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

Box 1: No

Four containers with 1000 RU/s each.

Box 2: No

Max 8000 RU/s for db2. 8 containers, so 1000 RU/s for each container.

Box 3: Yes

Max 8000 RU/s for db2. 8 containers, so 1000 RU/s for each container. Can very well add an additional container.

Instead configure an Azure Monitor alert to trigger the function.

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

Box 1: Yes

VM1 is on vnet1.subnet1 which has the Endpoint Status enabled.

Box 2: No

Only virtual network and their subnets added to Azure Cosmos account have access. Their peered VNets cannot access the account until the subnets within peered virtual networks are added to the account.

Box 3: No

Only virtual network and their subnets added to Azure Cosmos account have access.

 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.

 the Azure Cosmos DB integrated cache is an in-memory cache that is built-in to the Azure Cosmos DB dedicated gateway. The dedicated gateway is a front-end compute that stores cached data and routes requests to the backend database. You can choose from a variety of dedicated gateway sizes based on the number of cores and memory needed for your workload1. The integrated cache can reduce the RU consumption and latency of read operations by serving them from the cache instead of the backend containers2.

For your scenario, to ensure that App1 can use the integrated cache, you should perform these two actions:

Change the account endpoint to https://account1.sqlx.cosmos.azure.com . This is the dedicated gateway endpoint that you need to use to connect to your Azure Cosmos DB account and leverage the integrated cache. The standard gateway endpoint (https://account1.documents.azure.com) will not use the integrated cache 2.

Change the consistency level of requests to session. This is the highest consistency level that is supported by the integrated cache. If you use a higher consistency level (such as strong or bounded staleness), your requests will bypass the integrated cache and go directly to the backend containers

C: When triggers are registered, you can specify the operations that it can run with.

F: When executing, pre-triggers are passed in the RequestOptions object by specifying PreTriggerInclude and then passing the name of the trigger in a List object.

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.

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.

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: 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.

You can facilitate aggregate data by using Change Feed and Azure Functions, and then use it for reporting.

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.