Selecting the Right Database Service

8 Best Practices for Application Security, Identity, and Compliance

9 Dive efficiency with Cloud Operation Automation and DevOps in AWS

10 Bigdata and streaming data processing in AWS

11 Datawarehouse, Data Query and Visualization in AWS

12 Machine Learning, IoT, and Blockchain in AWS

13 Containers in AWS

14 Microservice and Event-Driven Architectures

15 Domain-Driven Design

16 Data Lake Patterns – Integrating Your Data across the Enterprise

17 Availability, Reliability, and Scalability Patterns

18 AWS Hands-On Lab and Use Case

Key metrics in a data lake

Now more than ever, digital transformation projects have tight deadlines and are forced to continue doing more with fewer resources. It is vital to demonstrate added value and results quickly. As we will see in later chapters, AWS offers many services to assist in creating an enterprise data lake. However, the tooling needed to measure the success of enterprise data lake implementations is still somewhat lacking.

A successful data lake implementation can serve a corporation well for years. A key to this success and longevity is being able to communicate whether the implementation is adding value or not effectively. However, most metrics for an enterprise data lake are not binary and are more granular than just saying that a project is green or red.

Metrics to gauge the success of your data lake

A list of metrics that can be used to gauge the success of your data lake follows. It is not meant to be a comprehensive list but rather a starting point...