Service Level Objectives
for Elastic

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Elastic with Nobl9

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Elasticsearch is a powerful open-source search and analytics engine often used for managing large datasets, logging, and observability. It’s particularly effective in real-time monitoring environments, where it gathers metrics, logs, and traces to help teams understand system performance and identify issues. Elasticsearch excels in scalability, making it ideal for distributed systems that need to process high volumes of data quickly. Its ability to provide fast, real-time insights and its flexibility in integrating with other observability tools makes it a popular choice across industries.

Nobl9 enhances Elasticsearch by using its rich data streams to create targeted, business-critical Service Level Objectives (SLOs). While Elasticsearch provides valuable raw data for logs, metrics, and traces, Nobl9 helps teams focus on what really impacts user experience by converting that data into actionable SLOs. Nobl9's advanced reporting and dashboards give teams a comprehensive, real-time view of how systems are performing against business goals. Additionally, since Nobl9 is data source agnostic, it can combine Elasticsearch data with other platforms, allowing teams to measure service reliability across multiple tools and ecosystems. This offers a more holistic approach to performance management, ensuring teams focus on maintaining key objectives that directly affect user satisfaction.

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