Mezmo

What is Mezmo?

Mezmo is a comprehensive telemetry data pipeline and log analysis platform designed to help engineering, DevOps, and SRE teams efficiently collect, profile, transform, and route telemetry data. By leveraging AI-powered data profiling and customizable processors, Mezmo enables users to reduce log volumes, improve data quality, and maintain compliance. It integrates seamlessly with popular observability tools like Splunk, DataDog, New Relic, and Grafana, empowering teams to gain actionable insights faster while controlling costs. Mezmo also offers features such as in-stream alerts, usage quotas, and enterprise-grade access controls to enhance operational efficiency and security.

Key Features

• AI-Powered Data Profiling

  Automatically analyze telemetry data to identify patterns, noisy logs, and optimization opportunities for efficient data processing.

• Flexible Telemetry Pipelines

  Build and customize pipelines with processors to filter, reduce, sample, deduplicate, and route data to multiple destinations.

• Cost Control and Usage Quotas

  Set daily and monthly data ingestion limits with alerts and automatic log exclusion to manage costs effectively.

• Seamless Integration

  Route optimized telemetry data to leading observability platforms such as Splunk, DataDog, New Relic, Grafana, and Prometheus.

• Enterprise Features

  Support for shared sources, processor groups, single sign-on, and granular access controls for large-scale deployments.

• Fast Time-to-Value

  Onboard and create optimized telemetry pipelines in under 15 minutes using Mezmo Flow, an AI-enabled guided workflow.

Use Cases

• Log Volume Reduction : Reduce telemetry data size by filtering and transforming logs to lower storage costs and improve system performance.
• Incident Response Acceleration : Use in-stream alerts and responsive pipelines to detect anomalies and act quickly to resolve issues.
• Data Compliance and Security : Redact and encrypt sensitive information within telemetry data to meet regulatory requirements.
• Observability Modernization : Centralize and optimize data from diverse sources to enable efficient migration or integration with multiple observability tools.
• Enterprise-Scale Data Management : Manage large telemetry deployments with fine-grained user access, shared configurations, and pipeline as code capabilities.

FAQs