
Security operations teams are facing an overwhelming surge in telemetry data from endpoints, cloud platforms, and third-party services—a surge that’s growing at an estimated 20% annually. Traditional security tools, like SIEMs, are buckling under the weight, unable to scale to meet the demands of this new era by themselves.
Modern security telemetry pipelines are emerging as a viable solution for many lean-forward security teams by providing an easy and scalable way to refine and distribute data rather than simply consuming it for silod use-cases as is traditionally done in SIEM.
By simplifying data collection, automating data deduplication and hygiene, and enhancing security telemetry in real-time for improved incident handling and orchestation, these pipelines commoditize data engineering for security operations, ensuring that security teams can focus on what truly matters: protecting their business by identifying and responding to threats.
In this article, we’ll explore emerging operating models for security telemetry pipelines and how they are changing traditional security operations.
The Case for Modern Security Telemetry Pipelines
Security data operations today is shaped by the large number and shifting variety of different data sources. Effective threat detection today requires visibility across a diverse attack surface consisting of remote and mobile users accessing highly distributed services and infrastructure from a wide range of different devices.
While traditional security tools are still useful, they were never designed with these data volumes in mind. Security Information and Event Management (SIEM) platforms, for example, are effective at aggregating and correlating alert data but struggle to maintain streaming real-time processing capabilities at the scales we typically see in enterprises now. They were also never intended as data distributors. This is where modern security data pipelines come into play.
These pipelines act as data refineries, automating data collection and data hygiene, contextual enrichment, shaping, and routing for various purposes across the entire lifecycle of security data.
This ensures that only the most critical information reaches analysts, allowing them to focus on more valuable and strategic activities like threat hunting and incident response. With automation handling repetitive tasks, security teams can now reclaim more time to focus on the core mission.
“Modern telemetry pipelines transform SecOps from reactive to proactive, enabling faster and more precise threat detection while reducing operational overheads”
Modernizing SIEM Operations with Automated Data Hygiene and Intelligent Transformation
Replacing SIEM collectors and log shippers with pipelines to reduce SIEM costs and offload compliance data to low-cost storage.
Security data pipelines can be an essential tool for modernizing SIEM operations. Traditional SIEMs are often criticized for alert overload, manual tuning requirements, and their inability to scale as data volumes grow. Pipelines solve these issues by automating and generalizing data normalization and by preprocessing data before distributing it for further consumption by SIEM and other tools.
For instance, Auguria’s platform can largerly generalize security data originating from a wide variety of unique products in diverse data formats, automating the normalization process in our Schema Workbench. This standardizes disparate data into a unified structure that can be processed more efficiently, ultimately helping SIEMs do better at real-time threat correlation and automating aspects of incident response.
Fig. 1: Security Telemetry Pipeline distributing security data to SIEM, SDL and AWS
A true security data pipeline also does far more than just transforming data—what is typically called ETL, for "Extract, Transform, Load." Ideally, they also clean up incoming data before it gets sent to the SIEM, reducing data volume and consequently ingest-based costs and overheads. They further reduce the volume of alerts generated by eliminating duplicates (deduplication) and trimming redundant and irrelevant data, allowing security teams to focus on more signals and less noise. The result is a far more efficient SIEM, one that can keep pace with the scale of modern security environments.
Augmenting Security Analysts Through Alert Classification & Prioritization
Accerating incident response with enriched and contextualized data
Another great use case for security telemetry pipelines is increasing the effectiveness of security analysts by automating routine classification and prioritization of alerts and providing pre-enriched data to aid in analysis. Today’s security teams are often stretched thin, dealing with an ever-growing number of alerts and threats. Security data pipelines can augment their capabilities by providing more context-rich data in real-time.
In a typical security telemetry pipeline, data is enriched as it flows through different stages, incorporating context and intelligence. This is crucial for helping analysts prioritize alerts and respond to the most critical threats. Instead of wasting time sifting through raw data, analysts are presented with actionable insights right in the events.
Auguria’s solution also applies advanced analytics and machine learning to further enhance this process, allowing security analysts to detect more sophisticated threats with greater precision. Our solution contextualises data with ranking and an inbuilt ontology, enabling security teams to instantly understand whether an event is routine or anomalous. By automating these advanced curation capabilities, security teams can focus their efforts on higher-level tasks like threat hunting and incident response.
Mastering Security Data Lakes with Real-Time Analysis and Enrichment
Running a standalone security data lake, usually combined with additional SecOps tools, as SIEM replacement
For data lakes to ever become an effective alternative to SIEM, organizations must move beyond mere storage and collection. Security data lakes are effective at storing vast amounts of data but need to be integrated into a real-time processing framework to offer more than just long-term historical search and be valuable in automated threat detection. Security data pipelines are one solution to this challenge.
Security Telemetry Pipelines enable real-time enrichment of data as it enters the system. Data can be automatically classified, duplicated, and compacted before being analyzed. This reduces the amount of noise and irrelevant data that security teams need to process. The enriched data that flows through the pipeline is more actionable and easier to correlate with known threats and attack patterns.
Fig. 2: Security Telemetry Pipeline using ServiceNow, Snowflake, and Anvilogic as a SIEM replacement.
Pipelines also allow for greater flexibility and scalability. As data volumes grow, pipelines can adjust to handle the increased load without slowing down detection times. This is essential for organizations dealing with hybrid and multi-cloud environments, where data sources are not only numerous but also highly diverse.
Building Open XDR with a Federated Data Fabric
This model leverages specialized tools and platforms to provide effective threat detection, visibility, and response capabilities
Another promising application of security data pipelines is in building federated and open Extended Detection and Response (XDR) architectures. XDR integrates data from multiple layers, including endpoints, networks, cloud, and identity systems, to provide more focused threat detection. The problem is that few platform providers solve everything, so end-users still end up having to integrate other technologies. And if you want best-of-breed across the security stack, you will have to extend or build yourself. Integrating data from so many sources can be challenging, especially when dealing with vendor-specific formats and proprietary platforms.
Security data pipelines overcome these challenges by acting as a bridge between different data types and vendor solutions. By automating the normalization of data and applying advanced analytics, pipelines make it easier to build a federated detection and response system that isn’t dependent on a single vendor’s ecosystem. This allows organizations to achieve true cyberplasticity, adapting to new threats and technologies without being locked into a rigid set of tools.ipelines also facilitate Open-XDR by creating a unified data structure that can be shared across tools and platforms. This enables security teams to scale their detection and response efforts across a broader range of environments, making their security
The future of security operations isn’t consolidated. It’s Integrated
Security data pipelines are transforming the way organizations manage and process security data. By automating many of the manual tasks that burden security teams, pipelines free up analysts to focus on more strategic activities. The integration of real-time data enrichment and advanced analytics ensures that security operations can scale effectively while staying agile in the face of evolving threats.
“In a world where seconds matter, Auguria empowers teams to act with precision, confidence, and speed.”
The future of security isn’t about adding more tools but making existing tools work smarter. Auguria’s Security Knowledge Layer™ enables organisations to overcome data overload and operational inefficiencies, paving the way for AI-driven SecOps.
As we move towards decentralised security models and advanced architectures like security data fabrics and cybersecurity mesh architectures, the ability to refine, enrich, and prioritise data in real-time will be crucial.
Ready to see Auguria in action? As the market evolves towards more distributed models and cybersecurity mesh architectures, Auguria is at the forefront of transforming how organisations manage security data.
Want to learn more about how modern telemetry pipelines can drive efficiency and resilience in your organisation? Let's talk!
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