Atjaunināt sīkdatņu piekrišanu

E-grāmata: Managing Cloud Native Data on Kubernetes: Architecting Cloud Native Data Services Using Open Source Technology

3.33/5 (6 ratings by Goodreads)
,
  • Formāts: 332 pages
  • Izdošanas datums: 02-Dec-2022
  • Izdevniecība: O'Reilly Media
  • Valoda: eng
  • ISBN-13: 9781098111342
Citas grāmatas par šo tēmu:
  • Formāts - EPUB+DRM
  • Cena: 54,09 €*
  • * ši ir gala cena, t.i., netiek piemērotas nekādas papildus atlaides
  • Ielikt grozā
  • Pievienot vēlmju sarakstam
  • Šī e-grāmata paredzēta tikai personīgai lietošanai. E-grāmatas nav iespējams atgriezt un nauda par iegādātajām e-grāmatām netiek atmaksāta.
Managing Cloud Native Data on Kubernetes: Architecting Cloud Native Data Services Using Open Source TechnologyPalielināt
  • Formāts: 332 pages
  • Izdošanas datums: 02-Dec-2022
  • Izdevniecība: O'Reilly Media
  • Valoda: eng
  • ISBN-13: 9781098111342
Citas grāmatas par šo tēmu:

DRM restrictions

  • Kopēšana (kopēt/ievietot):

    nav atļauts

  • Drukāšana:

    nav atļauts

  • Lietošana:

    Digitālo tiesību pārvaldība (Digital Rights Management (DRM))
    Izdevējs ir piegādājis šo grāmatu šifrētā veidā, kas nozīmē, ka jums ir jāinstalē bezmaksas programmatūra, lai to atbloķētu un lasītu. Lai lasītu šo e-grāmatu, jums ir jāizveido Adobe ID. Vairāk informācijas šeit. E-grāmatu var lasīt un lejupielādēt līdz 6 ierīcēm (vienam lietotājam ar vienu un to pašu Adobe ID).

    Nepieciešamā programmatūra
    Lai lasītu šo e-grāmatu mobilajā ierīcē (tālrunī vai planšetdatorā), jums būs jāinstalē šī bezmaksas lietotne: PocketBook Reader (iOS / Android)

    Lai lejupielādētu un lasītu šo e-grāmatu datorā vai Mac datorā, jums ir nepieciešamid Adobe Digital Editions (šī ir bezmaksas lietotne, kas īpaši izstrādāta e-grāmatām. Tā nav tas pats, kas Adobe Reader, kas, iespējams, jau ir jūsu datorā.)

    Jūs nevarat lasīt šo e-grāmatu, izmantojot Amazon Kindle.

Kubernetes has become the primary platform for deploying and managing cloud native applications. But because it was originally designed for stateless workloads, working with data on Kubernetes has been challenging. If you want to avoid the inefficiencies and duplicative costs of having separate infrastructure for applications and data, this practical guide can help.

Using Kubernetes as your platform, you'll discover open source technologies that are designed and built for the cloud. Delve into case studies to avoid the pitfalls others have faced and explore new use cases. Get an insider's view of what's coming from the innovators who are creating next-generation architectures and infrastructure. And you'll learn how to:

  • Manage different data use cases on Kubernetes
  • Reduce costs and simplify application development
  • Leverage data and infrastructure to create new use cases and business models
  • Make data infrastructure choices that are cost-efficient, secure, scalable, and elastic
  • And more

Foreword xi
Preface xv
1 Introduction to Cloud Native Data Infrastructure: Persistence, Streaming, and Batch Analytics
1(18)
Infrastructure Types
2(2)
What Is Cloud Native Data?
4(2)
More Infrastructure, More Problems
6(1)
Kubernetes Leading the Way
7(3)
Managing Compute on Kubernetes
8(1)
Managing Network on Kubernetes
9(1)
Managing Storage on Kubernetes
9(1)
Cloud Native Data Components
10(1)
Looking Forward
11(1)
Getting Ready for the Revolution
12(5)
Adopt an SRE Mindset
12(2)
Embrace Distributed Computing
14(1)
Principles of Cloud Native Data Infrastructure
14(3)
Summary
17(2)
2 Managing Data Storage on Kubernetes
19(32)
Docker, Containers, and State
19(7)
Managing State in Docker
21(1)
Bind Mounts
21(1)
Volumes
22(1)
Tmpfs Mounts
23(1)
Volume Drivers
24(2)
Kubernetes Resources for Data Storage
26(16)
Pods and Volumes
26(7)
PersistentVolumes
33(4)
PersistentVolumeClaims
37(2)
StorageClasses
39(3)
Kubernetes Storage Architecture
42(7)
Flexvolume
42(1)
Container Storage Interface
43(2)
Container Attached Storage
45(2)
Container Object Storage Interface
47(2)
Summary
49(2)
3 Databases on Kubernetes the Hard Way
51(30)
The Hard Way
52(1)
Prerequisites for Running Data Infrastructure on Kubernetes
53(1)
Running MySQL on Kubernetes
53(12)
ReplicaSets
54(2)
Deployments
56(4)
Services
60(3)
Accessing MySQL
63(2)
Running Apache Cassandra on Kubernetes
65(15)
Stateful Sets
67(11)
Accessing Cassandra
78(2)
Summary
80(1)
4 Automating Database Deployment on Kubernetes with Helm
81(22)
Deploying Applications with Helm Charts
82(1)
Using Helm to Deploy MySQL
83(11)
How Helm Works
87(2)
Labels
89(1)
ServiceAccounts
90(1)
Secrets
90(1)
ConfigMaps
91(2)
Updating Helm Charts
93(1)
Uninstalling Helm Charts
94(1)
Using Helm to Deploy Apache Cassandra
94(5)
Affinity and Anti-Affinity
96(3)
Helm, CI/CD, and Operations
99(3)
Summary
102(1)
5 Automating Database Management on Kubernetes with Operators
103(32)
Extending the Kubernetes Control Plane
104(3)
Extending Kubernetes Clients
105(1)
Extending Kubernetes Control Plane Components
105(1)
Extending Kubernetes Worker Node Components
106(1)
The Operator Pattern
107(7)
Controllers
107(3)
Custom Resources
110(2)
Operators
112(2)
Managing MySQL in Kubernetes Using the Vitess Operator
114(13)
Vitess Overview
114(3)
PlanetScale Vitess Operator
117(10)
A Growing Ecosystem of Operators
127(6)
Choosing Operators
127(3)
Building Operators
130(3)
Summary
133(2)
6 Integrating Data Infrastructure in a Kubernetes Stack
135(32)
K8ssandra: Production-Ready Cassandra on Kubernetes
135(8)
K8ssandra Architecture
136(1)
Installing the K8ssandra Operator
137(4)
Creating a K8ssandraCluster
141(2)
Managing Cassandra in Kubernetes with Cass Operator
143(4)
Enabling Developer Productivity with Stargate APIs
147(3)
Unified Monitoring Infrastructure with Prometheus and Grafana
150(4)
Performing Repairs with Cassandra Reaper
154(2)
Backing Up and Restoring Data with Cassandra Medusa
156(3)
Creating a Backup
157(1)
Restoring from Backup
158(1)
Deploying Multicluster Applications in Kubernetes
159(6)
Summary
165(2)
7 The Kubernetes Native Database
167(28)
Why a Kubernetes Native Approach Is Needed
167(2)
Hybrid Data Access at Scale with TiDB
169(13)
TiDB Architecture
170(3)
Deploying TiDB in Kubernetes
173(9)
Serverless Cassandra with DataStax Astra DB
182(7)
What to Look for in a Kubernetes Native Database
189(5)
Basic Requirements
189(2)
The Future of Kubernetes Native
191(3)
Summary
194(1)
8 Streaming Data on Kubernetes
195(24)
Introduction to Streaming
195(4)
Types of Delivery
196(1)
Delivery Guarantees
197(1)
Feature Scope
198(1)
The Role of Streaming in Kubernetes
199(3)
Streaming on Kubernetes with Apache Pulsar
202(10)
Preparing Your Environment
205(2)
Securing Communications by Default with cert-manager
207(4)
Using Helm to Deploy Apache Pulsar
211(1)
Stream Analytics with Apache Flink
212(5)
Deploying Apache Flink on Kubernetes
214(3)
Summary
217(2)
9 Data Analytics on Kubernetes
219(28)
Introduction to Analytics
220(1)
Deploying Analytic Workloads in Kubernetes
221(3)
Introduction to Apache Spark
224(2)
Deploying Apache Spark in Kubernetes
226(4)
Build Your Custom Container
228(1)
Submit and Run Your Application
228(2)
Kubernetes Operator for Apache Spark
230(3)
Alternative Schedulers for Kubernetes
233(7)
Apache YuniKorn
235(2)
Volcano
237(3)
Analytic Engines for Kubernetes
240(6)
Dask
242(2)
Ray
244(2)
Summary
246(1)
10 Machine Learning and Other Emerging Use Cases
247(22)
The Cloud Native AI/ML Stack
248(13)
AI/ML Definitions
248(2)
Defining an AI/ML Stack
250(2)
Real-Time Model Serving with KServe
252(3)
Full Lifecycle Feature Management with Feast
255(3)
Vector Similarity Search with Milvus
258(3)
Efficient Data Movement with Apache Arrow
261(3)
Versioned Object Storage with lakeFS
264(4)
Summary
268(1)
11 Migrating Data Workloads to Kubernetes
269(24)
The Vision: Application-Aware Platforms
269(2)
Charting Your Path to Success
271(17)
People
272(4)
Technology
276(7)
Process
283(5)
The Future of Cloud Native Data
288(4)
Summary
292(1)
Index 293
Jeff has worked as a software engineer and architect in multiple industries and as a developer advocate helping engineers succeed with Apache Cassandra. He's involved in multiple open source projects in the Cassandra and Kubernetes ecosystems including Stargate and K8ssandra. Jeff is coauthor of the O'Reilly books Cassandra: The Definitive Guide and Managing Cloud Native Data on Kubernetes. Patrick McFadin has been a distributed systems hacker since he first plugged a modem into his Atari computer. Looking for adventure, he joined the US Navy, working on the Naval Tactical Data System (NTDS), which cemented his love of distributed systems. He then spent the 1990s working on infrastructure as the internet started to take off and barely survived the ensuing dot-com crash. Along the way, Patrick picked up a Computer Engineering degree from Cal Poly, San Luis Obispo, and has been focusing on high-scale internet infrastructure ever since. His latest obsession is distributed data systems, and he has been a steady contributor to the Apache Cassandra project since 2011.
Biežāk uzdotie jautājumi par e-grāmatām Biežāk uzdotie jautājumi par e-grāmatām
Permanent link: https://www.kriso.lv/db/97810981113426e.html
Keywords: