Scaleflux provides a cloud‑native observability platform that consolidates metrics, logs, and traces from multi‑cloud and on‑premises workloads into unified, real‑time dashboards. It uses AI‑driven anomaly detection and predictive scaling models to surface bottlenecks, automate root‑cause analysis, and recommend cost‑effective scaling actions, while offering customizable alerts and open API integrations for DevOps and SRE teams.
Funding
$200M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
2OSGFounders
Product
Problem
Enterprises often lack a unified platform to monitor, analyze, and optimize the performance of distributed cloud applications, leading to fragmented visibility and inefficient resource utilization.
Solution
Scaleflux offers a cloud-native observability platform that aggregates metrics, logs, and traces from heterogeneous environments into a single pane. The service provides real-time dashboards, automated anomaly detection, and predictive scaling recommendations powered by machine-learning models. Users can set custom alerts and integrate the platform with existing CI/CD pipelines and incident‑response tools via APIs. By centralizing performance data, Scaleflux enables teams to quickly identify bottlenecks, reduce downtime, and optimize infrastructure costs.
Target Audience
Primary customers are DevOps engineers, site reliability teams, and cloud architects managing large‑scale, distributed applications in enterprise environments.
Features
- Unified collection of metrics, logs, and distributed traces across multi‑cloud and on‑premises workloads
- AI‑driven anomaly detection and root‑cause analysis with contextual recommendations
- Auto‑scaling suggestions based on predictive usage patterns and cost models
- Customizable real‑time dashboards and alerting rules
- Open APIs and native integrations with popular CI/CD, ticketing, and monitoring ecosystems