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E-raamat: Google Cloud Platform in Action

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  • Formaat: 632 pages
  • Ilmumisaeg: 15-Aug-2018
  • Kirjastus: Manning Publications
  • Keel: eng
  • ISBN-13: 9781638355908
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Google Cloud Platform in ActionSuurem pilt
  • Formaat: 632 pages
  • Ilmumisaeg: 15-Aug-2018
  • Kirjastus: Manning Publications
  • Keel: eng
  • ISBN-13: 9781638355908
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DESCRIPTION

Cloud services make it easy to get infrastructure in a flexible and ondemand

way. While there are many cloud services to choose from,

Google Cloud Platform offers unique services that let you focus on

building powerful applications.





Google Cloud Services in Action teaches readers to build and launch web applications that scale while leveraging the Google Cloud

Platform. Readers begin with the basics, learning how cloud services

work, and the specifics of the Google Cloud Platform. The book

includes hands-on step-by-step instruction on deploying applications,

handling large amounts of data, and much more By the end, readers

will know how to build, leverage, and deploy cloud-based applications

so web applications get started more quickly, suffer fewer disasters,

and require less maintenance.





KEY FEATURES

Hands on code examples

Lots of useful images

Written in an approachable way

Helps readers get their applications deployed quickly

AUDIENCE

Readers will have a working knowledge of application development in a

modern language and an understanding of application architecture. No

knowledge of cloud services required.

ABOUT THE TECHNOLOGY

Put simply, Google Cloud Platform (GCP) is a collection of products that

allows developers to use Googles internal infrastructure via a set of APIs.

In other words, GCP is a collection of products and services that help users

solve infrastructure problems "The Google Way".
Foreword xvii
Preface xix
Acknowledgments xxi
About This Book xxiii
About The Cover Illustration xxvii
Part 1 Getting Started 1(50)
1 What is "cloud"?
3(21)
1.1 What is Google Cloud Platform?
4(1)
1.2 Why cloud?
4(2)
Why not cloud?
5(1)
1.3 What to expect from cloud services
6(3)
Computing
6(1)
Storage
7(1)
Analytics (aka, Big Data)
8(1)
Networking
8(1)
Pricing
9(1)
1.4 Building an application for the cloud
9(4)
What is a cloud application?
9(1)
Example: serving photos
10(2)
Example projects
12(1)
1.5 Getting started with Google Cloud Platform
13(5)
Signing up for GCP
13(1)
Exploring the console
14(1)
Understanding projects
15(1)
Installing the SDK
16(2)
1.6 Interacting with GCP
18(6)
In the browser: the Cloud Console
18(2)
On the command line: gcloud
20(2)
In your own code: google-cloud-*
22(2)
2 Trying it out: deploying WordPress on Google Cloud
24(14)
2.1 System layout overview
25(1)
2.2 Digging into the database
26(5)
Turning on a Cloud SQL instance
27(1)
Securing your Cloud SQL instance
28(2)
Connecting to your Cloud SQL instance
30(1)
Configuring your Cloud SQL instance for WordPress
30(1)
2.3 Deploying the WordPress VM
31(2)
2.4 Configuring WordPress
33(3)
2.5 Reviewing the system
36(1)
2.6 Turning it off
37(1)
3 The cloud data center
38(13)
3.1 Data center locations
39(3)
3.2 Isolation levels and fault tolerance
42(3)
Zones
42(1)
Regions
42(1)
Designing for fault tolerance
43(2)
Automatic high availability
45(1)
3.3 Safety concerns
45(3)
Security
46(1)
Privacy
47(1)
Special cases
48(1)
3.4 Resource isolation and performance
48(3)
Part 2 Storage 51(190)
4 Cloud SQL: managed relational storage
53(36)
4.1 What's Cloud SQL?
54(1)
4.2 Interacting with Cloud SQL
54(6)
4.3 Configuring Cloud SQL for production
60(8)
Access control
60(1)
Connecting over SSL
61(5)
Maintenance windows
66(1)
Extra MySQL options
67(1)
4.4 Scaling up (and down)
68(3)
Computing power
69(1)
Storage
69(2)
4.5 Replication
71(4)
Replica-specific operations
75(1)
4.6 Backup and restore
75(6)
Automated daily backups
76(1)
Manual data export to Cloud Storage
77(4)
4.7 Understanding pricing
81(2)
4.8 When should I use Cloud SQL?
83(2)
Structure
83(1)
Query complexity
84(1)
Durability
84(1)
Speed (latency)
84(1)
Throughput
84(1)
4.9 Cost
85(2)
Overall
85(2)
4.10 Weighing Cloud SQL against a VM running MySQL
87(2)
5 Cloud Datastore: document storage
89(28)
5.1 What's Cloud Datastore?
90(11)
Design goals for Cloud Datastore
91(1)
Concepts
92(4)
Consistency and replication
96(3)
Consistency with data locality
99(2)
5.2 Interacting with Cloud Datastore
101(6)
5.3 Backup and restore
107(3)
5.4 Understanding pricing
110(1)
Storage costs
110(1)
Per-operation costs
110(1)
5.5 When should I use Cloud Datastore?
111(6)
Structure
111(1)
Query complexity
112(1)
Durability
112(1)
Speed (latency)
112(1)
Throughput
113(1)
Cost
113(1)
Overall
113(2)
Other document storage systems
115(2)
6 Cloud Spanner: large-scale SQL
117(41)
6.1 What is NewSQL?
118(1)
6.2 What is Spanner?
118(1)
6.3 Concepts
118(3)
Instances
119(1)
Nodes
120(1)
Databases
120(1)
Tables
120(1)
6.4 Interacting with Cloud Spanner
121(11)
Creating an instance and database
122(3)
Creating a table
125(2)
Adding data
127(1)
Querying data
127(4)
Altering database schema
131(1)
6.5 Advanced concepts
132(20)
Interleaved tables
133(3)
Primary keys
136(1)
Split points
137(1)
Choosing primary keys
138(1)
Secondary indexes
139(6)
Transactions
145(7)
6.6 Understanding pricing
152(1)
6.7 When should I use Cloud Spanner?
153(5)
Structure
154(1)
Query complexity
154(1)
Durability
154(1)
Speed (latency)
154(1)
Throughput
154(1)
Cost
155(1)
Overall
155(3)
7 Cloud Bigtable: large-scale structured data
158(41)
7.1 What is Bigtable?
159(3)
Design goals
159(2)
Design nongoals
161(1)
Design overview
162(1)
7.2 Concepts
162(11)
Data model concepts
163(5)
Infrastructure concepts
168(5)
7.3 Interacting with Cloud Bigtable
173(11)
Creating a Bigtable Instance
173(2)
Creating your schema
175(2)
Managing your data
177(4)
Importing and exporting data
181(3)
7.4 Understanding pricing
184(1)
7.5 When should I use Cloud Bigtable?
185(5)
Structure
185(1)
Query complexity
186(1)
Durability
186(1)
Speed (latency)
186(1)
Throughput
186(1)
Cost
187(1)
Overall
187(3)
7.6 What's the difference between Bigtable and HBase?
190(1)
7.7 Case study: InstaSnap recommendations
191(7)
Querying needs
191(1)
Tables
192(1)
Users table
192(3)
Recommendations table
195(1)
Processing data
196(2)
7.8 Summary
198(1)
8 Cloud Storage: object storage
199(42)
8.1 Concepts
200(1)
Buckets and objects
200(1)
8.2 Storing data in Cloud Storage
201(3)
8.3 Choosing the right storage class
204(3)
Multiregional storage
204(1)
Regional storage
205(1)
Nearline storage
205(1)
Coldline storage
206(1)
8.4 Access control
207(12)
Limiting access with ACLs
207(6)
Signed URLs
213(4)
Logging access to your data
217(2)
8.5 Object versions
219(4)
8.6 Object lifecycles
223(2)
8.7 Change notifications
225(3)
URL restrictions
227(1)
8.8 Common use cases
228(2)
Hosting user content
228(1)
Data archival
229(1)
8.9 Understanding pricing
230(6)
Amount of data stored
231(1)
Amount of data transferred
232(1)
Number of operations executed
233(1)
Nearline and Coldline pricing
234(2)
8.10 When should I use Cloud Storage?
236(7)
Structure
236(1)
Query complexity
236(1)
Durability
236(1)
Speed (latency)
237(1)
Throughput
237(1)
Overall
237(1)
To-do list
237(1)
E*Exchange
238(1)
InstaSnap
238(3)
Part 3 Computing 241(184)
9 Compute Engine: virtual machines
243(63)
9.1 Launching your first (or second) VM
244(1)
9.2 Block storage with Persistent Disks
245(19)
Disks as resources
246(1)
Attaching and detaching disks
247(3)
Using your disks
250(2)
Resizing disks
252(1)
Snapshots
253(5)
Images
258(1)
Performance
259(2)
Encryption
261(3)
9.3 Instance groups and dynamic resources
264(12)
Changing the size of an instance group
269(1)
Rolling updates
270(4)
Autoscaling
274(2)
9.4 Ephemeral computing with preemptible VMs
276(4)
Why use preemptible machines?
277(1)
Turning on preemptible VMs
278(1)
Handling terminations
278(1)
Preemption selection
279(1)
9.5 Load balancing
280(9)
Backend configuration
282(3)
Host and path rules
285(1)
Frontend configuration
286(1)
Reviewing the configuration
287(2)
9.6 Cloud CDN
289(5)
Enabling Cloud CDN
290(3)
Cache control
293(1)
9.7 Understanding pricing
294(7)
Computing capacity
294(1)
Sustained use discounts
295(3)
Preemptible prices
298(1)
Storage
298(1)
Network traffic
299(2)
9.8 When should I use GCE?
301(5)
Flexibility
301(1)
Complexity
302(1)
Performance
302(1)
Cost
302(1)
Overall
302(1)
To-Do List
303(1)
E*Exchange
303(1)
InstaSnap
304(2)
10 Kubernetes Engine: managed Kubernetes clusters
306(31)
10.1 What are containers?
307(3)
Configuration
307(1)
Standardization
307(2)
Isolation
309(1)
10.2 What is Docker?
310(1)
10.3 What is Kubernetes?
310(5)
Clusters
312(1)
Nodes
312(1)
Pods
313(1)
Services
314(1)
10.4 What is Kubernetes Engine?
315(1)
10.5 Interacting with Kubernetes Engine
315(12)
Defining your application
315(2)
Running your container locally
317(2)
Deploying to your container registry
319(1)
Setting up your Kubernetes Engine cluster
320(1)
Deploying your application
321(2)
Replicating your application
323(2)
Using the Kubernetes UI
325(2)
10.6 Maintaining your cluster
327(5)
Upgrading the Kubernetes master node
327(2)
Upgrading cluster nodes
329(2)
Resizing your cluster
331(1)
10.7 Understanding pricing
332(1)
10.8 When should I use Kubernetes Engine?
332(5)
Flexibility
332(1)
Complexity
333(1)
Performance
333(1)
Cost
334(1)
Overall
334(1)
To-Do List
334(1)
E*Exchange
335(1)
InstaSnap
335(2)
11 App Engine: fully managed applications
337(48)
11.1 Concepts
338(5)
Applications
339(2)
Services
341(1)
Versions
342(1)
Instances
342(1)
11.2 Interacting with App Engine
343(18)
Building an application in App Engine Standard
344(9)
On App Engine Flex
353(8)
11.3 Scaling your application
361(10)
Scaling on App Engine Standard
362(5)
Scaling on App Engine Flex
367(1)
Choosing instance configurations
368(3)
11.4 Using App Engine Standard's managed services
371(8)
Storing data with Cloud Datastore
371(1)
Caching ephemeral data
372(2)
Deferring tasks
374(1)
Splitting traffic
375(4)
11.5 Understanding pricing
379(1)
11.6 When should I use App Engine?
380(5)
Flexibility
380(1)
Complexity
381(1)
Performance
381(1)
Cost
381(1)
Overall
382(1)
To-Do List
382(1)
E*Exchange
382(1)
InstaSnap
383(2)
12 Cloud Functions: seroerless applications
385(21)
12.1 What are microservices?
385(1)
12.2 What is Google Cloud Functions?
386(5)
Concepts
388(3)
12.3 Interacting with Cloud Functions
391(4)
Creating a function
391(1)
Deploying a function
392(2)
Triggering a function
394(1)
12.4 Advanced concepts
395(8)
Updating functions
395(1)
Deleting functions
396(1)
Using dependencies
396(3)
Calling other Cloud APIs
399(2)
Using a Google Source Repository
401(2)
12.5 Understanding pricing
403(3)
13 Cloud DNS: managed DNS hosting
406(19)
13.1 What is Cloud DNS?
407(3)
Example DNS entries
409(1)
13.2 Interacting with Cloud DNS
410(8)
Using the Cloud Console
410(4)
Using the Node.js client
414(4)
13.3 Understanding pricing
418(1)
Personal DNS hosting
418(1)
Startup business DNS hosting
418(1)
13.4 Case study: giving machines DNS names at boot
419(6)
Part 4 Machine Learning 425(94)
14 Cloud Vision: image recognition
427(19)
14.1 Annotating images
428(15)
Label annotations
429(3)
Faces
432(3)
Text recognition
435(2)
Logo recognition
437(3)
Safe-for-work detection
440(1)
Combining multiple detection types
441(2)
14.2 Understanding pricing
443(1)
14.3 Case study: enforcing valid profile photos
443(3)
15 Cloud Natural Language: text analysis
446(17)
15.1 How does the Natural Language API work?
447(1)
15.2 Sentiment analysis
448(4)
15.3 Entity recognition
452(3)
15.4 Syntax analysis
455(2)
15.5 Understanding pricing
457(2)
15.6 Case study: suggesting InstaSnap hash-tags
459(4)
16 Cloud Speech: audio-to-text conversion
463(10)
16.1 Simple speech recognition
465(2)
16.2 Continuous speech recognition
467(1)
16.3 Hinting with custom words and phrases
468(1)
16.4 Understanding pricing
469(1)
16.5 Case study: InstaSnap video captions
469(4)
17 Cloud Translation: multilanguage machine translation
473(12)
17.1 How does the Translation API work?
475(2)
17.2 Language detection
477(2)
17.3 Text translation
479(2)
17.4 Understanding pricing
481(1)
17.5 Case study: translating InstaSnap captions
481(4)
18 Cloud Machine Learning Engine: managed machine learning
485(34)
18.1 What is machine learning?
485(6)
What are neural networks?
486(2)
What is TensorFlow?
488(3)
18.2 What is Cloud Machine Learning Engine?
491(7)
Concepts
492(3)
Putting it all together
495(3)
18.3 Interacting with Cloud ML Engine
498(16)
Overview of US Census data
498(1)
Creating a model
499(2)
Setting up Cloud Storage
501(2)
Training your model
503(3)
Making predictions
506(3)
Configuring your underlying resources
509(5)
18.4 Understanding pricing
514(7)
Training costs
514(2)
Prediction costs
516(3)
Part 5 Data Processing And Analytics 519(70)
19 BigQuery: highly scalable data warehouse
521(26)
19.1 What is BigQuery?
521(7)
Why BigQuery?
522(1)
How does BigQuery work?
522(3)
Concepts
525(3)
19.2 Interacting with BigQuery
528(16)
Querying data
528(5)
Loading data
533(9)
Exporting datasets
542(2)
19.3 Understanding pricing
544(3)
Storage pricing
544(1)
Data manipulation pricing
545(1)
Query pricing
545(2)
20 Cloud Dataflow: large-scale data processing
547(21)
20.1 What is Apache Beam?
549(7)
Concepts
550(5)
Putting it all together
555(1)
20.2 What is Cloud Dataflow?
556(1)
20.3 Interacting with Cloud Dataflow
557(8)
Setting up
557(2)
Creating a pipeline
559(1)
Executing a pipeline locally
560(1)
Executing a pipeline using Cloud Dataflow
561(4)
20.4 Understanding pricing
565(3)
21 Cloud Pub/Sub: managed event publishing
568(21)
21.1 The headache of messaging
569(1)
21.2 What is Cloud Pub/Sub?
569(1)
21.3 Life of a message
569(3)
21.4 Concepts
572(4)
Topics
572(1)
Messages
572(2)
Subscriptions
574(1)
Sample configuration
575(1)
21.5 Trying it out
576(5)
Sending your first message
576(2)
Receiving your first message
578(3)
21.6 Push subscriptions
581(2)
21.7 Understanding pricing
583(1)
21.8 Messaging patterns
584(5)
Fan-out broadcast messaging
584(3)
Work-queue messaging
587(2)
Index 589
AUTHOR BIO





John Geewax is a Software Engineer at Google working specifically on

Google Cloud Platform. He has been using cloud services since 2008.
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