Ingext vs SentinelOne Observo
Detailed Analysis
Observo AI — formerly known as SentinelOne Observio — extends the SentinelOne Singularity platform with streaming ingestion, enrichment, and routing for endpoint telemetry.
Ingext, in contrast, is a vendor-agnostic streaming data fabric engineered to unify telemetry from security, observability, and compliance systems into a single, continuous pipeline.
Learn more: For a comprehensive explanation of data fabrics and their role in SIEM architecture:
Read: Why We Need a Data FabricThis page compares both platforms under the SIEM Data Fabric Evaluation Framework, assessing each against the two must-have gates and five technical criteria that define a true streaming data fabric.
Evaluation Framework Recap
Stage 1 – Gate Requirements
Failing either gate disqualifies a product from being a streaming data fabric.
Transformation (Parsing)
Inline parsing, normalization, timestamp correction, and enrichment before storage. Ensures data becomes usable as it flows, not after ingestion.
Learn about SIEM architectureStreaming Continuity
Continuous, unpaused flow with buffering, retries, and rolling upgrades. Guarantees reliability and low latency even during bursts or outages.
Stage 2 – Technical Criteria
Routing
Conditional, multi-destination routing to SIEMs, archives, and data lakes. Enables tiered data delivery and cost-efficient control.
Learn more: Understanding the strategic decision between SIEM storage and data lakes directly impacts routing strategies.
Read: SIEM vs Data LakeFiltering / Dropping
Inline filtering or sampling to remove redundant telemetry. Reduces downstream cost and noise.
Output Versatility
Direct output to metrics systems, data lakes, and SIEMs. Allows one fabric to serve multiple analytic domains.
Processing Logic
Declarative or rule-based inline computation and enrichment. Adds real-time intelligence without post-processing.
Agnostic Deployment
Operates across cloud, hybrid, or on-prem with open interfaces. Prevents vendor lock-in and supports enterprise diversity.
Gate Evaluation
| Gate | Ingext | SentinelOne Observo | Commentary |
|---|---|---|---|
| Transformation (Parsing) | Performs inline parsing, normalization, and enrichment across diverse telemetry types. | Performs inline normalization and enrichment of SentinelOne endpoint and identity telemetry. | Both meet the transformation gate; Ingext covers a broader range of sources beyond endpoint data. |
| Streaming Continuity | True streaming with buffering, retries, and zero-downtime updates. | Built on a real-time streaming ingestion engine within Singularity. | Both maintain continuous flow; Observo AI's pipeline is confined to SentinelOne's ecosystem. |
Gate Result: Both pass. Observo AI qualifies as a true streaming fabric inside SentinelOne, while Ingext extends that capability to multi-vendor data.
Stage 2 Criteria Analysis
| Criterion | Ingext | SentinelOne Observo | Summary |
|---|---|---|---|
| Routing | Conditional multi-sink routing (SIEM, data lake, archive, metrics). | Routing primarily within Singularity; limited external destinations. | Ingext enables open, tiered routing; Observo AI focuses on internal data movement. |
| Filtering / Dropping | Inline filtering and sampling with rule-based discard logic. | Performs in-stream filtering and reduction for endpoint events. | Both can filter; Ingext allows tenant-level and cross-source policies. |
| Output Versatility | Outputs to Splunk, Elastic, Sentinel, Parquet/S3, Prometheus. | Exports primarily to SentinelOne Log Base and integrated data lake. | Ingext supports full multi-destination streaming; Observo AI remains ecosystem-specific. |
| Processing Logic | Declarative FPL-style inline processing and enrichment. | Pre-defined transformation templates; limited custom logic. | Ingext provides richer logic for computed fields and correlation. |
| Agnostic Deployment | Deployable on-prem, hybrid, or cloud with open APIs (HTTP, HEC, Kafka). | Operates only within SentinelOne's SaaS environment. | Ingext is vendor-neutral; Observo AI is proprietary. |
Derived Cost Efficiency
| Factor | Ingext | SentinelOne Observo | Insight |
|---|---|---|---|
| Data Reduction Ratio | 3–10 : 1 through intelligent routing and filtering. | 2–3 : 1 typical within SentinelOne data flows. | Ingext achieves higher reduction via open routing and selective ingestion. |
| Processing Efficiency | Linear scale under 5× burst with predictable latency. | Scales with SentinelOne tenant size; opaque metrics externally. | Both efficient in context; Ingext provides transparent performance monitoring. |
| Effective Cost per Processed GB | Predictable tiered pricing; independent of vendor ecosystem. | Bundled into SentinelOne licensing; cost varies by edition. | Ingext offers transparent pricing; Observo AI cost tied to SentinelOne contracts. |
Summary of Findings
Ingext
- Meets all Gate and Stage 2 criteria.
- Handles mixed telemetry from multiple vendors in a single streaming fabric.
- Provides inline enrichment, routing, and reduction with deterministic performance.
- Offers open deployment across on-prem, hybrid, or full-cloud environments.
- Achieves predictable cost efficiency through selective routing and storage tiering.
Ideal for: Enterprises and MSSPs unifying telemetry across EDR, firewall, cloud, and identity systems under one streaming architecture.
SentinelOne Observo
- Passes both Gate requirements and performs strongly within SentinelOne Singularity.
- Enables real-time normalization and filtering of endpoint telemetry.
- Closed ecosystem: limited to SentinelOne sources and destinations.
- Minimal extensibility for third-party routing or enrichment.
- Functions best as a proprietary streaming layer inside the SentinelOne platform.
Ideal for: Organizations standardized on SentinelOne Singularity seeking internal streaming optimization rather than cross-vendor data integration.
Verdict
| Aspect | Ingext | SentinelOne Observo |
|---|---|---|
| Gate Compliance | ||
| Routing Flexibility | ||
| Filtering Control | ||
| Output Versatility | ||
| Processing Logic | ||
| Agnosticism | ||
| Overall Fit for SIEM Data Fabric |
Conclusion
Both Ingext and Observo AI qualify as streaming data fabrics — each performing inline transformation and maintaining continuous flow.
The difference lies in scope and openness:
Learn more: For insights on operationalizing data fabric capabilities effectively in your SOC:
Read: Run Your SOC like an MSSP- Observo AI provides reliable streaming for SentinelOne telemetry but remains confined to its ecosystem.
- Ingext generalizes that capability, delivering a vendor-neutral data fabric that connects SIEMs, data lakes, and analytics tools across the enterprise.