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Azurecloud~10 mins

Cosmos DB overview and use cases in Azure - Step-by-Step Execution

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Process Flow - Cosmos DB overview and use cases
Start: Need for global data
Choose Cosmos DB
Create Cosmos DB account
Select API (SQL, Mongo, Cassandra, etc.)
Design data model
Deploy and replicate data globally
Use Cosmos DB for apps
Scale and monitor performance
Meet low latency and high availability needs
This flow shows the steps from deciding to use Cosmos DB for global data needs, through setup, to using it in applications with scaling and monitoring.
Execution Sample
Azure
Create Cosmos DB account
Choose API (e.g., SQL)
Create container
Insert item
Query item
Scale throughput
This sequence shows basic Cosmos DB operations from setup to data use and scaling.
Process Table
StepActionInput/ConditionResult/Output
1Create Cosmos DB accountProvide account name and regionAccount created with global distribution option
2Select APIChoose SQL APIAPI set for SQL queries
3Create containerDefine database and container with partition keyContainer ready to store JSON documents
4Insert itemAdd JSON document {"id":1, "name":"Alice"}Item stored in container
5Query itemQuery for id=1Returns document {"id":1, "name":"Alice"}
6Scale throughputIncrease RU/s from 400 to 1000Throughput scaled, better performance
7Replicate dataEnable multi-region writeData replicated globally with low latency
8MonitorCheck metricsPerformance and availability monitored
9Use in appApp reads/writes dataApp experiences fast, reliable data access
10ExitNo more actionsEnd of Cosmos DB basic workflow
💡 All key Cosmos DB setup and usage steps completed
Status Tracker
VariableStartAfter Step 3After Step 4After Step 6Final
AccountNoneCreatedCreatedCreatedCreated
APINoneSQL selectedSQL selectedSQL selectedSQL selected
ContainerNoneCreatedCreatedCreatedCreated
Data ItemsEmptyEmpty1 item inserted1 item inserted1 item inserted
Throughput (RU/s)400 (default)4004001000 (scaled)1000
ReplicationSingle regionSingle regionSingle regionSingle regionMulti-region enabled
Key Moments - 3 Insights
Why do we choose an API like SQL or Mongo when creating Cosmos DB?
Because Cosmos DB supports multiple APIs to match different app needs; choosing SQL API (see step 2) lets you use familiar SQL queries on JSON data.
What happens when we scale throughput in Cosmos DB?
Scaling throughput (step 6) increases the Request Units per second (RU/s), allowing faster and more concurrent operations, improving app performance.
How does global replication affect data access?
Enabling multi-region replication (step 7) copies data to multiple regions, reducing latency and increasing availability for users worldwide.
Visual Quiz - 3 Questions
Test your understanding
Look at the execution table, what is the throughput after step 6?
A400 RU/s
B200 RU/s
C1000 RU/s
DUnlimited
💡 Hint
Check the 'Throughput (RU/s)' variable in the variable_tracker after step 6
At which step is the first data item inserted into Cosmos DB?
AStep 4
BStep 3
CStep 5
DStep 6
💡 Hint
Look at the execution_table row where 'Insert item' action happens
If we do not enable multi-region replication, what remains the replication state?
AMulti-region enabled
BSingle region
CNo replication
DReplication disabled
💡 Hint
See the 'Replication' variable in variable_tracker before step 7
Concept Snapshot
Cosmos DB is a globally distributed database service.
Choose an API (SQL, Mongo, Cassandra) to match your app.
Create containers to store JSON documents.
Scale throughput (RU/s) for performance.
Enable multi-region replication for low latency and high availability.
Use Cosmos DB for apps needing fast, global data access.
Full Transcript
This visual execution shows how to use Azure Cosmos DB from start to finish. First, you create a Cosmos DB account and select the API type, such as SQL. Then you create a container to hold your data. You insert items as JSON documents and query them using the chosen API. You can scale throughput to improve performance. Enabling multi-region replication copies data globally for fast access everywhere. Monitoring helps keep track of performance and availability. This process supports apps that need reliable, low-latency data worldwide.