Understanding Cloud Spanner

In this course you will learn about Cloud Spanner. You will get an introduction to Cloud Spanner, contrasting it with other Database products to understand when and how to use Spanner to solve your relational database needs at scale. You will learn how to create and manage Spanner databases using various tools on Google Cloud, learn to optimize relational schemas with Spanner’s distributed database model in mind, interact with your Spanner databases using the Spanner APIs, integrate Spanner with your applications, and learn how to use other Google tools for administering Spanner databases and managing your data. The lab culminates with a challenge lab where you demonstrate your knowledge of administering Spanner databases and managing data.

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Duration 3 days
Level intermediate
Format Instructor Led

What you'll learn

  • Build scalable, managed, relational databases using Google Cloud Spanner
  • Create and manage Spanner databases using the CLI, Terraform, Python API, and the Cloud Console
  • Optimize relational database schemas for Spanner’s distributed database model
  • Leverage Google Cloud tools for administering Spanner databases and managing data
  • Program and run queries and transactions using the Spanner API
  • Integrate Spanner with your applications

About this course

Overview
  • 3 days of intermediate level content
  • 10 Hands on Labs
    • Creating Spanner Instances and Databases (Console)
    • Creating Spanner Instances and Databases (CLI and Terraform)
    • Choosing Primary Keys
    • Managing Relationships with Foreign Keys and Interleaved Tables
    • Programming Spanner Applications with Python
    • Running Queries and Transactions
    • Deploying Spanner Applications with Cloud Functions and Cloud Run
    • Migrating Data to and from Spanner with Dataflow
    • Leverage the Autoscaler Tool for Cloud Spanner to Achieve Workload Elasticity
    • Challenge Lab: Administering a Spanner Database
Who this course is for

Database administrators, engineers/developers, and cloud architects who want to learn how to create, optimize, and manage Spanner databases and migrate existing databases into Spanner.

Prerequisite

Some prior Google Cloud experience at the fundamental level is assumed. Experience with relational databases, the SQL language, and some programming is also assumed.

Module 1
The Need for Spanner
Objectives
  • What is Spanner?
  • Spanner and the CAP Theorem
  • History of Spanner
  • Cloud Spanner Use Cases
Module 2
Getting Started with Spanner
Objectives
  • Planning Spanner Instances
  • Automating Instance Creating
  • Creating Databases in Spanner
Module 3
Optimizing Spanner Schemas
Objectives
  • Spanner Architecture
  • Choosing Primary Keys
  • Defining Database Schemas in Spanner
  • Understanding Interleaving and Foreign Keys
  • Understanding Secondary Indexes
Module 4
Programming Spanner Applications, Queries, and Transactions
Objectives
  • Authentication and Authorization
  • Using the Spanner Client Libraries
  • Running Queries
  • Managing Transactions
Module 5
Deploying Spanner Applications
Objectives
  • Using Spanner from Applications
  • Building Data Pipelines into and out of Spanner
Module 6
Spanner Administration
Objectives
  • Managing your Data in Spanner
  • Managing Change
  • Operations
Module 7
Capstone Project
Objectives
  • Spanner Best Practices
  • Capstone Project
Module 8
Creating Spanner Instances and Databases (Console)
Objectives
  • Compare Spanner configuration options.
  • Create Spanner databases using the Console.
  • Create Spanner databases using the PostgreSQL dialect.
Module 9
Instances and Databases (CLI and Terraform)Creating Spanner
Objectives
  • Create instances and databases using the gcloud CLI.
  • Automate Spanner infrastructure using Terraform.
Module 10
Choosing Primary Keys
Objectives
  • Generate Spanner primary keys as UUIDs.
  • Convert counters and timestamps into values appropriate for Spanner primary keys.
Module 11
Managing Relationships with Foreign Keys and Interleaved Tables
Objectives
  • Create a relational database with proper primary keys and relationships optimized for Spanner
  • Leverage indexes to improve read performance in Spanner
Module 12
Programming Spanner Applications with Python
Objectives
  • Use Python to create and delete Spanner instances and databases.
  • Program Spanner databases that use the PostgreSQL dialect.
Module 13
Running Queries and Transactions
Objectives
  • Run parameterized queries using indexes against a Spanner database using the Python Client library.
  • Execute transactions against a Spanner database.
Module 14
Deploying Spanner Applications with Cloud Functions and Cloud Run
Objectives
  • Deploy Cloud Functions that read and write to Spanner databases.
  • Set up and use the Spanner emulator for development.
  • Build a REST API that allows you to read and write Spanner data.
  • Deploy a REST API to Google Cloud Run.
Module 15
Migrating Data to and from Spanner with Dataflow
Objectives
  • Write ETL pipelines using Apache Beam.
  • Run Apache Beam pipelines using Google Cloud Dataflow.
Module 16
Leverage the Autoscaler Tool for Cloud Spanner to Achieve Workload Elasticity
Objectives
  • Configure the Autoscaler and environment
  • Deploy the Autoscaler
  • Observe the autoscaling
Module 17
Challenge Lab: Administering a Spanner Database
Objectives
  • Create a Spanner database and import existing data.
  • Backup and restore the database.
  • Export Spanner data and import it into BigQuery.
  • Deploy a data access API that allows access to your Spanner database.
  • Use the Operations monitoring tools for dashboards, uptime checks, and alerts.

AboutAppsbroker Academy

Appsbroker Academy is an Authorised Training Partner for Google Cloud. Drawing on our own highly skilled engineers’ unique experiences and expertise, we provide dedicated, industry-specific training using real-life examples to help your people to thrive.

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