You can use the Set-AzCosmosDBAccountRegion cmdlet to update the regions that an Azure Cosmos DB account uses. You can use this cmdlet to add a region or change the region failover order. The cmdlet requires a resource group name, an Azure Cosmos DB account name, and a list of regions in desired failover order1.

For your scenario, based on the PowerShell command, you are using the Set-AzCosmosDBAccountRegion cmdlet to update the regions for an Azure Cosmos DB account named account1 that is configured for automatic failover. The command specifies two regions: West US and East US. The effect of running the command is that the account will be configured for multi-region writes.

Multi-region writes is a feature of Azure Cosmos DB that allows you to write data to any region in your account and have it automatically replicated to all other regions. This feature provides high availability and low latency for write operations across multiple regions. To enable multi-region writes, you need to specify at least two regions in your account and set them as write regions2. In your command, you are setting both West US and East US as write regions by using the -IsZoneRedundant parameter with a value of $true for both regions.

Cosmos DB Operator: Can provision Azure Cosmos accounts, databases, and containers. Cannot access any data or use Data Explorer.

Children who do no have parents defined will appear on the list = NO

Children who do not have parents defined will not appear on the list. This is because the document schema defines the children property as an array of objects that contain the firstName and gender properties of each child, as well as a parents property that references the id values of the parents. If a child does not have parents defined, it means that the parents property is either missing or empty for that child. Therefore, such a child will not be included in the list of children who have parents defined.

Children who have more than one pet will appear on the list multiple times. = Yes

Children who have more than one pet will appear on the list multiple times. This is because the document schema defines the pets property as an array of objects that contain the givenName and type properties of each pet, as well as a children property that references the id values of the children who own the pet. If a child has more than one pet, it means that the child’s id value will appear in the children property of multiple pet objects. Therefore, such a child will be included in the list of children who have pets multiple times.

Children who do no have pets defined will appear on the list = No

Children who do not have pets defined will not appear on the list. This is because the document schema defines the pets property as an array of objects that contain the givenName and type properties of each pet, as well as a children property that references the id values of the children who own the pet. If a child does not have pets defined, it means that the child’s id value does not appear in the children property of any pet object. Therefore, such a child will not be included in the list of children who have pets defined.

Box 1: Serverless capacity mode

Azure Cosmos DB serverless best fits scenarios where you expect intermittent and unpredictable traffic with long idle times. Because provisioning capacity in such situations isn't required and may be cost-prohibitive, Azure Cosmos DB serverless should be considered in the following use-cases:

Getting started with Azure Cosmos DB

Running applications with bursty, intermittent traffic that is hard to forecast, or low (<10%) average-to-peak traffic ratio

Developing, testing, prototyping and running in production new applications where the traffic pattern is unknown

Integrating with serverless compute services like Azure Functions

Box 2: Provisioned throughput capacity mode and autoscale throughput

The use cases of autoscale include:

Variable or unpredictable workloads: When your workloads have variable or unpredictable spikes in usage, autoscale helps by automatically scaling up and down based on usage. Examples include retail websites that have different traffic patterns depending on seasonality; IOT workloads that have spikes at various times during the day; line of business applications that see peak usage a few times a month or year, and more. With autoscale, you no longer need to manually provision for peak or average capacity.

 Azure Cosmos DB offers two different capacity modes: provisioned throughput and serverless1. Provisioned throughput mode allows you to configure a certain amount of throughput (expressed in Request Units per second or RU/s) that is provisioned on your databases and containers. You get billed for the amount of throughput you’ve provisioned, regardless of how many RUs were consumed1. Serverless mode allows you to run your database operations without having to configure any previously provisioned capacity. You get billed for the number of RUs that were consumed by your database operations and the storage consumed by your data1.

To create a database that minimizes costs, you should consider the following factors:

The read and write volumes of your containers

The predictability and variability of your traffic

The latency and throughput requirements of your application

The geo-distribution and availability needs of your data

Based on these factors, one possible option that you could choose is B. Create a provisioned throughput account. Set the throughput for coll1 to Autoscale. Set the throughput for coll2 and coll3 to Manual.

This option has the following advantages:

It allows you to handle unpredictable read and write volumes for coll1 by using Autoscale, which automatically adjusts the provisioned throughput based on the current load1.

It allows you to handle predictable read and write volumes for coll2 and coll3 by using Manual, which lets you specify a fixed amount of provisioned throughput that meets your performance needs1.

It allows you to optimize your costs by paying only for the throughput you need for each container1.

It allows you to enable geo-distribution for your account if you need to replicate your data across multiple regions1.

This option also has some limitations, such as:

It may not be suitable for scenarios where all containers have intermittent or bursty traffic that is hard to forecast or has a low average-to-peak ratio1.

It may not be optimal for scenarios where all containers have low or sporadic traffic that does not justify provisioned capacity1.

It may not support availability zones or multi-master replication for your account1.

Depending on your specific use case and requirements, you may need to choose a different option. For example, you could use a serverless account if all containers have low or sporadic traffic that does not require predictable performance or geo-distribution1. Alternatively, you could use a provisioned throughput account with Manual for all containers if all containers have stable and consistent traffic that requires predictable performance or geo-distribution1.

Box 1: Yes

"path": "/*" is in includePaths.

Include the root path to selectively exclude paths that don't need to be indexed. This is the recommended approach as it lets Azure Cosmos DB proactively index any new property that may be added to your model.

Box 2: No

"path": "/firstName/?" is in excludePaths.

Box 3: Yes

"path": "/address/city/?" is in includePaths

Store multiple entity types in the same container.

App1 queries the con-product and con-productVendor containers.

Note: Request unit is a performance currency abstracting the system resources such as CPU, IOPS, and memory that are required to perform the database operations supported by Azure Cosmos DB.

Scenario:

Develop an app named App1 that will run from all locations and query the data in account1.

Once multi-region writes are configured, maximize the performance of App1 queries against the data in account1.

Whenever there are multiple solutions for a requirement, select the solution that provides the best performance, as long as there are no additional costs associated.

Scenario: Develop an app named App2 that will run from the retail stores and query the data in account2. App2 must be limited to a single DNS endpoint when accessing account2.

By using Azure Private Link, you can connect to an Azure Cosmos account via a private endpoint. The private endpoint is a set of private IP addresses in a subnet within your virtual network.

When you're using Private Link with an Azure Cosmos account through a direct mode connection, you can use only the TCP protocol. The HTTP protocol is not currently supported.

The partition key is what will determine how data is routed in the various partitions by Cosmos DB and needs to make sense in the context of your specific scenario. The IoT Device ID is generally the "natural" partition key for IoT applications.

Scenario: The iotdb database will contain two containers named con-iot1 and con-iot2.

Ensure that Azure Cosmos DB costs for IoT-related processing are predictable.

Bounded staleness is frequently chosen by globally distributed applications that expect low write latencies but require total global order guarantee. Bounded staleness is great for applications featuring group collaboration and sharing, stock ticker, publish-subscribe/queueing etc.

Scenario: Application updates in con-product frequently cause HTTP status code 429 "Too many requests". You discover that the 429 status code relates to excessive request unit (RU) consumption during the updates.

leaseCollectionPrefix: when set, the value is added as a prefix to the leases created in the Lease collection for this Function. Using a prefix allows two separate Azure Functions to share the same Lease collection by using different prefixes.

Scenario: Use Azure Functions to send notifications about product updates to different recipients.

Trigger the execution of two Azure functions following every update to any document in the con-product container.