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NEW QUESTION: 1
You are building a continuous deployment pipeline for a project stored in a Git source repository and want to ensure that code changes can be verified deploying to production. What should you do?
A. Use Spinnaker to deploy builds to production and run tests on production deployments.
B. Use Jenkins to build the staging branches and the master branch. Build and deploy changes to production for 10% of users before doing a complete rollout.
C. Use Jenkins to monitor tags in the repository. Deploy staging tags to a staging environment for testing.
After testing, tag the repository for production and deploy that to the production environment.
D. Use Spinnaker to deploy builds to production using the red/black deployment strategy so that changes can easily be rolled back.
Answer: B
NEW QUESTION: 2
public class country {
public enum Continent {ASIA, EUROPE}
String name;
Continent region;
public Country (String na, Continent reg) {
name = na, region = reg;
}
public String getName () {return name;}
public Continent getRegion () {return region;}
}
List<Country> couList = Arrays.asList (
new Country ("Japan", Country.Continent.ASIA),
new Country ("Italy", Country.Continent.EUROPE),
new Country ("Germany", Country.Continent.EUROPE));
Map<Country.Continent, List<String>> regionNames = couList.stream ()
.collect(Collectors.groupingBy (Country ::getRegion,
Collectors.mapping(Country::getName, Collectors.toList()))));
System.out.println(regionNames);
A. {ASIA = [Japan], EUROPE = [Italy, Germany]}
B. {EUROPE = [Germany], EUROPE = [Italy], ASIA = [Japan]}
C. {EUROPE = [Germany, Italy], ASIA = [Japan]}
D. {EUROPE = [Italy, Germany], ASIA = [Japan]}
Answer: A
NEW QUESTION: 3
Azure Machine Learning Studioを使用して、大規模なデータストアからデータを取得しています。
システムクロックに基づいたランダムサンプリングシードを使用して、テスト目的でデータのサブセットを作成する必要があります。
パーティションとサンプルモジュールを実験に追加します。
モジュールのプロパティを選択する必要があります。
どの値を選択する必要がありますか？回答するには、回答エリアで適切なオプションを選択します。
注：それぞれの正しい選択には1ポイントの価値があります。
Answer:
Explanation:
Explanation
Box 1: Sampling
Create a sample of data
This option supports simple random sampling or stratified random sampling. This is useful if you want to create a smaller representative sample dataset for testing.
1. Add the Partition and Sample module to your experiment in Studio, and connect the dataset.
2. Partition or sample mode: Set this to Sampling.
3. Rate of sampling. See box 2 below.
Box 2: 0
3. Rate of sampling. Random seed for sampling: Optionally, type an integer to use as a seed value.
This option is important if you want the rows to be divided the same way every time. The default value is 0, meaning that a starting seed is generated based on the system clock. This can lead to slightly different results each time you run the experiment.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/partition-and-sample
NEW QUESTION: 4
Ihr Netzwerk enthält eine Active Directory-Gesamtstruktur mit dem Namen contoso.com, die mit Microsoft Azure Active Directory (Azure AD) synchronisiert wird.
Sie verwenden Microsoft System Center Configuration Manager (Aktueller Zweig) für die Geräteverwaltung.
Sie haben die in der folgenden Tabelle aufgeführten Windows 10-Geräte.
Sie konfigurieren die Configuration Manager-Ko-Verwaltung wie folgt:
Automatische Registrierung in Intune: Pilot
Pilotensammlung: Collection2
Sie konfigurieren Co-Management-Workloads wie in der folgenden Abbildung gezeigt.
Wählen Sie für jede der folgenden Anweisungen Ja aus, wenn die Anweisung wahr ist. Andernfalls wählen Sie Nein.
HINWEIS: Jede richtige Auswahl ist einen Punkt wert.
Answer:
Explanation:
Explanation
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Feedbacks
Aalk - 2014-05-05 16:45:18
Plato - 2014-05-05 16:45:51
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Eleanore - 2014-09-28 16:36:48