Microsoft DP-420 Dumps

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 optimize the data store for reading data, 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 design that you could implement is B. In a company container, create a document for each company. Embed the users into company documents. Use the company ID as the partition key.

This design has the following advantages:

• It stores companies and users as self-contained documents that can be easily retrieved by company ID1.
• It avoids storing redundant data or creating additional containers for users1.
• It allows you to browse by company and browse the users by company with simple queries1.
• It shows a details page for the company and all the related users by fetching a single document1.
• It leverages the benefits of embedding data, such as reducing the number of requests, improving query performance, and simplifying data consistency2.

This design also has some limitations, such as:

• It may not be suitable for some users who 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 users need to be associated with more than one company or queried independently from companies2.
• It may not be scalable for companies that have more than 1,000 users, as it could result in hot partitions or throttling2.

Depending on your specific use case and requirements, you may need to adjust this design 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.

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 and cannot 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.

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: incorrect connection URLs

400 Bad Request: Returned when there is an error in the request URI, headers, or body. The response body will contain an error message explaining what the specific problem is.

The HyperText Transfer Protocol (HTTP) 400 Bad Request response status code indicates that the server cannot or will not process the request due to something that is perceived to be a client error (for example, malformed request syntax, invalid request message framing, or deceptive request routing).

Box 2: 6 thousand

201 Created: Success on PUT or POST. Object created or updated successfully.

Note:

200 OK: Success on GET, PUT, or POST. Returned for a successful response.

404 Not Found: Returned when a resource does not exist on the server. If you are managing or querying an index, check the syntax and verify the index name is specified correctly.

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New and updated orders will be added to contoso-erp.orders: Yes

The code performs bulk data ingestion from contoso-app: No

Both contoso-app and contoso-erp have Analytics store enabled: Yes

The code uses the spark.readStream method to read data from a container named orders in a database named contoso-app. The data is then filtered by a condition and written to another container named orders in a database named contoso-erp using the spark.writeStream method. The write mode is set to “append”, which means that new and updated orders will be added to the destination container1.

The code does not perform bulk data ingestion from contoso-app, but rather stream processing. Bulk data ingestion is a process of loading large amounts of data into a data store in batches. Stream processing is a process of continuously processing data as it arrives in real-time2.

Both contoso-app and contoso-erp have Analytics store enabled, because they are both accessed by Spark pools using the spark.cosmos.oltp method. This method requires that the containers have Analytics store enabled, which is a feature that allows Spark pools to query data stored in Azure Cosmos DB containers using SQL APIs3.

Box 1 = The request level options

Azure Cosmos DB offers five well-defined consistency levels: strong, bounded staleness, session, consistent prefix and eventual. You can configure the default consistency level on your Azure Cosmos DB account at any time2. The default consistency level applies to all databases and containers under that account1. You can also override the default consistency level for a specific request by using the request options2.

Box 2 = The request level options

To modify the consistency level of a read operation in Azure Cosmos DB, you can use request-level options to override the account's default consistency setting. Therefore, to ensure that the read operations of App1 can request either consistent prefix or session consistency, you need to modify the request-level options for each operation. Reference: -

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.

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

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.

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.

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.