Description: Want to run your Kubernetes workloads safely and securely? This practical book provides a threat-based guide to Kubernetes security. Each chapter examines a particular component's architecture and potential default settings and then reviews existing high-profile attacks and historical Common Vulnerabilities and Exposures (CVEs). Authors Andrew Martin and Michael Hausenblas share best-practice configuration to help you harden clusters from possible angles of attack.This book begins with a vanilla Kubernetes installation with built-in defaults. You'll examine an abstract threat model of a distributed system running arbitrary workloads, and then progress to a detailed assessment of each component of a secure Kubernetes system.Understand where your Kubernetes system is vulnerable with threat modelling techniques Focus on pods, from configurations to attacks and defenses Secure your cluster and workload traffic Define and enforce policy with RBAC, OPA, and Kyverno Dive deep into sandboxing and isolation techniques Learn how to detect and mitigate supply chain attacks Explore filesystems, volumes, and sensitive information at rest Discover what can go wrong when running multitenant workloads in a cluster Learn what you can do if someone breaks in despite you having controls in place
Price: 51.17 USD
Location: East Hanover, New Jersey
End Time: 2024-12-03T15:54:00.000Z
Shipping Cost: 0 USD
Product Images
Item Specifics
Return shipping will be paid by: Buyer
All returns accepted: Returns Accepted
Item must be returned within: 60 Days
Refund will be given as: Money Back
Return policy details:
EAN: 9781492081739
UPC: 9781492081739
ISBN: 9781492081739
MPN: N/A
Book Title: Hacking Kubernetes: Threat-Driven Analysis and Def
Number of Pages: 311 Pages
Publication Name: Hacking Kubernetes : Threat-Driven Analysis and Defense
Language: English
Publisher: O'reilly Media, Incorporated
Subject: Cloud Computing, Security / General, Programming / Open Source, General
Publication Year: 2021
Item Height: 0.9 in
Type: Textbook
Item Weight: 19.1 Oz
Author: Andrew Martin, Michael Hausenblas
Subject Area: Mathematics, Computers
Item Length: 9.1 in
Item Width: 7.3 in
Format: Trade Paperback
