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Describe content sources that can be monitored by MongoDB software

MongoDB software provides a number of different tools for monitoring your deployment. The MongoDB Management Service (MMS) is a fully-managed service that monitors MongoDB instances and applications. MMS offers the following features:

• Automatic detection of new deployments
• Monitoring and alerting for MongoDB instances and applications, including application-level metrics
• Automated failure detection and recovery

Alerting on resource utilization, including CPU and memory usage, disk utilization, network throughput, latency, and more. Alerts can be sent by email or SMS message. You can also configure MMS to generate synthetic transactions against your database to generate alerts when performance degrades. In addition to MMS, you can use third-party tools such as New Relic's MongoDB agent or OpsDash to monitor your deployments. >> Dump C100DEV Collection <<

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Which MongoDB C100DEV Exam objectives are covered in the exam?

The MongoDB C100DEV exam is a new certification for MongoDB developers. It has been developed to help you demonstrate your knowledge of basic MongoDB features and to help you prepare for the more advanced MongoDB Engineer Certification. MongoDB C100DEV Dumps is the best and most effective way to pass your MongoDB Certified Developer 100-Dev certification. The exam will cover: Basic Concepts: These include topics such as installation, configuration, and concepts like the underlying architecture of MongoDB. Core Concepts: Topics include data modeling, documents, indexes, queries, and performance tuning. Advanced Concepts: Advanced topics include sharding and replication across multiple instances of MongoDB.

MongoDB Certified Developer Associate Exam Sample Questions (Q167-Q172):

NEW QUESTION # 167
We have a movies collection with the following document structure: { _id: ObjectId("573a1390f29313caabcd6223"), genres: [ 'Comedy', 'Drama', 'Family' ], title: 'The Poor Little Rich Girl', released: ISODate("1917-03-05T00:00:00.000Z"), year: 1917, imdb: { rating: 6.9, votes: 884, id: 8443 } } We need to use Aggregation Framework to fetch all movies from this collection where 'Drama' is not in genres list and the minimum 'imdb.votes' is at least 100. Additionally, in the projection stage, we want to leave only the following fields: -> title -> genres -> imdb.votes We also want to sort the result set by decreasing imdb votes and limit the number of documents retuned to 5. Example output: [ { imdb: { votes: 1294646 }, genres: [ 'Action', 'Mystery', 'Sci-Fi' ], title: 'Inception' }, { imdb: { votes: 1109724 }, genres: [ 'Adventure', 'Fantasy' ], title: 'The Lord of the Rings: The Fellowship of the Ring' }, { imdb: { votes: 1081144 }, genres: [ 'Adventure', 'Fantasy' ], title: 'The Lord of the Rings: The Return of the King' }, { imdb: { votes: 1080566 }, genres: [ 'Action', 'Sci-Fi' ], title: 'The Matrix' }, { imdb: { votes: 1004805 }, genres: [ 'Action', 'Thriller' ], title: 'The Dark Knight Rises' } ] Which pipeline should you use?

• A. [{ $match: { genres: { $nin: ['Drama'] }, 'imdb.votes': { $gte: 100 } } }, { $project: { _id: 0, title: 1, genres: 1, 'imdb.votes': 1 } }, { $sort: { 'imdb.votes': -1 } }, { $limit: 5 }]
• B. [{ $match: { genres: { $in: ['Drama'] }, 'imdb.votes': { $gte: 100 } } }, { $project: { _id: 0, title: 1, genres: 1, 'imdb.votes': 1 } }, { $sort: { 'imdb.votes': -1 } }, { $limit: 5 }]
• C. [{ $match: { genres: { $nin: ['Drama'] }, 'imdb.votes': { $gte: 100 } } }, { $project: { _id: 0, title: 1, genres: 1, 'imdb.votes': 1 } }, { $sort: { 'imdb.votes': -1 } }]

Answer: A Explanation:
https://docs.mongodb.com/manual/aggregation/
NEW QUESTION # 168
Data modeling. You are considering the use of nesting or the references in your data model. Data read operations must be fast. Which option would be more appropriate?

• A. Use of nesting.
• B. Use of reference.

Answer: A Explanation:
https://docs.mongodb.com/manual/core/data-modeling-introduction/
NEW QUESTION # 169
Which command do you use to display all indexes in routes collection?

• A. db.routes.indexes()
• B. db.routes.dropIndex()
• C. db.routes.dropIndex()
• D. db.routes.getIndexes()

Answer: D Explanation:
https://docs.mongodb.com/manual/reference/method/db.collection.getIndexes/
NEW QUESTION # 170
In your database there is a movies collection with the following document structure: { _id: ObjectId("573a1390f29313caabcd42e8"), genres: [ 'Short', 'Western' ], title: 'The Great Train Robbery', rated: 'TV-G', year: 1903, imdb: { rating: 7.4, votes: 9847, id: 439 }, countries: [ 'USA' ] }, { _id: ObjectId("573a1390f29313caabcd4323"), genres: [ 'Short', 'Drama', 'Fantasy' ], rated: 'UNRATED', title: 'The Land Beyond the Sunset', year: 1912, imdb: { rating: 7.1, votes: 448, id: 488 }, countries: [ 'USA' ] }, { _id: ObjectId("573a1390f29313caabcd446f"), genres: [ 'Short', 'Drama' ], title: 'A Corner in Wheat', rated: 'G', year: 1909, imdb: { rating: 6.6, votes: 1375, id: 832 }, countries: [ 'USA' ] } How can you group these documents to extract the distribution of rated field?

• A. db.movies.aggregate( { $group: { _id: 'rated', count: { $sum: 1 } } } )
• B. db.movies.aggregate( { $group: { _id: '$rated', count: { $sum: 1 } } } )
• C. db.movies.aggregate( { $group: { _id: '$rated', $count: { $sum: 1 } } } )
• D. db.movies.aggregate( { $group: { _id: '$rated', count: { $avg: 1 } } } )

Answer: B Explanation:
https://docs.mongodb.com/manual/reference/method/db.collection.aggregate/
NEW QUESTION # 171
Select all true statements regarding to transactions in MongoDB.

• A. The collections used in a transaction can be in different databases.
• B. We cannot read/write to collections in the config, admin, or local databases.
• C. Transactions are associated with a session.

Answer: A,B,C Explanation:
https://docs.mongodb.com/manual/core/transactions/
NEW QUESTION # 172
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