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AWS DVA-C02 Drill: S3 Storage Classes - Balancing Retrieval Speed with Cost

Jeff Taakey
Author
Jeff Taakey
21+ Year Enterprise Architect | AWS SAA/SAP & Multi-Cloud Expert.

Jeff’s Note
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Unlike generic exam dumps, ADH analyzes this scenario through the lens of a Real-World Lead Developer.

For DVA-C02 candidates, the confusion often lies in quick retrieval vs. archival cost optimization for object storage. In production, this is about knowing exactly which S3 storage class supports millisecond retrievals while minimizing costs over long retention periods. Let’s drill down.

The Certification Drill (Simulated Question)
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Scenario
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A dynamic media startup named PixelStream is deploying a video processing application on Amazon EC2 instances. The application generates large video clip files (several GBs daily). These files are infrequently accessed but must be available to users within minutes whenever requested during the first 12 months of storage. PixelStream is required to retain these files for 7 years due to compliance reasons.

The Requirement:
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Determine the most cost-effective, operationally simple solution to store these generated files so that initial 12-month retrievals are near-instantaneous, while ensuring long-term archival for 7 years.

The Options
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  • A) Store files in an Amazon S3 bucket using the S3 Glacier Instant Retrieval storage class. Use an S3 Lifecycle policy to transition the files to S3 Glacier Deep Archive after 1 year.
  • B) Store files in an Amazon S3 bucket using the S3 Standard storage class. Use an S3 Lifecycle policy to transition the files to S3 Glacier Flexible Retrieval after 1 year.
  • C) Store the files on an Amazon Elastic Block Store (EBS) volume. Use Amazon Data Lifecycle Manager (DLM) to create snapshots and store them in S3.
  • D) Store the files on an Amazon Elastic File System (EFS) mount. Enable EFS lifecycle management to transition files to EFS Standard-Infrequent Access (Standard-IA) after 1 year.

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Correct Answer
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A

Quick Insight: The Developer Imperative
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The fastest retrieval within minutes after upload combined with very low access frequency fits the S3 Glacier Instant Retrieval tier perfectly for year 1. Transitioning to Glacier Deep Archive after that minimizes cost over the remaining 6 years. Other options either have slower retrievals, higher costs, or are operationally complex.

Content Locked: The Expert Analysis
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You’ve identified the answer. But do you know the implementation details that separate a Junior from a Senior?


The Expert’s Analysis
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Correct Answer
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Option A

The Winning Logic
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Storing files initially in S3 Glacier Instant Retrieval meets the critical requirement of near-immediate file availability (milliseconds retrievals) during the first year, despite infrequent access. After 1 year, lifecycle transitioning to S3 Glacier Deep Archive ensures minimal long-term storage costs for the remaining 6 years, balancing compliance and cost-effectiveness.

  • S3 Glacier Instant Retrieval is designed for rarely accessed data that still requires immediate retrieval. Its retrieval times are typically milliseconds, which fits the “available within minutes” constraint without incurring the longer multi-hour delays of Glacier Flexible Retrieval or Deep Archive.
  • The lifecycle policy automates transitioning data to cheaper but slower storage after 1 year, meeting retention and cost goals.
  • EBS volumes (Option C) and EFS (Option D) are generally far more expensive at scale for long-term archival and do not offer integrated lifecycle policies to Glacier tiers.
  • S3 Standard (Option B) keeps data readily available but at significantly higher cost during year 1, and Glacier Flexible Retrieval does not provide instant or millisecond retrieval, instead offering minutes to hours, risking user experience degradation.

The Technical Blueprint
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# Example lifecycle policy JSON to transition objects after 1 year
aws s3api put-bucket-lifecycle-configuration --bucket pixelstream-videos \
--lifecycle-configuration '{
  "Rules": [
    {
      "ID": "GlacierInstantThenDeepArchive",
      "Filter": {},
      "Status": "Enabled",
      "Transitions": [
        {
          "Days": 0,
          "StorageClass": "GLACIER_INSTANT_RETRIEVAL"
        },
        {
          "Days": 365,
          "StorageClass": "DEEP_ARCHIVE"
        }
      ],
      "NoncurrentVersionTransitions": [],
      "AbortIncompleteMultipartUpload": {
        "DaysAfterInitiation": 7
      }
    }
  ]
}'

The Comparative Analysis
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Option API Complexity Performance Use Case
A Medium (Lifecycle policies + Glacier Instant Retrieval API) Millisecond retrievals in year 1 + minimal cost year 2-7 Ideal for archival with occasional fast access early on
B Low (Standard + Lifecycle) Millisecond retrieval year 1, minutes-hours retrieval year 2-7 Higher cost, slower retrieval after transition
C High (EBS + DLM snapshots) Instant access, high cost and complexity Unsuitable for long-term archival at scale
D Medium (EFS + lifecycle) Instant access year 1, infrequent access tier reduces cost moderately Expensive, not optimized for archival of large infrequently accessed data

Real-World Application (Practitioner Insight)
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Exam Rule
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“For the exam, always pick S3 Glacier Instant Retrieval when you see a requirement for rarely accessed data needing immediate availability.”

Real World
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“In real production environments, we might add caching layers or indexing services on top if user requests demand complex search or partial retrievals—but for pure file storage with access time constraints, the above remains optimal.”


(CTA) Stop Guessing, Start Mastering
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Disclaimer

This is a study note based on simulated scenarios for the DVA-C02 exam.

The DevPro Network: Mission and Founder

A 21-Year Tech Leadership Journey

Jeff Taakey has driven complex systems for over two decades, serving in pivotal roles as an Architect, Technical Director, and startup Co-founder/CTO.

He holds both an MBA degree and a Computer Science Master's degree from an English-speaking university in Hong Kong. His expertise is further backed by multiple international certifications including TOGAF, PMP, ITIL, and AWS SAA.

His experience spans diverse sectors and includes leading large, multidisciplinary teams (up to 86 people). He has also served as a Development Team Lead while cooperating with global teams spanning North America, Europe, and Asia-Pacific. He has spearheaded the design of an industry cloud platform. This work was often conducted within global Fortune 500 environments like IBM, Citi and Panasonic.

Following a recent Master’s degree from an English-speaking university in Hong Kong, he launched this platform to share advanced, practical technical knowledge with the global developer community.


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