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Description

ET Ducky serves as a comprehensive diagnostics platform and remote monitoring management (RMM) solution tailored for both Windows and Linux endpoints. It captures kernel-level events—utilizing ETW on Windows and eBPF on Linux—and processes them on the agent, ensuring that personally identifiable information (PII) is filtered out while leveraging AI to articulate the root causes of alerts in straightforward terms. Surrounding this foundational capability are essential RMM tools that enable teams to respond effectively, including a browser-based remote desktop, threshold alerts that come with pre-explained root causes, behavioral security measures like ransomware detection and host isolation, approved-script execution, insightful reporting, multi-agent queries, and fleet management functionalities. Notably, raw event data remains on the machine, with only the curated evidence and AI-generated conclusions transmitted to the cloud. Designed specifically for IT teams and managed service providers (MSPs), it aims to significantly reduce the time taken to resolve tickets that other solutions might only address superficially, integrating RMM, application performance monitoring (APM), and behavioral detection into a single streamlined product. Users can take advantage of a free tier by bringing their own AI key, while paid plans start at $39 per month, making it an accessible option for various organizations. Each feature is crafted to enhance operational efficiency and drive effective incident management.

Description

Metoro serves as an AI Site Reliability Engineer tailored for Kubernetes environments, assisting Site Reliability Engineers, DevOps professionals, and software developers in managing production effectively. This innovative tool autonomously oversees both services and infrastructure to identify any issues as they emerge, subsequently diagnosing the root causes and implementing solutions by creating pull requests. Utilizing eBPF, Metoro gathers all necessary telemetry without requiring modifications to the codebase, ensuring that every container, service, and host is monitored at the kernel level in real-time. Users can effortlessly deploy Metoro into their clusters with a single helm install command, leading to a fully operational setup in approximately five minutes. Its seamless integration and rapid deployment make it an invaluable asset for teams looking to enhance their operational efficiency.