The correct answer is C. parseCsv() .
CrowdStrike LogScale documentation for parseCsv() states that the function supports a configurable delimiter parameter, and it is used to split a field into named columns. Because this log is space-delimited and the values are always in the same order, parseCsv() is the appropriate parser function by specifying a space as the delimiter and naming the columns in order.
Why the other options are incorrect:
* A. parseCEF() is for CEF-formatted logs, which this event is not.
* B. parseJson() is for JSON, and this event is plain text.
* D. parseFixedWidth() is meant for logs where each field occupies a strict character width.
CrowdStrike's docs describe it as valuable when data must maintain strict positional formatting and defined field lengths. This question only guarantees field order , not fixed character widths, so parseFixedWidth() is not the best match.

The correct answer is A. Full .
CrowdStrike's Falcon LogScale Collector Fleet Management enrollment documentation states that the enrollment mode can be full or localConfig , and it specifically defines full as the mode that enrolls the collector into Fleet Management with the configuration of log sources stored and managed centrally in LogScale/Next-Gen SIEM.
Why the other options are incorrect:
B). Complete and C. Central are not documented enrollment mode names. D. localConfig is a valid mode, but CrowdStrike says that mode keeps the log source configuration managed and stored locally on the host , not centrally.

The primary factor in sizing log collector clients is the amount of log data they will process daily.
Accurate estimation of daily log volume ensures that the collectors have sufficient capacity for ingestion, buffering, and forwarding without data loss.

The correct answer is D. 500 . In CrowdStrike Next-Gen SIEM correlation content limits, the maximum number of active correlation rules allowed in a single CID is 500 . This represents the upper bound for enabled rule objects at the customer-ID level and is intended to balance detection scale with performance and manageability of rule-driven detections. This is why the other options are incorrect and 500 is the correct limit.