Telemetry data (logs, metrics, and traces) is becoming increasingly important for organizations in today’s digital landscape. Developers, SREs, and security engineers use telemetry data in different ways to achieve their respective goals, which can lead to challenges in managing the increasing amounts of data.

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In a rapidly growing digital landscape, organizations face challenges with collecting and processing telemetry data (logs, metrics, and traces). As the amount of telemetry data increases, organizations need to understand how various groups use it so they can optimize operations and keep costs in check.

Developers, site reliability engineers (SREs), and security engineers all interact with telemetry data in different ways to achieve their respective goals. Developers use telemetry data for troubleshooting, debugging, and testing software. SREs use it to ensure software performance and stability. And security engineers use it to identify and address vulnerabilities in software applications and systems.

By understanding each group’s interactions with telemetry data, organizations can determine the most effective way to manage it at scale. Observability pipelines provide a solution to this data management challenge, giving each group the visibility they need to improve their processes.

Managing Telemetry Data with Pipelines

Developers, SREs, and security engineers often face the challenge of managing increasing amounts of telemetry data and the corresponding storage cost. This is due to the expanding and diverse nature of data sources, such as containerized environments, which makes gathering and processing data time-consuming. On top of that, developers and security engineers simultaneously work with three to four observability tools to analyze data and SREs six to seven — leading to even more complexity. (Also Read: How Can Containerization Help Your Business).

Telemetry pipelines can alleviate the strain of data management by providing greater control of the data. Teams can use them to collect, transform, and direct data to its desired location while maintaining the appropriate context. They can use pipelines to interact with, manage, transform, and gain insights into data in transit before it hits any downstream observability tool. These capabilities allow developers, security engineers, and SREs to cut down on data costs, extract more value, and only pay for the data they use.

To support developers, SREs, and security engineers in managing data, telemetry pipelines should include these elements:

  • Collect Data from Multiple Sources: Developers and security engineers often need to analyze data in different formats from multiple sources, which can lead to manual collection and management. A telemetry pipeline that aggregates data from these sources, such as cloud services and applications, reduces manual work and makes the process easier. The pipeline should support open standards such as OpenTelemetry and popular formats for effortless data ingestion, allowing for easy configuration changes.
  • Transform and Route Data: Data transformation is a crucial aspect of observability, allowing for easy consumption, despite differences in sources and formats. An observability pipeline that can transform and route data provides a foundation for cross-team insights. Transformation, such as augmentation and enrichment, adds value to the data by providing additional context.
  • Integrate Functionality Easily: Developers, security engineers, and SREs invest considerable resources in integrating their data with a particular provider. In fact, they work with three to four observability platforms to analyze data and make decisions. Telemetry pipelines that integrate with the downstream tools they already use can reduce effort, resources, and manual management.
  • Aggregate Data From Cloud Services, Apps: In most cases, SREs need support for sources such as cloud services, cloud applications, and firewalls for troubleshooting, monitoring uptime, and analytics. A telemetry pipeline that can gather data from these various cloud environments would decrease the workload of collecting and preparing the data manually.
  • Data Compliance: Sensitive data present in logs can potentially lead to fines or data breaches that directly cost organizations. Pipelines can help redact or mask sensitive data, encrypt PII information, and decrypt it as needed, making sure the compliance requirements are met.

Access to telemetry data is a crucial factor in the success of software applications and systems, requiring the availability of data across developer, SRE, and security engineer teams. Pipelines allow organizations to take ownership of their data, make it available to various teams, and avoid data lock-ins in a single system. As the amount of telemetry data increases, organizations must find ways to handle it efficiently. Telemetry pipelines provide a centralized platform for data management and allow each team to interact with the data in a manner that aligns with their objectives.

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