DP-420 Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB Questions and Answers

You can set up alerts from the Azure Cosmos DB pane or the Azure Monitor service in the Azure portal.

Note: Alerts are used to set up recurring tests to monitor the availability and responsiveness of your Azure Cosmos DB resources. Alerts can send you a notification in the form of an email, or execute an Azure Function when one of your metrics reaches the threshold or if a specific event is logged in the activity log.

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.

Setting ConflictResolutionMode to Custom and using the default settings for the policy will not ensure that conflicts are sent to the conflict feed. You need to define a custom stored procedure using the "conflictingItems" parameter to handle conflicts properly.

you can migrate data from various data sources to Azure Cosmos DB using different tools and methods. The choice of the migration tool depends on factors such as the data source, the Azure Cosmos DB API, the size of data, and the expected migration duration1. Some of the common migration tools are:

Azure Cosmos DB Data Migration tool: This is an open source tool that can import data to Azure Cosmos DB from sources such as JSON files, MongoDB, SQL Server, CSV files, and Azure Cosmos DB collections. This tool supports the SQL API and the Table API of Azure Cosmos DB2.

Azure Data Factory: This is a cloud-based data integration service that can copy data from various sources to Azure Cosmos DB using connectors. This tool supports the SQL API, MongoDB API, Cassandra API, Gremlin API, and Table API of Azure CosmosDB3.

Azure Cosmos DB live data migrator: This is a command-line tool that can migrate data from one Azure Cosmos DB container to another container within the same or different account. This tool supports live migration with minimal downtime and works with any Azure Cosmos DB API4.

For your scenario, if you want to migrate data from a third-party application that is exposed through an OData endpoint to a container in Azure Cosmos DB for NoSQL, you should use Azure Data Factory. Azure Data Factory has an OData connector that can read data from an OData source and write it to an Azure Cosmos DB sink using the SQL API5. You can create a copy activity in Azure Data Factory that specifies the OData source and the Azure Cosmos DB sink, and run it on demand or on a schedule.

According to the Azure Cosmos DB documentation1, Always Encrypted is a feature designed to protect sensitive data, such as credit card numbers or national identification numbers, stored in Azure Cosmos DB. Always Encrypted allows clients to encrypt sensitive data inside client applications and never reveal the encryption keys to the database.

To use Always Encrypted, you need to define an encryption policy for each container that specifies which properties should be encrypted and which data encryption keys (DEK) should be used. The DEKs are stored in Azure Cosmos DB and are wrapped by customer-managed keys (CMK) that are stored in Azure Key Vault.

Based on the encryption policy shown in the exhibits, the creditcard property is encrypted with a DEK named dek1, and the SSN property is encrypted with a DEK named dek2. Both DEKs are wrapped by a CMK named cmk1.

To answer your statements:

You can perform a query that filters on the creditcard property = No. This is because the creditcard property is encrypted and cannot be used for filtering or sorting operations1.

You can perform a query that filters on the SSN property = No. This is also because the SSN property is encrypted andcannot be used for filtering or sorting operations1.

An application can be allowed to read the creditcard property while being restricted from reading the SSN property = Yes. This is possible by using different CMKs to wrap different DEKs and applying access policies on the CMKs in Azure Key Vault. For example, if you use cmk2 to wrap dek2 instead of cmk1, you can grant an application access to cmk1 but not cmk2, which means it can read the creditcard property but not the SSN property2.

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.

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.

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.

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.