Search icon CANCEL
Subscription
0
Cart icon
Cart
Close icon
You have no products in your basket yet
Save more on your purchases!
Savings automatically calculated. No voucher code required
Arrow left icon
All Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Newsletters
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Modern Data Architecture on AWS

You're reading from  Modern Data Architecture on AWS

Product type Book
Published in Aug 2023
Publisher Packt
ISBN-13 9781801813396
Pages 420 pages
Edition 1st Edition
Languages
Author (1):
Behram Irani Behram Irani
Profile icon Behram Irani
Toc

Table of Contents (24) Chapters close

Preface 1. Part 1: Foundational Data Lake
2. Prologue: The Data and Analytics Journey So Far 3. Chapter 1: Modern Data Architecture on AWS 4. Chapter 2: Scalable Data Lakes 5. Part 2: Purpose-Built Services And Unified Data Access
6. Chapter 3: Batch Data Ingestion 7. Chapter 4: Streaming Data Ingestion 8. Chapter 5: Data Processing 9. Chapter 6: Interactive Analytics 10. Chapter 7: Data Warehousing 11. Chapter 8: Data Sharing 12. Chapter 9: Data Federation 13. Chapter 10: Predictive Analytics 14. Chapter 11: Generative AI 15. Chapter 12: Operational Analytics 16. Chapter 13: Business Intelligence 17. Part 3: Govern, Scale, Optimize And Operationalize
18. Chapter 14: Data Governance 19. Chapter 15: Data Mesh 20. Chapter 16: Performant and Cost-Effective Data Platform 21. Chapter 17: Automate, Operationalize, and Monetize 22. Index 23. Other Books You May Enjoy

Tool-specific performance tuning

We covered a lot about optimizing the service infrastructure in this chapter. However, often, optimizations happen at the service or tool level. This is caused by changing the configurations of the service or fine-tuning the logic that runs on these services. Typically, tuning is done to improve performance, which also helps save costs. It will not be possible to cover every aspect of performance tuning in this section, but we will try to cover some of the obvious ones from some of the key services that help build a data platform on AWS.

Performance tuning measures on Amazon Redshift

Many aspects of performance tuning depend on root cause analysis; hence, we may not be able to cover every tunable in Redshift. Also, recent Redshift autonomics advancements have made a lot of tunable settings automatic now; things such as data distribution, sorting, and analyze and vacuum operations can all be made automatic by the service. However, some common tunable...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at €14.99/month. Cancel anytime}