You are troubleshooting the current issues caused by the application updates.
Which action can address the application updates issue without affecting the functionality of the application?
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.
You need to select the partition key for con-iot1. The solution must meet the IoT telemetry requirements.
What should you select?
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.
You need to identify which connectivity mode to use when implementing App2. The solution must support the planned changes and meet the business requirements.
Which connectivity mode should you identify?
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.
You configure multi-region writes for account1.
You need to ensure that App1 supports the new configuration for account1. The solution must meet the business requirements and the product catalog requirements.
What should you do?
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.
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.
You have a container named container1 in an Azure Cosmos DB Core (SQL) API account. Upserts of items in container1 occur every three seconds.
You have an Azure Functions app named function1 that is supposed to run whenever items are inserted or replaced in container1.
You discover that function1 runs, but not on every upsert.
You need to ensure that function1 processes each upsert within one second of the upsert.
Which property should you change in the Function.json file of function1?
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.
A: checkpointInterval: When set, it defines, in milliseconds, the interval between lease checkpoints. Default is always after each Function call.
C: maxItemsPerInvocation: When set, this property sets the maximum number of items received per Function call. If operations in the monitored collection are performed through stored procedures, transaction scope is preserved when reading items from the change feed. As a result, the number of items received could be higher than the specified value so that the items changed by the same transaction are returned as part of one atomic batch.