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Optimizing Data for Service Management Objective Monitoring

4 MIN READ
MIN READ
Braxton Johnston

9.12.24

Data expert and outdoor nerd with a passion for powerful, intuitive logging.
4 MIN READ
MIN READ

The introduction of Service Level Indicators (SLIs) and Service Level Objectives (SLOs) for monitoring the performance of web applications is raising serious challenges to the world of traditional observability workflows, with new tools coming onto the scene to help manage, automate, and track progress for meeting SLOs. One challenge is determining which metrics contained with the logs are useful as SLIs, and then optimizing the telemetry data for SLO monitoring tool.

This demo shows how you can use a Mezmo Telemetry Pipeline to optimize your telemetry data for use with an SLO monitoring tool, in this case Nobl9, but the same principles apply for other monitoring tools, such as Grafana and Datadog. By using a Mezmo Telemetry Pipeline to manage and process SLI data, you can:

* Enable intuitive, visual SLI definitions for stakeholders across the enterprise, including Product Managers, Engineering Managers, Developers, and Site Reliability Engineers

* Enable rapid integration with your SLO monitoring tools by providing the data you need in the right format

* Explore useful SLIs in the telemetry stream by having access to real-time streams and profiles of your source data

For more information on how a Mezmo Telemetry Pipeline can help you identify SLIs and manage your SLOs, reach out to our Technical Services team for a free consultation.




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