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Zorluk: OrtaDatabase and Storage Strategy

A smart utility provider is designing a new IoT monitoring platform to ingest and store metrics from 10 million10 \text{ million} smart meters globally. The system requirements include:
- High-throughput write ingestion of telemetry data (each write payload is approximately 500 bytes500 \text{ bytes}) with sub-second response times.
- Aggregated daily telemetry summaries that must be retained for audit purposes, where they are queried occasionally but must be highly durable and cost-effective.

Which two database and storage strategies should the solutions architect choose to meet these requirements? (Select TWO.)

  1. Deploy Amazon DynamoDB with auto-scaling to ingest the real-time telemetry writes, utilizing its partition-based horizontal scalability.Cevap
  2. Store the aggregated daily summaries in Amazon S3, using S3 Lifecycle policies to transition objects to S3 Standard-Infrequent Access after 30 days to optimize storage costs.Cevap
  3. C
    Provision an Amazon Aurora PostgreSQL Global Database with multiple reader instances to ingest the primary telemetry write traffic across multiple AWS Regions.
  4. D
    Deploy a single-AZ Amazon RDS for MySQL instance with a cross-Region Read Replica to achieve a near-zero RPO and RTO for telemetry writes during a disaster recovery event.
  5. E
    Encrypt the telemetry data client-side before storage using the AWS-managed KMS key for Amazon S3 shared across separate logging and processing accounts.

Cevap

Deploy Amazon DynamoDB with auto-scaling to ingest the real-time telemetry writes, and store the aggregated daily summaries in Amazon S3 with S3 Lifecycle policies to transition objects to Amazon S3 Standard-Infrequent Access after 30 days.
For the high-throughput write workload, Amazon DynamoDB is the correct option because it scales partition capacity horizontally and delivers single-digit millisecond latency. For the aggregated daily reports, storing files in Amazon S3 and using S3 Lifecycle policies to transition objects to S3 Standard-Infrequent Access after 30 days meets the durability, compliance, and cost-efficiency requirements.

Adım Adım Çözüm

1
Analyze write ingestion requirements.
Identified high-throughput, low-latency, small-payload writes (500 bytes500 \text{ bytes}) from 10 million10 \text{ million} devices, pointing to a key-value NoSQL database.
DynamoDB scales horizontally and handles high-frequency writes with sub-second latencies.
2
Analyze data archival and auditing requirements.
Identified aggregated daily summaries requiring high durability, cost efficiency, and occasional query support.
Amazon S3 provides 99.999999999%99.999999999\% durability. Utilizing S3 Standard-IA for data older than 30 days lowers storage costs while maintaining millisecond retrieval times.
3
Evaluate and rule out multi-Region write solutions that violate core services limits.
Disqualified Aurora read replicas for scaling writes and cross-account AWS-managed KMS key sharing.
Aurora Global Database only permits writes to the primary writer instance, and AWS-managed KMS keys cannot be shared cross-account.

Anahtar Kavram

Selecting the optimal AWS database and storage service based on access patterns, write scaling requirements, and cross-account access limitations.
Tahmini Süre:2m 0s
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Database and Storage Strategy

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