Course
digicode: UCS
Understanding Cloud Spanner
Get an introduction to Cloud Spanner and understand how it differs from other database products. You also learn when and how to use Cloud Spanner to solve your relational database needs at scale.
Duration
3 days
Price
2'550.–
exkl. 8.1% MWST
Course facts
- Building scalable, managed, relational databases by using Cloud Spanner
- Creating and managing Cloud Spanner databases by using the CLI, Terraform, Python API, and the Google Cloud console
- Programming and running queries and transactions by using the Cloud Spanner API
- Integrating Cloud Spanner with applications
- What is Spanner?
- Spanner and the CAP Theorem
- History of Spanner
- Cloud Spanner Use Cases
- 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.
- Planning Spanner Instances
- Automating Instance Creating
- Creating Databases in Spanner
- 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
- Lab: Creating Spanner Instances and Databases (Console)
- Lab: Creating Spanner Instances and Databases (CLI and Terraform)
- Spanner Architecture
- Choosing Primary Keys
- Defining Database Schemas in Spanner
- Understanding Interleaving and Foreign Keys
- Understanding Secondary Indexes
- Optimize schemas for Spanner architecture.
- Choose appropriate primary keys.
- Manage relationships with primary and foreign keys and with interleaved tables.
- Lab: Choosing Primary Keys
- Lab: Managing relationships with Foreign Keys and Interleaved Tables
- Authentication and Authorization
- Using the Spanner Client Libraries
- Running Queries
- Managing Transactions
- 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.
- Lab: Programming Spanner Applications with Python
- Lab: Running Queries and Transactions
- Using Spanner from Applications
- Building Data Pipelines into and out of Spanner
- Deploy Spanner applications to Google Cloud serverless runtimes.
- Migrate data to and from Cloud Spanner by using Dataflow jobs and Apache Beam.
- Lab: Deploying Spanner Applications with Cloud Functions and Cloud Run
- Lab: Migrating Data to and from Spanner with Dataflow
- Managing your Data in Spanner
- Managing Change Operations
- Administer Cloud Spanner instances.
- Backup, restore, import, and export data.
- Modify database schemas with no downtime.
- Monitor your Cloud Spanner databases and applications
- Lab: Reconciling Account Data with Cloud Spanner Change Streams
- Lab: Leverage the Autoscaler Tool for Cloud Spanner to Achieve Workload Elasticity
- Review best practices for using Cloud Spanner
- Challenge Lab: Administering a Spanner Database
- Cloud Spanner
- Cloud Functions
- Cloud Run
- Dataflow