As organizations embrace the complexity of modern IT ecosystems—spanning cloud-native, hybrid environments, and distributed systems—the need for streamlined data management has become more critical than ever. At the heart of this transformation lies the telemetry pipeline, a system designed to collect, process, and route telemetry data like logs, metrics, and traces. These pipelines ensure businesses can handle the growing volumes of data generated across multiple sources while enabling real-time analysis and decision-making.
What is a Telemetry Pipeline?
A telemetry pipeline is a foundational component in modern IT ecosystems, designed to collect, process, and route telemetry data—such as logs, metrics, and traces—from various data sources to designated destinations. Whether the goal is operational monitoring, application performance management, or security information and event management (SIEM), telemetry pipelines enable organizations to handle and optimize the immense flow of information generated across their systems.
Key components of a telemetry pipeline include:
Data collectors and agents
Data processors for filtering, enrichment, and transformation
Routing mechanisms for directing data to appropriate destinations
Storage systems for both hot and cold data
Analytics and visualization tools for deriving insights
In today’s distributed IT environments—featuring cloud, hybrid, and on-premises systems—the challenges surrounding telemetry data have grown exponentially. As organizations embrace digital transformation, the sheer volumes of data being generated can strain even the most robust infrastructure. Scaling pipelines to keep up with this growth often results in skyrocketing costs and increasing complexity. Moreover, maintaining real-time performance becomes an uphill battle as data moves through multiple stages of data processing.
Managing costs is another significant hurdle. Traditional approaches to telemetry pipelines often involve ingesting all available data into centralized platforms, driving up storage and licensing fees. Yet, not all telemetry data is equally valuable—some of it is redundant or irrelevant. Without a solution to intelligently filter, enrich, or shape this data, organizations risk wasting resources while struggling to extract meaningful insights.
Beyond costs and scale, the diversity of telemetry data introduces further complexity. Different types of telemetry data require unique handling to ensure consistency and usability. This makes data management more challenging as businesses aim to extract actionable insights without overburdening their tools.
A robust telemetry pipeline addresses these challenges by streamlining data collection, transforming raw data into actionable insights, and ensuring the right information reaches the right systems. But not all telemetry pipelines offer the same level of efficiency and control. Cribl sets itself apart by giving organizations the power to reduce the amount of data ingested, route it efficiently, and enrich it with meaningful context—all while maintaining data flexibility and avoiding vendor lock-in. Cribl’s unique approach empowers businesses to manage their telemetry pipelines with confidence, ensuring their observability platforms remain cost-effective, performant, and adaptable to future demands.
How Does a Telemetry Pipeline Work?
A telemetry pipeline operates through three fundamental stages: data collection, data processing, and data routing. Together, these components form a seamless flow of information, transforming raw telemetry data from multiple data sources into actionable insights delivered to the appropriate destinations. This process not only ensures that organizations can monitor and analyze their IT environments in real time but also optimizes costs and system performance by handling volumes of data efficiently. Let’s dive into each stage and explore how they work.
[Data Sources] → [Collection] → [Processing] → [Routing] → [Destinations]
Data Collection
The first stage of any telemetry pipeline is data collection, where telemetry data is gathered from various sources across an organization’s infrastructure. These sources can include applications, servers, containers, databases, and more. In modern environments, this process must be capable of handling multiple sources simultaneously, collecting diverse types of telemetry data, such as logs, metrics, and traces.
Example: Consider a global e-commerce platform that needs to monitor its website uptime, user activity, and payment systems. Data collection tools like agents or collectors gather logs from web servers, metrics from application performance monitoring tools, and traces from distributed tracing systems. This raw data is then sent to the telemetry pipeline for further processing.
The challenge here lies in ensuring that data is collected consistently and without disrupting system performance. Cribl’s approach focuses on optimizing data collection by enabling organizations to selectively collect only the data they need, minimizing unnecessary ingestion and preserving bandwidth.
Data Processing
Once data is collected, it enters the data processing stage, where it is prepared for analysis. During this step, the pipeline transforms data, cleanses it by removing duplicates or anomalies, and enriches it with contextual information to make it more actionable. This stage is critical for managing data volume and ensuring the pipeline delivers insights rather than raw, unstructured information.
Example: A financial institution monitoring transactions for fraud might process telemetry data by filtering out non-relevant logs and enriching critical events with geolocation data. This ensures that their fraud detection systems focus only on suspicious activities, reducing the load on downstream systems like security information and event management (SIEM) platforms.
Cribl’s platform stands out by offering flexible data shaping capabilities. Organizations can redact sensitive data to ensure compliance, normalize logs into consistent formats, or even aggregate metrics to reduce the amount of data sent downstream—all without sacrificing data quality.
Data Routing
The final stage of a telemetry pipeline is data routing, where processed data is directed to its intended destinations, such as observability platforms, storage systems, or security tools. The routing process ensures that the right teams and tools have access to the information they need, whether for troubleshooting, monitoring, or long-term analysis.
Example: In a DevOps environment, telemetry data from application performance monitoring might be routed to a real-time observability platform, while archival logs are sent to cold storage for compliance purposes. At the same time, security-related logs may be forwarded to a SIEM for immediate threat detection.
Cribl’s approach to data routing is designed for ultimate telemetry data flexibility. Organizations can route the same dataset to multiple destinations, enrich data for one tool while minimizing it for another, or even replay historical data to new platforms. This ensures that businesses maintain full control over their telemetry data without being locked into specific vendors.
By integrating data collection, processing, and routing into a cohesive telemetry pipeline, organizations can unlock the full potential of their telemetry data. Cribl’s solutions empower businesses to optimize these stages with precision, ensuring their pipelines are not just functional but a strategic advantage in managing complex, modern IT ecosystems.
Telemetry Data Pipeline Use Cases
Telemetry pipelines play a vital role in a variety of industries, enabling organizations to harness the power of real-time data collection, processing, and routing to drive critical operations, optimize performance, and ensure compliance. The flexibility and scalability of telemetry pipelines make them indispensable in managing the growing volumes of data generated by diverse data sources. Below, we explore some key industries where telemetry pipelines have become essential.
Technology and Software Development
In the fast-paced world of technology and software development, telemetry pipelines are critical for maintaining observability platforms and ensuring seamless operations across DevOps environments. These pipelines enable teams to monitor application performance, troubleshoot issues, and optimize resource usage in real time.
Example: A SaaS company delivering cloud-based services uses telemetry pipelines to monitor server health, application response times, and user behavior. By efficiently processing and routing telemetry data to monitoring tools, the company can detect and resolve issues before they impact end users.
Financial Services
For financial institutions, where precision and security are paramount, telemetry pipelines offer a reliable way to manage log data, monitor transactions, and detect anomalies. With the ability to process and route sensitive data, pipelines help banks and financial organizations comply with regulations and safeguard customer information.
Example: A global bank uses telemetry pipelines to analyze millions of transactions daily, identifying potential fraud by enriching transactional data with contextual details, such as location and device information. Meanwhile, audit logs are routed to long-term storage for compliance purposes.
Healthcare
In the healthcare sector, telemetry pipelines are increasingly being used to manage the flow of critical patient and operational data. By reducing the amount of data ingested and prioritizing actionable insights, telemetry pipelines help hospitals and providers optimize care delivery while meeting strict regulatory standards.
Example: A hospital system leverages telemetry pipelines to monitor the performance of medical devices, ensuring real-time alerts for any malfunction. Simultaneously, patient data is securely routed to analytics tools for population health studies and compliance with HIPAA regulations.
Retail and E-Commerce
Retailers and e-commerce platforms rely on telemetry pipelines to monitor customer interactions, inventory systems, and payment processes. These pipelines ensure businesses can handle peak traffic periods while maintaining high-performance standards.
Example: An online retailer uses telemetry pipelines to process logs from its website and payment gateway during a flash sale. By routing relevant data to observability tools, the company ensures smooth user experiences while detecting any latency or failed transactions in real-time.
Telecommunications
The telecommunications industry depends on telemetry pipelines to monitor network performance and ensure uptime. With data flowing from distributed systems and devices, these pipelines provide the necessary infrastructure to maintain service reliability and scalability.
Example: A telecom provider uses telemetry pipelines to collect metrics from cell towers and user devices, enabling proactive maintenance. By routing specific data to different analytics platforms, the provider can ensure network stability while planning for capacity upgrades.
Manufacturing and Logistics
In manufacturing and logistics, telemetry pipelines are critical for managing data from sensors, machines, and vehicles. They ensure data processing happens efficiently, allowing for predictive maintenance and supply chain optimization.
Example: A manufacturing company employs telemetry pipelines to monitor equipment performance in a factory. Data from sensors is processed and routed to a central dashboard, enabling the operations team to predict and prevent equipment failures before they occur.
Public Sector and Government
Governments and public sector organizations increasingly rely on telemetry pipelines to manage IT systems, monitor critical infrastructure, and ensure data security. With the ability to process large-scale data from diverse sources, these pipelines help agencies operate efficiently while safeguarding sensitive information.
Example: A government agency uses telemetry pipelines to monitor cybersecurity threats in its network. Logs from various endpoints are routed to a SIEM platform for real-time threat detection and incident response.
Telemetry pipelines are a universal solution to the challenges of data management, offering scalability, flexibility, and performance across industries. Cribl’s approach to telemetry pipelines further empowers organizations to tailor their data strategies, ensuring that every byte of telemetry data is transformed into actionable insights, no matter the use case.
Why Flexibility is Critical in Telemetry Pipelines?
As telemetry data continues to grow at a 28% CAGR, flexibility has become a cornerstone for effective telemetry pipeline management. Yet, many traditional tools lock organizations into specific tools and platforms, limiting their ability to adapt and optimize. These proprietary systems often force businesses to conform their workflows to the pipeline’s restrictions, stifling innovation, complicating compliance efforts, and adding unnecessary complexity and cost to telemetry data management.
The problem with such rigidity is clear: as IT ecosystems grow more diverse, organizations need the freedom to integrate multiple sources of telemetry data, ranging from log data to metrics and traces, into the tools best suited to their needs. Without vendor-neutral solutions, teams are left with limited choices, unable to fully leverage advancements in observability platforms, security tools, or analytics systems.
This is where Cribl, the Data Engine for IT and Security, shines. Unlike traditional solutions, Cribl puts organizations in control of their telemetry pipelines with Cribl Stream. By offering unmatched data flexibility, Cribl allows teams to route, enrich, and transform their telemetry data to meet specific business requirements. This freedom enables organizations to choose the tools and platforms that align with their goals while avoiding vendor lock-in.
Cribl’s Approach: Telemetry Pipelines Made Flexible and Scalable
Cribl takes an innovative approach to telemetry pipelines, offering organizations a unique combination of flexibility, scalability, and control. By focusing on empowering businesses rather than imposing limitations, Cribl ensures that telemetry pipelines work as a strategic advantage, not a bottleneck.
Key Benefits of Cribl’s Telemetry Pipeline Approach
Cost Efficiency: Cribl reduces operational expenses by minimizing unnecessary data ingestion and processing, helping organizations allocate resources more effectively.
Enhanced Data Control: Organizations retain complete control over their telemetry data, enabling them to decide what gets collected, processed, and routed—without relying on predefined vendor workflows.
Easily Route Any Source to Any Destination: Cribl’s telemetry pipeline excels at enabling organizations to route data from any source to any destination, offering unparalleled flexibility in managing telemetry data. Whether the data originates from cloud-native applications, on-premises servers, API endpoints, or hybrid environments, Cribl ensures seamless integration with diverse data sources and tools. By breaking the limitations of traditional pipelines, Cribl allows businesses to tailor their data flows to meet specific operational needs.
For example, log data from application performance monitoring tools can be routed directly to observability platforms, while compliance-critical logs are sent to secure storage or a SIEM for analysis. This level of control empowers organizations to ensure the right data reaches the right systems without unnecessary duplication or complexity.
Future-Proof Flexibility: With its vendor-neutral architecture and replay capabilities, Cribl enables organizations to adopt new tools or platforms as their needs evolve, ensuring long-term adaptability.
Improved Compliance and Security: Cribl simplifies the handling of sensitive data, allowing businesses to redact, encrypt, or selectively route data to comply with regulatory requirements without adding complexity.
Cribl’s telemetry pipeline approach transforms the way organizations handle telemetry data, enabling them to work smarter, adapt faster, and drive greater value from their observability and security strategies. By prioritizing data flexibility and control, Cribl positions itself as a trusted partner for businesses navigating the challenges of modern IT telemetry data management.