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

Box 1: Yes

Non-relational data increases write costs, but can decrease read costs.

Box 2: Yes

Non-relational data increases write costs, but can decrease read costs.

Box 3: No

Non-relational data increases write costs, but can decrease read costs.

Box 1 = The current backup policy provides protection for: 2 Hours Azure Cosmos DB automatically takes backups of your data at regular intervals. The backup interval and the retention period can be configured from the Azure portal. You can also choose between two backup modes: periodic backup mode and continuous backup mode. Periodic backup mode is the default mode for all existing accounts and it takes a full backup of your database every 4 hours by default. Continuous backup mode is a new mode that allows you to restore to any point of time within either 7 or 30 days1.

For your scenario, based on the exhibit, you have configured a backup for an Azure Cosmos DB for NoSQL account using the periodic backup mode with a backup interval of 1 hour and a retention period of 2 hours. This means that Azure Cosmos DB will take a full backup of your database every hour and keep only the latest two backups. Therefore, the current backup policy provides protection for 2 hours.

Box 2: In case of emergency, you must (answer choice) to restore the backup = create a support ticket

Azure Cosmos DB automatically takes backups of your data at regular intervals. You can configure the backup interval and the retention period from the Azure portal. You can also choose between two backup modes: periodic backup mode and continuous backup mode. Periodic backup mode is the default mode for all existing accounts and it takes a full backup of your database every 4 hours by default. Continuous backup mode is a new mode that allows you to restore to any point of time within either 7 or 30 days1.

For your scenario, based on the exhibit, you have configured a backup for an Azure Cosmos DB for NoSQL account using the periodic backup mode with a backup interval of 1 hour and a retention period of 2 hours. This means that Azure Cosmos DB will take a full backup of your database every hour and keep only the latest two backups. In case of emergency, you must create a support ticket to restore the backup. This is the answer to your question.

To restore data from a periodic backup, you need to create a support request with Azure Cosmos DB team and provide the following information:

The name of your Azure Cosmos DB account

The name of the database or container that you want to restore

The date and time (in UTC) that you want to restore from

The name of the target Azure Cosmos DB account where you want to restore the data

The name of the target resource group where you want to restore the data

The Azure Cosmos DB team will then initiate the restore process and notify you when it is completed2.

Box 1: Yes

Records with different OrderIDs will match.

Box 2: Yes

Records with different OrderIDs will match.

Box 3: No

Only records with one specific OrderId will match

This is because the write concern is mapped to the default consistency level configured on your Azure Cosmos DB account, which is strong in this case. Strong consistency ensures that every write operation is synchronously committed to every region associated with your Azure Cosmos DB account. The eventual consistency level that the application uses only applies to the read operations. Eventual consistency offers higher availability and better performance, but it does not guarantee the order or latency of the reads.

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.

Box 1: CompanyID

After you create a container with a unique key policy, the creation of a new or an update of an existing item resulting in a duplicate within a logical partition is prevented, as specified by the unique key constraint. The partition key combined with the unique key guarantees the uniqueness of an item within the scope of the container.

For example, consider an Azure Cosmos container with Email address as the unique key constraint and CompanyID as the partition key. When you configure the user's email address with a unique key, each item has a unique email address within a given CompanyID. Two items can't be created with duplicate email addresses and with the same partition key value.

Box 2: emailAddress

Box 1 = Randomized

Box 2 = Deterministic

Always Encrypted for Azure Cosmos DB supports two types of encryption: deterministic and randomized1. Deterministic encryption always produces the same encrypted value for any given plain text value. Randomized encryption produces a different encrypted value for the same plain text value.

For dateOfBirth, randomized encryption is the strongest type of encryption because it provides better protection against statistical analysis and brute-force attacks. Deterministic encryption would not be suitable for dateOfBirth because it could reveal patterns or allow equality comparisons1.

For healthStatus, deterministic encryption is the strongest type of encryption because it allows queries to perform equality comparisons and filters on the encrypted property. Randomized encryption would not be suitable for healthStatus because it would prevent any queries on the encrypted property1.

Azure Cosmos DB is a multi-model database that supports various data models, such as documents, key-value, graph, and column-family3. The core content-model of Cosmos DB’s database engine is based on atom-record-sequence (ARS), which allows it to store and query different types of data in a flexible and efficient way3.

To develop a model that supports order read operations and minimizes the number of requests, you should consider the following factors:

The size and shape of your data

The frequency and complexity of your queries

The latency and throughput requirements of your application

The trade-offs between storage efficiency and query performance

Based on these factors, one possible model that you could implement is B. Create a single database that contains one container. Create a separate document for each order and embed the order items into the order documents.

This model has the following advantages:

It stores orders and order items as self-contained documents that can be easily retrieved by order ID1.

It avoids storing redundant data or creating additional containers for order items1.

It allows you to view the order history of a customer with simple queries1.

It leverages the benefits of embedding data, such as reducing the number of requests, improving query performance, and simplifying data consistency2.

This model also has some limitations, such as:

It may not be suitable for some order items that have data that is greater than 2 KB, as it could exceed the maximum document size limit of 2 MB2.

It may not be optimal for scenarios where order items need to be queried independently from orders or aggregated by other criteria2.

It may not support transactions across multiple orders or customers, as transactions are scoped to a single logical partition2.

Depending on your specific use case and requirements, you may need to adjust this model or choose a different one. For example, you could use a hybrid data model that combines embedding and referencing data2, or you could use a graph data model that expresses entities and relationships as vertices and edges.

If the primary write region fails, applications that write to the database must use a different connection string to continue to use the service. = NOYou do not need to use a different connection string to continue to use the service if the primary write region fails. This is because Azure Cosmos DB supports automatic failover, which means that it will automatically switch the primary write region to another region in case of a regional outage2. The application does not need to change the connection string or specify the failover priority3. The connection string contains a list of all the regions associated with your account, and Azure Cosmos DB will route the requests to the appropriate region based on the availability and latency1.

The primary Read-Only SQL Connection String and the Secondary Read-Only SQL Connection String will connect to different regions from an application running in the East US Azure region = YesThe primary read-only SQL connection string and the secondary read-only SQL connection string will connect to different regions from an application running in the East US Azure region. This is because the primary read-only SQL connection string contains the endpoint for the East US region, which is the same as the primary write region. The secondary read-only SQL connection string contains the endpoint for the West US region, which is the additional read region. Therefore, if an application running in the East US Azure region uses these connection strings, it will connect to different regions depending on which one it chooses.

Applications can choose from which region by setting the PreferredLocations property within their connection properties = Yes

Applications can choose from which region by setting the PreferredLocations property within their connection properties. This property allows you to specify a list of regions that you prefer to read from based on their proximity to your application2. Azure Cosmos DB will route the requests to the appropriate region based on the availability and latency1. You can also set the ApplicationRegion property to the region where your application is deployed, and Azure Cosmos DB will automatically populate the PreferredLocations property based on the geo-proximity from that location1.

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

The indexing policy has an includedPaths array that contains only one path: /product/brand/? . This means that only the properties under /product/brand will be indexed. The ? symbol indicates that only scalar values will be indexed, not arrays or objects1.

The excludedPaths array contains a single path: /* . This means that all other properties will be excluded from indexing. The * symbol indicates a wildcard that matches any property name1.

Therefore, the paths /product/category , /product/[ ]/category , and /product/brand/tailspin will not be indexed.

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.

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.

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.

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.

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.