Axoflow + Splunk: Reduced, AI‑Ready Security Data

Splunk’s HTTP Event Collector (HEC) offers several benefits for feeding security data into your Splunk Enterprise or Splunk Cloud Platform environment, including:

• Flexible event format and batching support
  HEC accepts events in JSON or raw format, and allows multiple events in a single HTTP request. It supports structured data ingestion, and batching to reduce overhead and improve throughput.
• Improved parsing performance and indexing efficiency
  Because Axoflow sends all data to Splunk HEC with metadata (sourcetype, host, time, etc) included, the Splunk can process the data more efficiently. Faster parsing means lower latency from ingestion to availability in Splunk search, lower compute needs, and better performance at scale.
• Secure and scalable ingestion channel
  HEC operates over HTTP(S) and supports TLS encryption in transit, enabling clients to send data securely from diverse locations. The endpoint-based architecture makes it easier to load-balance and scale ingestion across Splunk clusters, improving throughput and resilience.

Axoflow optimizes ingestion costs by reducing data volume before it ever reaches your Splunk environment — while preserving the fidelity of the security telemetry your analysts rely on. Here’s how it works:

• Parse and normalize in the pipeline > Send only meaningful, well-structured data into Splunk
  Axoflow processes incoming data in the pipeline, classifying and parsing events into structured formats early in the flow. By identifying what fields and values actually matter for detection, correlation, and compliance, Axoflow filters out unnecessary payload elements and redundant metadata.
• Smart filtering and field reduction.
  Through flexible routing and filtering policies, Axoflow can remove repetitive fields, drop unneeded event types, and normalize vendor-specific formats into Splunk’s expected sourcetypes. For example, a firewall log stream can be reduced by 30–50% without losing any detection-relevant information.
• Enrich once — not everywhere.
  Instead of enriching data repeatedly inside Splunk (which adds cost at query time), Axoflow performs enrichment upstream — for example, tagging logs with geolocation or asset context as they pass through the pipeline. This ensures enrichment is done once and stored efficiently, keeping indexed data lean and consistent.
• Use dynamic routing to control what goes where.
  Axoflow allows you to route high-value or high-context events directly into Splunk while diverting verbose or low-value telemetry to a cheaper storage tier (e.g., object storage, data lake, or SIEM cold storage). That way, Splunk only receives the data needed for search, detection, and dashboards — without losing the ability to access full-fidelity data later if needed.‍
• Monitor and tune with pipeline metrics.
  Axoflow provides detailed metrics on data volume, event types, and transformation stages. You can visualize what’s contributing most to ingestion size and adjust filters or parsers accordingly — ensuring that your Splunk license is used for the highest-value data.