Azure Cosmos DB for PostgreSQL
Offered By: Microsoft via Microsoft Learn
Course Description
Overview
- Module 1: In this module, you'll learn how to model, build, and alter a scalable, distributed, relational database in Azure Cosmos DB for PostgreSQL.In this module, you will: - Identify key considerations for modeling data for Azure Cosmos DB for PostgreSQL.
- Classify tables in Azure Cosmos DB for PostgreSQL.
- Create tables within an Azure Cosmos DB for PostgreSQL cluster.
- Alter tables within an Azure Cosmos DB for PostgreSQL cluster.
 
- Module 2: Understand how data is distributed across Azure Cosmos DB for PostgreSQL to efficiently ingest and query data across the cluster.By the end of this module, you'll be able to: - Identify data ingestion techniques in Azure Cosmos DB for PostgreSQL.
- Run queries on distributed data in Azure Cosmos DB for PostgreSQL.
- Examine ways to view data distribution.
 
- Module 3: In this module, you learn how to use PostgreSQL extensions to enhance and extend the functionality of Azure Cosmos DB for PostgreSQL. PostgreSQL allows you to extend the functionality of a database by using extensions. Extensions allow for bundling multiple related SQL objects together in a single package that can be loaded or removed from the database with a single command. After being loaded in the database, extensions can function like built-in features.By the end of this module, you'll be able to: - Install different extensions available in Azure Cosmos DB for PostgreSQL.
- Extend the functionality of an Azure Cosmos DB for PostgreSQL database using extensions.
 
- Module 4: Learn how to scale and rebalance data, create read replicas, and enable high availability on an Azure Cosmos DB for PostgreSQL cluster.By the end of this module, you're able to: - Scale and rebalance data in an Azure Cosmos DB for PostgreSQL cluster to accommodate data growth
- Add a read replica to a region in Azure Cosmos DB for PostgreSQL to address analytics demans
- Configure high availability for Azure Cosmos DB for PostgreSQL to ensure data is available when the users need it
 
- Module 5: In this module, you learn how to grow from a single-node, nondistributed cluster to a multi-node, distributed cluster by using Azure Cosmos DB for PostgreSQL.In this module, you'll: - Create a single-node instance of Azure Cosmos DB for PostgreSQL.
- Identify changes to upgrade an existing single-node, nondistributed cluster to a multi-node, distributed cluster.
- Scale the database and distribute the data across multiple nodes.
 
- Module 6: Azure Cosmos DB for PostgreSQL is the ideal database from hosting PostgreSQL at any scale. The distributed architecture allows multitenant software as a service (SaaS) application providers to easily scale from a single-node to a multi-node distributed cluster as the number of tenants grows.By the end of this module, you'll be able to: - Prepare tables that are in a single-node database for distribution.
- Transition from a single-node database to a multi-node database by using Azure Cosmos DB for PostgreSQL.
- Distribute multitenant tables with minimal application impact.
- Monitor the utilization of multitenant databases by using Azure Cosmos DB for PostgreSQL.
 
Syllabus
- Module 1: Module 1: Model data for Azure Cosmos DB for PostgreSQL- Introduction
- Classify tables based on processing
- Exercise - Create tables in Azure Cosmos DB for PostgreSQL
- Scaffold data for distribution
- Exercise - Create scaffolding in Azure Cosmos DB for PostgreSQL
- Partition time series data
- Exercise - Create time series partitions
- Alter scaffolding in a distributed environment
- Exercise - Alter scaffolding in Azure Cosmos DB for PostgreSQL
- Knowledge check
- Summary
 
- Module 2: Module 2: Ingest and query data using Azure Cosmos DB for PostgreSQL- Introduction
- Load data into Azure Cosmos DB for PostgreSQL distributed tables
- Exercise - Load data into distributed tables with Azure Cosmos DB for PostgreSQL
- Use coordinator metadata tables and views to understand data distribution
- Exercise - Query coordinator metadata tables to understand data distribution
- Understand distributed query execution
- Query distributed tables in Azure Cosmos DB for PostgreSQL
- Examine anti-patterns for distributed queries
- Exercise - Query distributed data using Azure Cosmos DB for PostgreSQL
- Examine unsupported features
- Knowledge check
- Summary
 
- Module 3: Module 3: Extend the functionality of Azure Cosmos DB for PostgreSQL using extensions- Introduction
- Examine distributed capabilities provided by Citus
- Exercise - Explore how Citus distributes tables
- Apply PostgreSQL extensions
- Understand the Azure Storage extension
- Exercise - Work with data files in Azure Blob Storage directly from Azure Cosmos DB for PostgreSQL
- Knowledge check
- Summary
 
- Module 4: Module 4: Manage performance and availability in Azure Cosmos DB for PostgreSQL- Introduction
- Scale and rebalance data in Azure Cosmos DB for PostgreSQL
- Exercise - Scale and rebalance data
- Work with read replicas in Azure Cosmos DB for PostgreSQL
- Exercise - Manage read replicas
- Configure high availability in Azure Cosmos DB for PostgreSQL
- Exercise - Configure high availability
- Knowledge check
- Summary
 
- Module 5: Module 5: Scale from a single node to multiple nodes by using Azure Cosmos DB for PostgreSQL- Introduction
- Use cases for single-node Azure Cosmos DB for PostgreSQL
- Exercise - Create a single-node cluster in Azure Cosmos DB for PostgreSQL
- Understand architecture changes when you scale in Azure Cosmos DB for PostgreSQL
- Exercise - Scale from a single node to multiple nodes in Azure Cosmos DB for PostgreSQL
- Address schema concerns when you scale to multi-node, distributed data
- Distribute tables in Azure Cosmos DB for PostgreSQL
- Exercise - Distribute data in Azure Cosmos DB for PostgreSQL
- Knowledge check
- Summary
 
- Module 6: Module 6: Design multitenant SaaS apps by using Azure Cosmos DB for PostgreSQL- Introduction
- Prepare tables for a multitenant data architecture
- Exercise - Prepare tables for distribution
- Distribute tables with minimal application disruption
- Exercise - Distribute multitenant tables
- Monitor tenants in a multitenant database
- Isolate tenants in a multitenant SaaS database
- Exercise - Isolate a tenant in a multitenant database
- Knowledge check
- Summary
 
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