Skill UI

This tool monitors Certificate Transparency (CT) logs to detect unauthorized certificate issuance for owned domains, discover hidden subdomains, and track suspicious certificate activity. By querying public CT logs and APIs (like crt.sh), it helps build continuous security pipelines, identify potential phishing infrastructure, and map the external attack surface for comprehensive threat intelligence.

A comprehensive guide for optimizing query latency in Qdrant. This resource explains advanced performance tuning techniques, focusing on critical resource management like RAM utilization, segment count adjustments, and HNSW parameter tuning. It details strategies for scaling, quantization, and hardware considerations (e.g., local NVMe) to ensure consistently low-latency search performance, and outlines common pitfalls to avoid.

A comprehensive guide for diagnosing production performance issues in Qdrant vector databases. Learn how to systematically check the optimizer status, analyze high memory usage (OOM crashes), and troubleshoot slow query latencies using key metrics and dedicated API endpoints. Essential for maintaining optimal operational health.

This skill provides comprehensive API calls using `curl` to interact with the CAST AI platform. It allows users to list connected Kubernetes clusters, retrieve detailed cost savings reports, and inspect the inventory of managed nodes. It is essential for verifying connectivity, auditing cloud spending, and monitoring resource allocation after onboarding.

This comprehensive guide details how to set up end-to-end observability for ClickHouse. It covers extracting key metrics using built-in system tables (e.g., query logs, merge status), integrating the metrics with Prometheus, and finally visualizing performance, throughput, and health indicators on Grafana dashboards. Essential for monitoring production-grade ClickHouse deployments and configuring reliable alerting.

This guide provides a comprehensive framework for investigating production issues on the Nexu platform using the Datadog Logs API. It details how to query crash events, analyze OpenClaw stderr output, check gateway startup status, and review API request logs (including 5xx errors). It includes best practices for authentication, filtering by pod/time, and parsing raw JSON logs using Python for actionable insights.

A comprehensive guide for managing the full lifecycle of OpenKruise within the KubeSphere platform. This skill assists users with installation, upgrading, querying status (CRDs, Pods, logs), generating manifests for advanced workloads (SidecarSet, CloneSet), performing rollouts, and troubleshooting complex runtime issues like webhooks or missing configurations, utilizing both kubectl and KubeSphere APIs.

This skill provides a deep dive into optimizing Oracle Cloud Infrastructure (OCI) resources. It guides users through selecting appropriate compute shapes (e.g., E5.Flex, A1.Flex) and understanding the performance tiers for block volumes (Balanced, Ultra High Performance). Users can programmatically query available shapes, create performance-tuned volumes, and monitor real-time IOPS and network bandwidth using the OCI SDK, ensuring optimal infrastructure decisions for any workload.

This guide provides comprehensive guidance on scaling Qdrant, a vector database. It helps users diagnose performance bottlenecks and determine the optimal horizontal or vertical scaling strategy. Strategies are categorized based on specific needs: increasing data volume, improving query throughput (QPS), minimizing query latency, or managing high query result volumes.

This comprehensive guide provides advanced strategies for optimizing and scaling Qdrant vector database throughput (QPS). It covers performance tuning techniques, such as optimizing segment size, enabling quantization, and using batch search. Furthermore, it details horizontal scaling methods using read replicas and addressing disk I/O bottlenecks, ensuring high performance for large-scale, high-concurrency retrieval applications.

This component is an essential extension for KubeSphere Observability Platform, designed for comprehensive collection, processing, and storage of Kubernetes and KubeSphere audit events. It supports various sinks, including OpenSearch and Doris, and provides an API for querying historical audit data, ensuring robust auditing capabilities for platform operations.

This extension component is integral to the KubeSphere Observability Platform. It provides robust mechanisms for collecting, processing, and storing Kubernetes events using the kube-events-exporter. Users can leverage the detailed event query API to gain deep insights into cluster activity, making it essential for comprehensive system monitoring and observability setup.