This is a multiple-response question. Both B and C are viable strategies, depending on the specific context and complexity. Option B is a native XSIAM solution: XSIAM's Multiline Log Parser is specifically designed for such scenarios. It allows defining a start pattern to group related lines into a single logical event before subsequent parsing. Within that single event, multiple parse_regex() or parse_kv() operations can then extract fields from different lines, using a common identifier (like a transaction ID) for correlation within the same event. Option C is also a common and effective approach, especially if the multiline parsing logic is highly complex or requires custom logic not easily expressed in Data Flow. Pre-processing the logs externally ensures that XSIAM receives well-formed, single-event records, simplifying subsequent ingestion and analysis. Option A is inefficient and prone to errors due to the difficulty of reliably joining disparate event fragments. Option D is highly inefficient for large datasets and makes real-time analysis challenging. Option E (ML-based parsing) is generally for unstructured or semi-structured data, not for highly irregular but logically structured multiline events where explicit rules are needed.