Quick Answer
The correct answer is to use SAP HANA CloudWatch integration via SQL queries, as this method directly captures HANA-specific memory consumption from built-in SQL views like M_HOST_MEMORY and M_MEMORY. Unlike generic OS-level metrics, these SQL queries expose precise HANA memory details such as allocation limit, used memory, and heap memory, which are essential for accurate monitoring. On the AWS Certified SAP on AWS Specialty PAS-C01 exam, this scenario tests your understanding of how the SAP HANA CloudWatch integration leverages a dedicated AWS Lambda function to execute SQL queries and push results as custom CloudWatch metrics. A common trap is choosing OS-level metrics like MemoryUtilization, which miss HANA’s internal memory management. Remember the mnemonic “SQL for SAP” — when monitoring SAP HANA memory, always think SQL views, not OS metrics.
This PAS-C01 practice question tests your understanding of design of sap workloads on aws. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. 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.
An SAP system administrator needs to monitor the memory usage of SAP HANA on AWS. Which CloudWatch metric or log should be used to track HANA memory consumption?
CloudWatch Logs from HANA trace files
Why wrong: Trace files are not structured metrics.
SAP HANA CloudWatch integration via SQL queries
HANA exposes memory metrics via SQL, which can be sent to CloudWatch.
EC2 instance-level memory metrics
Why wrong: EC2 metrics show host memory, not HANA usage.
AWS CloudWatch Agent for OS metrics
Why wrong: OS metrics do not show HANA-specific memory.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
SAP HANA CloudWatch integration via SQL queries
Option B is correct because SAP HANA exposes memory consumption metrics via built-in SQL views (e.g., M_HOST_MEMORY, M_MEMORY), and the SAP HANA CloudWatch integration uses a dedicated AWS Lambda function to execute these SQL queries and push the results as custom CloudWatch metrics. This is the only option that directly captures HANA-specific memory usage, such as allocation limit, used memory, and heap memory, rather than generic OS-level metrics.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
CloudWatch Logs from HANA trace files
Why it's wrong here
Trace files are not structured metrics.
SAP HANA CloudWatch integration via SQL queries
Why this is correct
HANA exposes memory metrics via SQL, which can be sent to CloudWatch.
Related concept
Read the scenario before looking for a memorised answer.
EC2 instance-level memory metrics
Why it's wrong here
EC2 metrics show host memory, not HANA usage.
AWS CloudWatch Agent for OS metrics
Why it's wrong here
OS metrics do not show HANA-specific memory.
Common exam traps
The trap here is that candidates often confuse OS-level memory metrics (which require the CloudWatch Agent) with HANA-specific memory metrics, not realizing that HANA’s internal memory management (e.g., column store, row store, heap) is only accessible through its SQL views, not through standard OS monitoring tools.
Trap categories for this question
Command / output trap
EC2 metrics show host memory, not HANA usage.
Detailed technical explanation
The SAP HANA CloudWatch integration leverages a Lambda function that connects to HANA using the JDBC driver and executes SQL queries like SELECT * FROM M_HOST_MEMORY to retrieve memory metrics. These metrics are then published as custom CloudWatch metrics under the namespace 'SAP/HANA', allowing for granular monitoring of HANA-specific memory components such as allocation limit, used memory, and heap memory. In real-world scenarios, this integration is critical for proactive scaling because HANA memory pressure can lead to allocation failures or performance degradation before OS-level memory metrics show any anomaly.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
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FAQ
Design of SAP Workloads on AWS — This question tests Design of SAP Workloads on AWS — Read the scenario before looking for a memorised answer..
The correct answer is: SAP HANA CloudWatch integration via SQL queries — Option B is correct because SAP HANA exposes memory consumption metrics via built-in SQL views (e.g., M_HOST_MEMORY, M_MEMORY), and the SAP HANA CloudWatch integration uses a dedicated AWS Lambda function to execute these SQL queries and push the results as custom CloudWatch metrics. This is the only option that directly captures HANA-specific memory usage, such as allocation limit, used memory, and heap memory, rather than generic OS-level metrics.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 24, 2026
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