GCP-UCS: Understanding Cloud Spanner

Module 1: The Need for Spanner
Topics:

• What is Spanner?
• Spanner and the CAP Theorem
• History of Spanner
• Cloud Spanner Use Cases

Objectives:

• Explain the core concepts and features of Cloud Spanner
• Understand how Cloud Spanner fits in the CAP theorem.
• Describe the history of Cloud Spanner.
• Explain Cloud Spanner use cases.

Module 2: Getting Started with Spanner
Topics:

• Planning Spanner Instances
• Automating Instance Creating
• Creating Databases in Spanner

Objectives:

• Architect Cloud Spanner instances based on location, capacity, availability, and cost.
• Create Spanner instances by using the Google Cloud console, Google Cloud CLI, and Terraform.
• Create Spanner databases by using SQL

Activities:

• Lab: Creating Spanner Instances and Databases (Console)
• Lab: Creating Spanner Instances and Databases (CLI and Terraform)

Module 3: Optimizing Spanner Schemas
Topics:

• Spanner Architecture
• Choosing Primary Keys
• Defining Database Schemas in Spanner
• Understanding Interleaving and Foreign Keys
• Understanding Secondary Indexes

Objectives:

• Optimize schemas for Spanner architecture.
• Choose appropriate primary keys.
• Manage relationships with primary and foreign keys and with interleaved tables.

Activities:

• Lab: Choosing Primary Keys
• Lab: Managing relationships with Foreign Keys and Interleaved Tables

Module 4: Programming Spanner Applications, Queries, and Transactions
Topics:

• Authentication and Authorization
• Using the Spanner Client Libraries
• Running Queries
• Managing Transactions

Objectives:

• Authenticate users and applications that access Spanner databases using Identity Access Management.
• Program Spanner applications using Google Cloud client libraries and Python.
• Optimize queries using strong reads, stale reads, and indexes.
• Manage transactions in Spanner.

Activities:

• Lab: Programming Spanner Applications with Python
• Lab: Running Queries and Transactions

Module 5: Deploying Spanner Applications
Topics:

• Using Spanner from Applications
• Building Data Pipelines into and out of Spanner

Objectives

• Deploy Spanner applications to Google Cloud serverless runtimes.
• Migrate data to and from Cloud Spanner by using Dataflow jobs and Apache Beam.

Activities:

• Lab: Deploying Spanner Applications with Cloud Functions and Cloud Run
• Lab: Migrating Data to and from Spanner with Dataflow

Module 6: Spanner Administration
Topics:

• Managing your Data in Spanner
• Managing Change Operations

Objectives:

• Administer Cloud Spanner instances.
• Backup, restore, import, and export data.
• Modify database schemas with no downtime.
• Monitor your Cloud Spanner databases and applications

Activities:

• Lab: Reconciling Account Data with Cloud Spanner Change Streams
• Lab: Leverage the Autoscaler Tool for Cloud Spanner to Achieve Workload Elasticity

Module 7: Spanner Best Practices
Topics:

• Spanner Best Practices
• Challenge Lab

Objectives:

• Review best practices for using Cloud Spanner

Activities:

• Challenge Lab: Administering a Spanner Database