This EX294 practice question tests your understanding of transform data with filters and plugins. 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 large-scale Ansible deployment processes a list of thousands of network devices. Using the `subelements` filter to iterate over interfaces is causing very slow playbook execution. Which approach can significantly improve performance?
Use a custom filter plugin in Python that uses list comprehensions
Python-level processing is much faster than Jinja2.
Use `with_nested` instead
Why wrong: with_nested is even more resource-intensive.
Use `set_fact` with loops inside the task
Why wrong: Still uses Jinja2 loops; no performance gain.
Use `with_items` with `json_query` instead
Why wrong: json_query may have similar overhead; not a guaranteed improvement.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Use a custom filter plugin in Python that uses list comprehensions
The `subelements` filter in Ansible processes nested data structures by iterating over each parent element and its child elements, which can be extremely slow for large datasets due to the overhead of Jinja2 template evaluation and repeated lookups. A custom filter plugin written in Python using list comprehensions avoids this overhead by executing native Python code directly, which is significantly faster because it operates at the interpreter level without the iterative Jinja2 expansion. This approach reduces the number of tasks and template evaluations, improving performance for thousands of network devices.
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.
Use a custom filter plugin in Python that uses list comprehensions
Why this is correct
Python-level processing is much faster than Jinja2.
Related concept
Read the scenario before looking for a memorised answer.
Use `with_nested` instead
Why it's wrong here
with_nested is even more resource-intensive.
Use `set_fact` with loops inside the task
Why it's wrong here
Still uses Jinja2 loops; no performance gain.
Use `with_items` with `json_query` instead
Why it's wrong here
json_query may have similar overhead; not a guaranteed improvement.
Common exam traps
The trap here is that candidates often assume `with_nested` or `json_query` are equivalent or faster alternatives, but they fail to recognize that the performance bottleneck is the Jinja2 template engine itself, which a custom Python plugin bypasses entirely.
Trap categories for this question
Similar concept trap
json_query may have similar overhead; not a guaranteed improvement.
Detailed technical explanation
Under the hood, Ansible's `subelements` filter expands the parent-child relationship into a flat list of tuples during task compilation, which for thousands of devices with multiple interfaces can generate millions of items, causing memory and CPU strain. A custom filter plugin in Python executes as compiled bytecode within the Ansible controller process, leveraging list comprehensions that are optimized at the C level in CPython, resulting in orders-of-magnitude speed improvements. In real-world scenarios, such as managing a network with 10,000 switches each having 48 interfaces, the difference can be hours versus minutes.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
A small business has 20 workstations on the 192.168.1.0/24 network and one public IP from its ISP. The router uses PAT (NAT overload) so all 20 devices share one public address using different source ports. NAT questions test whether you understand the four address terms and which direction each translation applies.
What to study next
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FAQ
Transform data with filters and plugins — This question tests Transform data with filters and plugins — Read the scenario before looking for a memorised answer..
The correct answer is: Use a custom filter plugin in Python that uses list comprehensions — The `subelements` filter in Ansible processes nested data structures by iterating over each parent element and its child elements, which can be extremely slow for large datasets due to the overhead of Jinja2 template evaluation and repeated lookups. A custom filter plugin written in Python using list comprehensions avoids this overhead by executing native Python code directly, which is significantly faster because it operates at the interpreter level without the iterative Jinja2 expansion. This approach reduces the number of tasks and template evaluations, improving performance for thousands of network devices.
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 25, 2026
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