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NEW QUESTION: 1
You administer a Microsoft Azure SQL Database database in the US Central region named contosodb. Contosodb runs
on a Standard tier within the SI performance level.
You have multiple business-critical applications that use contosodb.
You need to ensure that you can bring contosodb back online in the event of a natural disaster in the US Central
region. You want to achieve this goal with the least amount of downtime.
Which two actions should you perform? Each correct answer presents part of the solution.
A. Use point in time restore.
B. Use automated Export.
C. Upgrade to S2 performance level.
D. Upgrade to Premium tier.
E. Downgrade to Basic tier.
F. Use active geo-replication.
Answer: D,F
Explanation:
B: The Active Geo-Replication feature implements a mechanism to provide database redundancy within the same
Microsoft Azure region or in different regions (geo-redundancy).
One of the primary benefits of Active Geo-Replication is that it provides a database-level disaster recovery solution.
Using Active Geo-Replication, you can configure a user database in the Premium service tier to replicate transactions
to databases on different Microsoft Azure SQL Database servers within the same or different regions. Cross-region
redundancy enables applications to recover from a permanent loss of a datacenter caused by natural disasters,
catastrophic human errors, or malicious acts.
D: Active Geo-Replication is available for databases in the Premium service tier only.

NEW QUESTION: 2
You have an Azure Stream Analytics query. The query returns a result set that contains 10,000 distinct values for a column named clusterID.
You monitor the Stream Analytics job and discover high latency.
You need to reduce the latency.
Which two actions should you perform? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
A. Convert the query to a reference query.
B. Add a pass-through query.
C. Add a temporal analytic function.
D. Increase the number of streaming units.
E. Scale out the query by using PARTITION BY.
Answer: D,E
Explanation:
Explanation
C: Scaling a Stream Analytics job takes advantage of partitions in the input or output. Partitioning lets you divide data into subsets based on a partition key. A process that consumes the data (such as a Streaming Analytics job) can consume and write different partitions in parallel, which increases throughput.
E: Streaming Units (SUs) represents the computing resources that are allocated to execute a Stream Analytics job. The higher the number of SUs, the more CPU and memory resources are allocated for your job. This capacity lets you focus on the query logic and abstracts the need to manage the hardware to run your Stream Analytics job in a timely manner.
References:
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-parallelization
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-streaming-unit-consumption

NEW QUESTION: 3
Which CLI command applies the candidate configuration to the active configuration?
A. merge
B. copy run start
C. commit
D. load
Answer: B