How To Optimize Telemetry Pipelines For Better Observability and Security

    4 MIN READ

    Tucker Callaway (CEO, Mezmo) and Kevin Petrie (Vice President of Research, Eckerson Group) had a conversation centered around enterprises taking control of their data and the growing need for consolidated collection and management of telemetry data. They discuss how enterprises can optimize telemetry pipelines, take charge of their data, and enhance their observability and security game.

    Listen to the full episode here

    What is a Telemetry Pipeline?

    • Telemetry pipelines handle the collection, transformation, and routing of telemetry data to optimize storage and analysis.
    • Prioritize storing valuable data in expensive destinations and employ sampling or filtering for less critical data, leading to significant cost savings.

    The Evolution of Telemetry Pipelines

    • Enterprises are increasingly taking ownership of their data.
    • Consolidating data collection and management allows real-time analysis, control, and insights.
    • Telemetry pipelines represent a shift in the market, with a particular focus on the early stages of development.

    Understanding Telemetry Pipelines

    • Telemetry pipelines deal with a vast array of data sources, including cloud infrastructure, load balancers, clusters, virtual private networks, custom applications, and more.
    • The challenge lies in managing the noise generated by logs, metrics, and traces, requiring a balance between signal and noise.

    The Cost-Value Curve Problem

    • Telemetry data presents a unique challenge in terms of its cost curve.
    • The cost of collecting and storing data often outpaces the value derived from it.
    • The importance of data may suddenly spike in specific contexts, such as during a performance issue or security threat.

    Challenges in Data Management

    • The industry has taken control of applications and infrastructure but lags in data management.
    • Existing toolchains often result in duplicated efforts, with the average enterprise employing over six observability tools.
    • Telemetry pipelines address these challenges by managing the collection, transformation, and routing of data.

    Roles in Managing Telemetry Pipelines

    • Site Reliability Engineers, DevOps professionals, Cloud Ops, IT Ops, and others play crucial roles in managing telemetry pipelines.
    • Challenges arise from the dynamic nature of roles and confusion regarding data ownership.

    DataOps Framework Applied

    • Applying a DataOps lens involves continuous integration, testing, monitoring, and orchestrating pipelines.
    • Understanding data characteristics is foundational for testing, monitoring, and optimizing telemetry pipeline management.

    Plugging into Existing Tools

    • Mezmo optimizes existing observability tools like Datadog and Splunk rather than disrupting their usage.
    • A future opportunity is identified in transitioning to a model where storage and analysis are decoupled, allowing for more strategic control points.

    Telemetry pipelines are at the forefront of empowering enterprises to take control of their data. By addressing the cost-value curve problem, optimizing data management, and plugging into existing tools, Mezmo aims to enhance observability and security for SREs, DevOps, IT Ops, Sec Ops, Platform Engineers, and Data Ops professionals managing service functions. The evolution of telemetry pipelines presents exciting opportunities, emphasizing the importance of efficient and optimized data usage.

    Listen to the full episode here