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NEW QUESTION: 1
同じサブスクリプション内の10台のAzure仮想マシンで実行される5つの.NET Coreアプリケーションがあります。
アプリケーションが同じAzure Active Directory（Azure AD）IDを使用して認証できるようにするためのソリューションを推奨する必要があります。ソリューションは以下の要件を満たす必要があります。
* アプリケーションが10台の仮想マシンで実行されている場合にのみ認証できることを確認してください。
* 管理作業を最小限に抑えます。
あなたは推薦に何を含めるべきですか？回答するには、回答領域で適切なオプションを選択します。
注：それぞれ正しい選択は1ポイントの価値があります。

Answer:
Explanation:

Explanation

NEW QUESTION: 2
For this question, refer to the TerramEarth case study. To be compliant with European GDPR regulation, TerramEarth is required to delete data generated from its European customers after a period of 36 months when it contains personal data. In the new architecture, this data will be stored in both Cloud Storage and BigQuery. What should you do?
A. Create a BigQuery table for the European data, and set the table retention period to 36 months. For Cloud Storage, use gsutil to enable lifecycle management using a DELETE action with an Age condition of 36 months.
B. Create a BigQuery table for the European data, and set the table retention period to 36 months. For Cloud Storage, use gsutil to create a SetStorageClass to NONE action when with an Age condition of 36 months.
C. Create a BigQuery time-partitioned table for the European data, and set the partition expiration period to
36 months. For Cloud Storage, use gsutil to enable lifecycle management using a DELETE action with an Age condition of 36 months.
D. Create a BigQuery time-partitioned table for the European data, and set the partition period to 36 months. For Cloud Storage, use gsutil to create a SetStorageClass to NONE action with an Age condition of 36 months.
Answer: C
Explanation:
Topic 6, Mountkrik Games Case 2
Company Overview
Mountkirk Games makes online, session-based, multiplayer games for mobile platforms. They build all of their games using some server-side integration. Historically, they have used cloud providers to lease physical servers.
Due to the unexpected popularity of some of their games, they have had problems scaling their global audience, application servers, MySQL databases, and analytics tools.
Their current model is to write game statistics to files and send them through an ETL tool that loads them into a centralized MySQL database for reporting.
Solution Concept
Mountkirk Games is building a new game, which they expect to be very popular. They plan to deploy the game's backend on Google Compute Engine so they can capture streaming metrics, run intensive analytics, and take advantage of its autoscaling server environment and integrate with a managed NoSQL database.
Business Requirements
* Increase to a global footprint.
* Improve uptime - downtime is loss of players.
* Increase efficiency of the cloud resources we use.
* Reduce latency to all customers.
Technical Requirements
Requirements for Game Backend Platform
* Dynamically scale up or down based on game activity.
* Connect to a transactional database service to manage user profiles and game state.
* Store game activity in a timeseries database service for future analysis.
* As the system scales, ensure that data is not lost due to processing backlogs.
* Run hardened Linux distro.
Requirements for Game Analytics Platform
* Dynamically scale up or down based on game activity
* Process incoming data on the fly directly from the game servers
* Process data that arrives late because of slow mobile networks
* Allow queries to access at least 10 TB of historical data
* Process files that are regularly uploaded by users' mobile devices
Executive Statement
Our last successful game did not scale well with our previous cloud provider, resulting in lower user adoption and affecting the game's reputation. Our investors want more key performance indicators (KPIs) to evaluate the speed and stability of the game, as well as other metrics that provide deeper insight into usage patterns so we can adapt the game to target users. Additionally, our current technology stack cannot provide the scale we need, so we want to replace MySQL and move to an environment that provides autoscaling, low latency load balancing, and frees us up from managing physical servers.

NEW QUESTION: 3



A. reviewID
B. comment
C. starRating
D. productID
Answer: D
Explanation:
Explanation
Refer AWS documentation - DynamoDB Design partition key
The partition key portion of a table s primary key determines the logical partitions in which a table's data is stored. This in turn affects the underlying physical partitions. Provisioned I/O capacity for the table is divided evenly among these physical partitions. Therefore a partition key design that doesn't distribute I/O requests evenly can create "hot" partitions that result in throttling and use your provisioned I/O capacity inefficiently.
The optimal usage of a table's provisioned throughput depends not only on the workload patterns of individual items, but also on the partition-key design. This doesn't mean that you must access all partition key values to achieve an efficient throughput level, or even that the percentage of accessed partition key values must be high. It does mean that the more distinct partition key values that your workload accesses, the more those requests will be spread across the partitioned space. In general, you will use your provisioned throughput more efficiently as the ratio of partition key values accessed to the total number of partition key values increases.

NEW QUESTION: 4
Given the code fragment:
Stream<Path> files = Files.walk(Paths.get(System.getProperty("user.home"))); files.forEach (fName -> { //line n1 try { Path aPath = fName.toAbsolutePath(); //line n2 System.out.println(fName + ":"
+ Files.readAttributes(aPath,
Basic.File.Attributes.class).creationTime
());
} catch (IOException ex) {
ex.printStackTrace();
});
What is the result?
A. All files and directories under the home directory are listed along with their attributes.
B. A compilation error occurs at line n1.
C. A compilation error occurs at line n2.
D. The files in the home directory are listed along with their attributes.
Answer: A