The correct answer is to store data in S3 with lifecycle policies to transition between storage classes, and use Amazon Athena for queries. This solution is cost-effective because S3 lifecycle policies automatically move data from frequently accessed tiers like S3 Standard to lower-cost classes such as S3 Glacier Deep Archive as it ages, ensuring that a petabyte data lake remains affordable while retaining all data. Athena then enables serverless SQL queries directly on the data in place, eliminating the need for data movement or provisioning compute resources. On the AWS Certified Solutions Architect Professional SAP-C02 exam, this scenario tests your understanding of building a cost-optimized, queryable data lake without unnecessary infrastructure—a common trap is choosing Redshift for structured warehousing or EMR for heavy processing, both of which add cost and complexity for occasional queries. Remember the memory tip: "Lifecycle for cost, Athena for query—no clusters, no restore."
SAP-C02 Design for New Solutions Practice Question
This SAP-C02 practice question tests your understanding of design for new solutions. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A company is designing a new data lake on AWS. The data lake will store petabytes of data from various sources, including IoT devices, application logs, and streaming data. The data must be stored cost-effectively, and access patterns vary from frequently accessed recent data to rarely accessed historical data. The company also needs to run SQL queries on the data. Which solution should the architect recommend?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Store data in S3 with lifecycle policies to transition between storage classes, and use Amazon Athena for queries
Option C is correct because S3 with lifecycle policies can move data to lower-cost storage classes as it ages, and Athena can query data in place without loading. Option A is wrong because Redshift is designed for structured data warehouse workloads, not a data lake. Option B is wrong because S3 with Glacier does not support direct querying; data must be restored first. Option D is wrong because EMR requires managing clusters and is not cost-effective for occasional queries.
Key principle: NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✓
Store data in S3 with lifecycle policies to transition between storage classes, and use Amazon Athena for queries
Why this is correct
S3 provides cost-effective storage with lifecycle management, and Athena can query data directly.
Related concept
Static NAT maps one inside address to one outside address.
✗
Store data in S3 with lifecycle policies to transition to Glacier, and use S3 Select for queries
Why it's wrong here
S3 Select works on S3 objects, but Glacier requires restoration before querying.
✗
Store data in Amazon EMR on EC2 and query with Hive
Why it's wrong here
EMR requires cluster management and is not cost-effective for occasional queries.
✗
Store data in Amazon Redshift and query with Redshift Spectrum
Why it's wrong here
Redshift is a data warehouse, not a cost-effective data lake for petabyte-scale diverse data.
Common exam traps
Common exam trap: NAT rules depend on direction and matching traffic
NAT is not only about the public address. The inside/outside interface roles and the ACL or rule that matches traffic are just as important.
Detailed technical explanation
How to think about this question
NAT questions usually test address translation, overload/PAT behaviour, static mappings and whether the right traffic is being translated. Read the interface direction and address terms carefully.
KKey Concepts to Remember
Static NAT maps one inside address to one outside address.
PAT allows many inside hosts to share one public address using ports.
Inside local and inside global describe the private and translated addresses.
NAT ACLs identify traffic for translation, not always security filtering.
TExam Day Tips
→Identify inside and outside interfaces first.
→Check whether the scenario needs static NAT, dynamic NAT or PAT.
→Do not confuse NAT matching ACLs with normal packet-filtering intent.
Key takeaway
NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.
Real-world example
How this comes up in practice
A startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
What to study next
Got this wrong? Here's your next step.
Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related SAP-C02 NAT questions on configuration and troubleshooting.
Design for New Solutions — This question tests Design for New Solutions — Static NAT maps one inside address to one outside address..
What is the correct answer to this question?
The correct answer is: Store data in S3 with lifecycle policies to transition between storage classes, and use Amazon Athena for queries — Option C is correct because S3 with lifecycle policies can move data to lower-cost storage classes as it ages, and Athena can query data in place without loading. Option A is wrong because Redshift is designed for structured data warehouse workloads, not a data lake. Option B is wrong because S3 with Glacier does not support direct querying; data must be restored first. Option D is wrong because EMR requires managing clusters and is not cost-effective for occasional queries.
What should I do if I get this SAP-C02 question wrong?
Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related SAP-C02 NAT questions on configuration and troubleshooting.
What is the key concept behind this question?
Static NAT maps one inside address to one outside address.
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Question Discussion
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