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What is Randoli?

Randoli functions as a holistic observability and cost management platform utilizing OpenTelemetry, specifically tailored for Kubernetes, multicloud, hybrid, and AI/ML environments. By integrating crucial aspects such as infrastructure health, application performance, logs, metrics, traces, incidents, and cloud spending into one central interface, it enables teams to transition from multiple tools to a cohesive perspective on system performance. Its federated design smartly separates the control plane from the data plane, which allows for localized telemetry analysis, extraction of relevant signals, and on-demand data access during investigations, all while reducing ingestion and egress and maintaining data sovereignty. Randoli effectively monitors a variety of components, including clusters, nodes, pods, workloads, services, dependencies, latency, errors, throughput, and resource utilization across various platforms like AWS, Azure, Google Cloud, OpenShift, and local environments. Furthermore, it employs OpenTelemetry and eBPF for seamless, low-overhead instrumentation, which not only improves filtering and enriches telemetry but also facilitates real-time signal correlation, thereby enhancing overall observability. This cutting-edge methodology not only simplifies operational insights but also equips teams with the tools they need to proactively oversee performance and manage costs effectively within their cloud infrastructures. By adopting such an integrated approach, organizations can foster greater agility and responsiveness in their operations.

What is Coroot?

Coroot is a state-of-the-art, open-source observability platform that integrates artificial intelligence to deliver teams extensive insights into their applications and infrastructure, while also identifying and clarifying issues in real-time. This platform collects and processes telemetry data—including metrics, logs, traces, and profiling information—without requiring any modifications to existing code or complex configurations, employing eBPF for effortless system instrumentation and rapid insights. By creating a comprehensive model of your system, it accurately maps out services, dependencies, databases, and network connections, providing a transparent view of component interactions and enabling quick detection of irregularities or performance challenges. Additionally, Coroot’s AI-driven root cause analysis acts like a virtual assistant, methodically analyzing common failure patterns, identifying the sources of incidents, and delivering actionable recommendations, which significantly reduces the necessity for manual troubleshooting and accelerates resolution times. This groundbreaking methodology not only simplifies the troubleshooting process but also enhances the overall operational efficiency and reliability of teams, allowing them to focus on innovation and growth rather than getting bogged down by persistent issues. Ultimately, Coroot empowers organizations to harness the full potential of their technology stack with ease and confidence.

Media

Media

Integrations Supported

Amazon Web Services (AWS)
Google Cloud Platform
Kubernetes
Microsoft Azure
OpenTelemetry
Red Hat OpenShift

Integrations Supported

Microsoft Teams
PagerDuty
Slack

API Availability

API Availability

Pricing Information

$0.04 per hour
Free Version

Pricing Information

$1 per month
Free Trial Offered?

Supported Platforms

SaaS
On-Prem

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

24 Hour Support
Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub
Webinars
Online Training

Company Facts

Organization Name

Randoli

Date Founded

2017

Company Location

Canada

Company Website

www.randoli.io

Company Facts

Organization Name

Coroot

Date Founded

2021

Company Location

United States

Company Website

coroot.com

Categories and Features

AI Observability

Not specified

Cloud Monitoring

Not specified

Observability

Not specified

Categories and Features

Root Cause Analysis

Not specified

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