Enhancing Datadog Observability with Telemetry Pipelines

4 MIN READ
MIN READ
TABLE OF CONTENTS
    4 MIN READ
    MIN READ

    Datadog is a powerful observability platform. However, unlocking it’s full potential while managing costs necessitates more than just utilizing its platform, no matter how powerful it may be. It requires a strategic approach to data management. 

    Enter telemetry pipelines, a key to elevating your Datadog experience. 

    Telemetry pipelines offer a toolkit to achieve the essential steps for maximizing the value of your observability investment. The Mezmo Telemetry Pipeline is a great example of such.

    Let's dive into how telemetry pipelines can be a game-changer, while adhering to best practices.

    Sharpen Your Focus

    Noise filtering is paramount to a successful Datadog experience. This is where telemtry pipelines emerge to help sift through the data to help keep your eyes on the essentials. By processing the data before it is routed to Datadog, telemetry pipelines ensure that the most relevant insights are retained. 

    Master Strategic Storage

    Datadog's flexibility extends to defining retention policies, governing the duration data resides within its platform. By housing data within Datadog, you secure instant accessibility for reviews and new analyses.

    However, an inherent cost accompanies prolonged data storage within Datadog. As retention periods increase, so do the expenses.

    Here, telemetry pipelines provide a pathway to channel data to alternative, budget-friendly storage destinations like object storage or data lakes. This streamlines costs and harmonizes with Datadog's retention. Using telemetry pipelines, you can "rehydrate" data into Datadog whenever needed, reducing data retention expenses while keeping data readily available.

    Craft Precise Insights and Transform Logs into Metrics

    Telemetry pipelines can provide a similar function for Splunk. By harnessing these pipelines and using data transformation methods such as data filtering, data aggregation, sampling, event trimming, and employing prioritization mechanisms, you refine your data within Datadog and Splunk. This approach make analytics better.

    Additionally, as with any observability platform, the ability to transform voluminous logs into succinct metrics is vital. Being able to compress data volumes while retaining critical insights aligns with and echoes Datadog’s dedication to efficient data processing. 

    Amplify Backend Dynamics

    Operational efficiency is a shared goal across observability platforms, with Datadog being no exception. Telemetry pipelines, such as Mezmo, act as intermediaries (or buffers) that enable you to fine-tune data before it is routed to Datadog. This helps users increase Datadog's operations and robust system performance. 

    By strategically managing data before it reaches the backend, telemetry pipelines enhance the overall costs efficiency of your observability practice with Datadog or any other analytics platform..

    Telemetry Pipelines: The Optimal Datadog Enhancement

    Datadog stands as a potent tool on its own, but its potential is enhanced through the use of telemetry pipelines. With these pipelines, you are empowered to control data routing and processing, leading to reduced costs in contrast  to ingesting all data directly into Datadog.

    The Mezmo Telemetry Pipeline emerges as a comprehensive solution, addressing every facet of Datadog enhancement. By embracing Mezmo’s Telemetry Pipeline, you can elevate your Datadog experience, achieving heightened observability, cost-effective management, and data-driven excellence.


    Visit our telemetry pipeline page today to learn more about how our solution can help you unlock the full potential of Datadog. 

    false
    false