Cost-Optimized Batch Processing and Data Lifecycle in AWS
Short answer
D Deploy Amazon EC2 On-Demand Instances to run the batch jobs. Store the data in Amazon S3 Standard. Move the data to Amazon S3 Glacier Deep Archive after 30 days. Set an expiration to delete the data after 2 years.
Question
Key Takeaways
The core trap is balancing 'cannot be disrupted' (requiring On-Demand) against 'low cost' (suggesting Spot), while correctly applying S3 lifecycle rules to transition data from Standard to Deep Archive after 30 days.
This question evaluates the selection of cost-optimized EC2 instance types and S3 storage classes for a batch processing workload with specific availability and retention requirements.
Common mistake: Many candidates choose Option B or C, incorrectly selecting Spot Instances despite the 'cannot be disrupted' constraint, or choosing Glacier Instant Retrieval which has a 90-day minimum storage duration, violating the 30-day access window logic.
Expert Analysis
Why the Answer Is Correct
Option D is the correct solution because it aligns with both the reliability and cost constraints. The requirement that batch jobs 'cannot be disrupted' eliminates Spot Instances (Options A and C), as Spot instances can be interrupted by AWS with short notice. Therefore, On-Demand Instances are required. For storage, the data is accessed frequently for the first 30 days, making S3 Standard appropriate. After 30 days, it becomes infrequently accessed and must be retained for 2 years. S3 Glacier Deep Archive offers the lowest storage cost for long-term retention, significantly cheaper than other archival tiers, thus meeting the 'lowest possible cost' objective.
Why the Other Options Are Wrong
Option A and C use Spot Instances, which risk interruption, violating the 'cannot be disrupted' rule. Option B uses S3 Glacier Instant Retrieval, which has a 90-day minimum storage duration; since the data moves out of this tier after 30 days, you would incur additional deletion fees or fail to meet the lifecycle goal efficiently. Additionally, Option B still uses On-Demand, but the storage choice is suboptimal compared to Deep Archive for 2-year retention.
Community Comment Notes
Community consensus strongly favors D, with several users highlighting the critical distinction between job disruption risks and storage costs. User 'FlyingHawk' noted that Spot instances are out due to disruption risks and pointed out the 90-day minimum for Glacier Instant Retrieval makes B incorrect. User 'nebajp' succinctly summarized the logic: On-Demand for non-disruptable jobs and Deep Archive for long-term low-cost retention.
Official Reference
https://aws.amazon.com/ec2/pricing/
This link opens the official vendor documentation in a new tab.
Exam Strategy
Always prioritize the 'cannot be disrupted' keyword when choosing between On-Demand and Spot Instances; if stability is mandatory, Spot is never the answer. For long-term archival storage spanning years, always consider S3 Glacier Deep Archive as the default low-cost candidate unless retrieval speed is critical within minutes.
Frequently Asked Questions
Why not use Spot Instances to save money on compute?
Why is S3 Glacier Deep Archive better than Glacier Instant Retrieval here?
Community Votes
81% of anonymous learners picked answer D. Votes are pick records left by other test-takers — they are not the verified answer.
Discussion 10 contributions
Compiled from public community threads and reader submissions, lightly edited for clarity. Handles and vote tallies are shown as recorded, and comments reflect the views of individual contributors.
From public community threads 10
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nebajp 👍 9 Answered DD is the correct answer for 30 days - use Amazon S3 standard 2 years Retaining - Glacier Deep Archive Can not be Disrupted - On-Demand Instances
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flaviobrf 👍 5 Answered DI understand that D is the right anwser
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SR0312 👍 5 Answered BJob cannot be disrupted - On demand
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EllenLiu 👍 3 Answered DI am always confused about the choice between s3 standard and s3 glacier instant... short period of storage + frequently retrieve ==> s3 standard long period of storage + infrequently retrieve ==> s3 glacier instant s3 standard: $0.023 per GB for storage / $0.0004 get, select per 1000 request s3 glacier instant: $0.004 per GB for storage /$0.01 get, select per 1000 request https://aws.amazon.com/s3/pricing/?nc=sn&loc=4
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Anyio 👍 2 Answered DThe correct answer is D. Deploy Amazon EC2 On-Demand Instances to run the batch jobs. Store the data in Amazon S3 Standard. Move the data to Amazon S3 Glacier Deep Archive after 30 days. Set an expiration to delete the data after 2 years. Explanation: Option D: Correct. Since the batch jobs cannot be disrupted, using Amazon EC2 On-Demand Instances ensures the application runs without interruption. Initially storing data in Amazon S3 Standard allows for access during the 30-day period post-processing. Moving the data to Amazon S3 Glacier Deep Archive after 30 days optimizes storage costs for long-term retention of up to 2 years, the lowest cost for infrequent access. Setting an expiration ensures the data is deleted after 2 years, controlling costs and data lifecycle management.
Show 5 more comments
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FlyingHawk 👍 2 Answered D1. The short-lived batch jobs cannot be disrupted -> on demand. A and C are out 2. The data is accessed for 30 days and retained for 2 years. means S3 Standard (30 days) -> S3 Glacier -> expire. S3 Glicer instant Retrieval has a minimum storage for 90 days, so B is out.
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LeonSauveterre 👍 2 Answered DB - Amazon S3 Glacier Instant Retrieval is an archive storage class that delivers the lowest-cost storage for long-lived data that is rarely accessed and requires retrieval in milliseconds. So this is wrong because "The data is accessed for 30 days".
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spoved 👍 1 Answered Bhttps://aws.amazon.com/about-aws/whats-new/2021/11/amazon-s3-glacier-instant-retrieval-storage-class/ - The easiest way to store data in S3 Glacier Instant Retrieval is to use the S3 PUT API to upload data directly, or use S3 Lifecycle to transition data from the S3 Standard and S3 Standard-IA storage classes. - The company wants to keep the cost of running the application in the AWS Cloud as low as possible => B
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pujithacg8 👍 2D is correct
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siheom 👍 1 Answered CI VOTE C
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