Microsoft DP-420 Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB Exam Practice Test

Box 1: country

The country field is filterable.

Note: filterable: Indicates whether to enable the field to be referenced in $filter queries. Filterable differs from searchable in how strings are handled. Fields of type Edm.String or Collection(Edm.String) that are filterable do not undergo lexical analysis, so comparisons are for exact matches only.

Box 2: name

The name field is not Retrievable.

Retrievable: Indicates whether the field can be returned in a search result. Set this attribute to false if you want to use a field (for example, margin) as a filter, sorting, or scoring mechanism but do not want the field to be visible to the end user.

Note: searchable: Indicates whether the field is full-text searchable and can be referenced in search queries.

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.

Migrate

40000

According to the Azure CLI reference1, you need to use the az cosmosdb sql database throughput migrate command to migrate the throughput of the SQL database between autoscale and manually provisioned. You also need to use the --throughput-type parameter to specify the type of throughput to migrate to, and the --max-throughput parameter to specify the maximum throughput resource can scale to (RU/s).

To complete the CLI statements, you should replace the missing values with:

• --throughput-type autoscale
• --max-throughput 40000

The final command should look like this:

az cosmosdb sql database throughput migrate \

--account-name account1 \

--name db1 \

--resource-group rg1 \

--throughput-type autoscale \

--max-throughput 40000

Box 1: No

Each physical partition should have its own index, but since no index is used, the query is not cross-partition.

Box 2: No

Index utilization is 0% and Index Look up time is also zero.

Box 3: Yes

A partition key index will be created, and the query will perform across the partitions.

If a query has a filter with two or more properties, adding a composite index will improve performance.

Consider the following query:

SELECT * FROM c WHERE c.name = “Tim” and c.age > 18

In the absence of a composite index on (name ASC, and age ASC), we will utilize a range index for this query. We can improve the efficiency of this query by creating a composite index for name and age.

Queries with multiple equality filters and a maximum of one range filter (such as >,<, <=, >=, !=) will utilize the composite index.

Because the integrated cache is specific to your Azure Cosmos DB account and requires significant CPU and memory, it requires a dedicated gateway node. Connect to Azure Cosmos DB using gateway mode.

When DefaultTimeToLive is -1 then your Time to Live setting is On (No default)

Time to Live on a container, if present and the value is set to "-1", it is equal to infinity, and items don’t expire by default.

Time to Live on an item:

This Property is applicable only if DefaultTimeToLive is present and it is not set to null for the parent container.

If present, it overrides the DefaultTimeToLive value of the parent container.

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.

With an upsert operation we can either insert or update an existing record at the same time.

FeedPollDelay: The time (in milliseconds) for the delay between polling a partition for new changes on the feed, after all current changes are drained. Default is 5,000 milliseconds, or 5 seconds.

Azure Monitor is a service that provides comprehensive monitoring for Azure resources, including Azure Cosmos DB. You can use Azure Monitor to collect, analyze, and alert on metrics and logs from your Azure Cosmos DB account. You can create alerts for Azure Cosmos DB using Azure Monitor based on the metrics, activity log events, or Log Analytics logs on your account1.

For your scenario, if you want to receive an alert when requests that target the database exceed the available request units per second (RU/s), you should use the Document Quota metric. This metric measures the percentage of RU/s consumed by your account or container. You can create an alert rule on this metric from the Azure portal by following these steps2:

• In the Azure portal, select the Azure Cosmos DB account you want to monitor.
• Under the Monitoring section of the sidebar, select Alerts, and then select New alert rule.
• In the Create alert rule pane, fill out the Scope section by selecting your subscription name and resource type (Azure Cosmos DB accounts).
• In the Condition section, select Add condition and choose Document Quota from the list of signals.
• In the Configure signal logic pane, specify the threshold value and operator for your alert condition. For example, you can choose Greater than or equal to 90 as the threshold value and operator to receive an alert when your RU/s consumption reaches 90% or more of your provisioned throughput.
• In the Alert rule details section, specify a name and description for your alert rule.
• In the Actions section, select Add action group and choose how you want to receive notifications for your alert. For example, you can choose Email/SMS/Push/Voice as an action type and enter your email address or phone number as a receiver.
• Review your alert rule settings and select Create alert rule to save it.

The solution is incorrect because there is no "isTom" parameter in the Azure Cosmos DB SDK. The correct parameter is "isTombstone".

The following are the operation names in diagnostic logs for different operations:

RegionAddStart, RegionAddComplete

RegionRemoveStart, RegionRemoveComplete

AccountDeleteStart, AccountDeleteComplete

RegionFailoverStart, RegionFailoverComplete

AccountCreateStart, AccountCreateComplete

*AccountUpdateStart*, AccountUpdateComplete

VirtualNetworkDeleteStart, VirtualNetworkDeleteComplete

DiagnosticLogUpdateStart, DiagnosticLogUpdateComplete

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.

C: Avro is binary format, while JSON is text.

F: Kafka Connect for Azure Cosmos DB is a connector to read from and write data to Azure Cosmos DB. The Azure Cosmos DB sink connector allows you to export data from Apache Kafka topics to an Azure Cosmos DB database. The connector polls data from Kafka to write to containers in the database based on the topics subscription.

D: Create the Azure Cosmos DB sink connector in Kafka Connect. The following JSON body defines config for the sink connector.

Extract:

"connector.class": "com.azure.cosmos.kafka.connect.sink.CosmosDBSinkConnector",

"key.converter": "org.apache.kafka.connect.json.AvroConverter"

"connect.cosmos.containers.topicmap": "hotels#kafka"

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.

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.