Optimizing Log Management in Datadog: Cut Costs Without Losing Insights
2025.05.28-Mezmo-LandingPage-1540x660-PE

Sponsored By:

Mezmo-logo
Wednesday, May 28

3 pm ET

Logs are essential for troubleshooting and incident response, but as log volumes grow, so do the costs—especially for teams using Datadog. While Datadog excels at correlating logs, metrics, and traces, its ingestion-based pricing can quickly spiral out of control due to verbose debug logs, microservices sprawl, and unpredictable infrastructure spikes.

 

In this webinar, we’ll explore how to take control of logging costs without compromising visibility. You’ll learn how to identify high-value logs from low-signal noise and implement smarter log management strategies. Plus, we’ll introduce Mezmo’s Telemetry Pipeline, a powerful solution that helps you filter, shape, and route your data before it reaches Datadog—optimizing costs while preserving critical insights.

 

Join us to discover practical techniques for scaling your observability stack efficiently, so your team can focus on innovation instead of cost management.

Register Below:

We'll send you an email confirmation and calendar invite 

tina-modified

Tina Sturgis

Product Strategist - Mezmo
With over 25 years of experience, she is a visionary leader who excels at driving strategic initiatives and delivering measurable business impact across industries. At Mezmo, she is helping to reshape ‘traditional’ observability and log management by focusing on a pipeline-centric approach that delivers more value, control, transformation and trust in telemetry data.
unnamed (4)-1

Rishin Pandit

Product Manager - Mezmo
Rishin Pandit is a Product Manager at Mezmo, helping SREs and platform teams make their telemetry more actionable and effective. At Mezmo, he owns product development for features that give teams deeper visibility into their logs, metrics, and traces, along with greater control over what data is collected, retained, and analyzed. His work focuses on helping customers reduce telemetry costs while preserving critical signals, empowering them to optimize observability without sacrificing reliability or insight.