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| Section | Weight | Objectives |
|---|---|---|
| Sharding and Scalability | 10% | - Shard keys, chunk management, balancing - Query routing and cluster operations - Sharded cluster architecture |
| Backup, Recovery and Maintenance | 10% | - Restore procedures and disaster recovery - Logical and physical backup methods - Data consistency and integrity checks |
| Replication and High Availability | 15% | - Deployment and maintenance of replica sets - Replica set architecture and components - Failover, elections, read/write concern |
| MongoDB Architecture and Deployment | 20% | - Core concepts, JSON/BSON, data model - Installation and configuration - Storage engines and server management |
| Monitoring, Performance and Troubleshooting | 10% | - Diagnostics and resolving common issues - Performance tuning and optimization - Monitoring tools and metrics |
| CRUD Operations and Indexing | 20% | - Create, Read, Update, Delete operations - Index types, creation, and management - Query optimization and aggregation |
| Security and Access Control | 15% | - Role-based access control - Encryption, auditing, and security best practices - Authentication mechanisms |
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NEW QUESTION # 83
Which TWO indicators should an administrator keep an eye on to determine if the storage capacity is nearing its limit?
Answer: B,D
Explanation:
The most direct evidence that storage capacity is approaching exhaustion is high filesystem utilization and explicit operating-system errors showing that no space remains. Sustained disk utilization above 90% is a practical warning threshold because the deployment has little headroom for database growth, index builds, temporary files, journal activity, or operational spikes. The errno:28 No space left on device message is even stronger evidence: the operating system rejected a write because the relevant filesystem could not allocate additional space. The other choices can correlate with workload growth but do not specifically prove a capacity problem. Query execution time can increase because of poor indexes, cache misses, lock or ticket contention, or CPU pressure. A rising document count says nothing about remaining free space without knowing document size, index size, and volume capacity. Low read/write ticket availability reflects storage- engine concurrency pressure rather than filesystem capacity. Administrators should therefore monitor disk- used and disk-free metrics, alert well before full utilization, and investigate any ENOSPC-style log events immediately. B and D are the two storage-capacity indicators.
Study Guide reference/topic:Performance Monitoring and Tuning - disk capacity, storage metrics, alerts, and diagnostic logs.
NEW QUESTION # 84
Which of the following aggregate commands in MongoDB uses a pipeline approach with the goals of improving the aggregation performance?
Answer: D
NEW QUESTION # 85
A MongoDB collection named users contains sample documents with fields including name, age, address, description, city, and occupation.
The administrator uses the following query to perform a collection scan:
db.users.find({ city: " New York " , occupation: " Software Engineer " }) What compound index will improve the performance of the query the MOST?
Answer: A,C
Explanation:
The query contains equality predicates on both city and occupation, so an efficient compound index should contain both fields. Options A and C include only one query predicate plus the unrelated name field, forcing MongoDB to perform additional filtering that the index cannot resolve. Options B and D both contain the complete predicate set. For a query consisting entirely of equality predicates, MongoDB does not require those equality keys to appear in a particular order relative to one another for the query itself; { city: 1, occupation: 1 } and { occupation: 1, city: 1 } can both support the two equality conditions effectively. The original question appears to expect B because it mirrors the field order used in the query, but that distinction is not technically required under MongoDB ' s equality-key guidance. Field order becomes much more significant when the workload also needs a particular index prefix, sort order, range predicate, or when one ordering better supports additional common queries. Accordingly, the technically accurate review result is B and D, with B being the likely intended exam choice.
Study Guide reference/topic:Indexing and Query Optimization - compound indexes, equality predicates, and index key ordering.
NEW QUESTION # 86
Which of the following commands will return all the posts with number of likes greater than 100 and less than 200, both inclusive?
Answer: A
NEW QUESTION # 87
A MongoDB administrator is currently managing a single node MongoDB Enterprise deployment. The administrator is considering setting up replication with a secondary node and a delayed member.
Which TWO reasons align to the objectives of the administrator?
Answer: D,E
Explanation:
Adding replica-set members addresses availability and recovery objectives. A normal secondary maintains a replicated copy of the primary ' s data and can be elected primary if the current primary becomes unavailable, thereby improving service availability compared with a single-node deployment. That directly supports option D: A delayed member intentionally applies oplog entries later than the primary, preserving an older logical state of the dataset for a configured delay period. This can help recover from operator mistakes such as an accidental destructive update or drop operation because the administrator may be able to access the delayed copy before the damaging operation is applied there. That supports option A. A delayed member is not a substitute for long-term archival or a formal backup-retention policy; its recoverable history is constrained by the delay configuration and oplog window, so B is not the intended objective. Option C describes sharding, which partitions data across shards rather than simply replicating it. Encryption at rest is configured independently and is unrelated to adding secondaries or delayed members. Therefore, A and D are the two reasons that align with the proposed replication design.
Study Guide reference/topic:Cluster Reliability and Data Resilience - replica sets, delayed members, failover, and operator-error recovery.
NEW QUESTION # 88
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