Mezmo unveiled data profiling and responsive pipelines for Kubernetes telemetry data.
Now, site reliability engineers (SREs), platform engineers, and other infrastructure teams can understand telemetry data clearly, optimize with ease, and respond to incidents rapidly — ultimately cuttting costs and improving management of their Kubernetes environments
Mezmo Telemetry Pipeline now features capabilities that help companies understand, optimize and respond to telemetry data. Mezmo Data Profiling categorizes data so teams can understand where their data originates, what it contains, and how to pull signals out of the noise. Such an understanding helps determine strategy for data reduction, metrics transformation and data routing — sending the right data in the right format to observaability tools. Mezmo Responsive Pipelines can be configured to respond to changes based on specific conditions, such as during an incident when capturing more data is critical or during data drift in source systems.
"Based on feedback from the many SREs we've spoken with, we know that the first step in getting the most from your telemetry data and your observability investments is to understand your data, which is why we've invested in Data Profiling," said Tucker Callaway, CEO of Mezmo. "We also believe that telemetry pipelines must be responsive, not static. Our platform recognizes data drift or incidents detected within observability tools and then adjusts data streams and recommends remediation steps, so that teams can take immediate actions that improve mean time to resolution."
These product additions build on recent innovations, including Mezmo Edge, for running telemetry pipelines in local environments while managing them centrally via the cloud. Mezmo Edge allows teams to gain the benefits of Telemetry Pipeline without sending data outside of their networks, reducing egress costs and honoring enterprise compliance requirements. Mezmo also offers Pipelines as Code via Terraform to support SRE-focused development and automation. Building and managing Pipelines as Code helps SREs increase change velocity and reduce toil while ensuring consistency across deployments.
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