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Introduction to GCP

Introduction to GCP

Krunal Kapadiya

August 29, 2021
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  1. Google Cloud Introduction
    Krunal Kapadiya
    @krunal3kapadiya

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  2. Agenda
    - Getting Started...
    - Cloud Platform services
    - Resource Management
    - Developing, Deploying and Monitoring into Cloud
    - Kubernetes Engine
    - Big data and Machine Learning Services
    - Machine Learning APIs enable apps to see, hear and understand
    2

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  3. Getting Started...
    - What is Google Cloud
    - Difference between other cloud platform to Google Cloud
    - Cloud Network Architecture
    - Global
    - Regional
    - Zonal
    3

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  4. Cloud Platform services
    4
    Compute Storage
    Big Data Machine Learning

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  5. Compute
    5
    Kubernetes
    Engine
    App
    Engine
    Compute
    Engine

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  6. Storage
    6
    Storage
    Bigtable
    Cloud
    SQL
    Cloud
    Spanner
    Cloud
    Datastore

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  7. Big Data
    7
    Big
    Query
    Pub/Sub
    Data
    flow Dataproc Datalab

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  8. Machine Learning
    8
    Translate
    API
    NLP
    Vision
    API
    Speech
    API

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  9. Resource Management
    9

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  10. 10

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  11. Four ways to interact with GCP
    1. Cloud Platform console (web user interface)
    2. Cloud Shell and Cloud SDK (Command-line interface)
    3. Cloud Console Mobile App (For iOS and Android)
    4. REST-based API (for custom applications)
    11

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  12. Cloud Platform Console
    - Centralized console for all project data
    - Developer tools
    - Cloud Source Repositories
    - Cloud Shell
    - Access to product API
    - Manage and create project
    12

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  13. Google Cloud SDK
    - SDK includes CLI tools for Cloud Platform products and services
    - Gcloud, gsutil (Cloud Storage), bq (BigQuery)
    - Available as Docker Image
    - Available via cloud shell
    - Containerized version of Cloud SDK running on Compute Engine instance
    13

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  14. Cloud console mobile app
    - Manage virtual machine and database instances
    - Manage apps in Google App Engine
    - Manage your billing
    - Visualize your projects with customizable dashboard
    14

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  15. Developing, Deploying and Monitoring
    into Cloud
    15

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  16. Cloud Functions Beta
    - Create single-purpose functions that respond to events without a server or
    runtime
    - Event examples: New instance created, file added to cloud storage
    - Written in javascript: execute in managed Node.js environment on GCP
    16

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  17. Deployment Manager
    - Infrastructure management service
    - Create a .yaml template describing your environment and use Deployment
    Manager to create resources
    - Provides repeatable deployments
    17

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  18. Monitoring using stackdriver
    - Monitoring
    - Platform, system and application metrices
    - Uptime/health checks
    - Dashboards and alerts
    - Logging
    - Platform system, and application logs
    - Log search, view, filter and export
    - Log-based metrics
    - Debug (Debug applications)
    - Error reporting (Error notification, Error dashboard)
    - Trace (Letency reporting and sampling, Per-URL latency and statistics)
    18

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  19. Big data and Machine Learning
    Services
    19

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  20. Cloud Dataproc
    - Fast, easy, managed way to run Hadoop and Spark/Hive/Pig on GCP
    - Create clusters in 90 seconds or less, on average
    - Scale clusters up and down even when jobs are running
    20

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  21. Cloud Dataflow
    - Processes data using Compute Engine Instances
    - Clusters are sized for you
    - Automated scaling, no instance provisioning required
    - Write code once and get batch and streaming.
    - Transform-based programming model
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  22. Cloud Pub/Sub
    - Supports many asynchronous messaging
    - Includes support for offline customers
    - Based on proven google technologies
    - Integrates with cloud dataflow for data processing pipelines
    22

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  23. Cloud Datalab
    - Interactive tool for large scale data exploration, transformation, analysis and
    visualization
    - Integrated, open source
    - Runs on App Engine
    - Built on Jupyter (formerly IPython)`
    23

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  24. Containers in cloud
    - Compute Engine
    - Kubernetes Engine
    - App Engine
    24

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  25. Machine Learning APIs enable apps to see, hear and
    understand
    25

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  26. Cloud Machine Learning Platform
    Open source tool to build and run neural network Models
    - Wide platform support CPU or GPU mobile, server or cloud
    Fully managed machine learning service
    - Familiar notebook-based developer experience
    - Optimized for Google infrastructure: integrates with BigQuery and Cloud
    Storage
    26

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  27. Cloud Machine Learning Platform
    Pretrained machine learning models built by Google
    - Speech: Stream results in real time, detects 80 languages
    - Vision: Identify objects, landmarks, text and content
    - Translate: Language translation including detection
    - Natural Language: Structure, meaning of text
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  28. Structured data
    For structured data
    - Classification and regression
    - Recommendation
    - Anomaly detection
    For unstructured data
    - Image and video analytics
    - Text analytics
    28

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  29. Cloud Vision API
    - Analize images with a simple REST API
    - Logo detection, label detection etc
    - With Cloud vision API you can
    - Gain insight from images
    - Detect inappropriate content
    - Analyze sentiment
    - Extract text
    29

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  30. Cloud speech API
    - Recognizes over 80 languages and variants
    - Can return text in real time
    - Highly accurate, even in noisy environment
    - Access from any devices
    - Powered by Google’s Machine Learning
    30

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  31. Cloud Natural Language API
    - Uses machine learning models to reveal structure and meaning of text
    - Extract information about items mentioned in text documents, news articles,
    and blog posts
    - Analyze text uploaded in request or integrate with Cloud storage
    31

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  32. Cloud translation API
    - Translate arbitrary strings between thousands of languages in pairs
    - Programmatically detect a document’s language
    - Supports for dozens of languages
    32

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  33. Cloud Video Intelligence API Beta
    - Annotate the content of videos
    - Detect scenes changes
    - Flag inappropriate content
    - Support for variety of video formats
    33

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  34. References and links for GCP
    - (Hands on training) https://google.qwiklabs.com/
    - (More training with multiple APIs) https://cloud.google.com/training/
    34

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  35. https://krunal3kapadiya.app/
    Thank you!
    Krunal Kapadiya
    @krunal3kapadiya
    35

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