Results for “osquery”

Design, operate, and troubleshoot OCI services including OKE, IoT, Functions, and Enterprise AI with OCI Generative AI models, agents, RAG, and cost estimation.

Guides users through a structured, conversational process to generate a production-ready Terraform stack and OCI Resource Manager schema for OKE clusters on Oracle Cloud Infrastructure.

Diagnose and root-cause issues with OCI Kubernetes Engine clusters and workloads through evidence-driven investigation.

Navigate Oracle Cloud Infrastructure's Enterprise AI services: choose models, build agents with RAG and tools, estimate costs, secure access, and integrate with Oracle Database, APEX, and other platform services.

Patterns for OrbStack Linux VMs and Docker on macOS. Covers orbctl/orb commands, machine lifecycle, cloud-init, networking, file sharing, and SSH access. Must use when working with OrbStack, orbctl commands, or Linux VMs on macOS.

Query external data from Oxla — Kafka topics via catalogs, Apache Iceberg tables, and S3/GCS/Azure parquet/ORC files — alongside native Oxla tables. Use when querying Kafka topics with CREATE KAFKA CATALOG or CREATE REDPANDA CATALOG, reading Apache Iceberg tables with the catalog=>path.table syntax, loading or.

Configure Jetson UPHY lane allocation on Orin/Thor custom carriers by editing ODMDATA tokens and dispatching per-controller kernel-DT overlay skills.

Migrates OSGi EventAdmin handlers and JCR EventListeners to AEM Cloud Service-compliant patterns, including EventHandler+JobConsumer split, routing rules, and leader-only execution.

Deploy and manage network honeypots using OpenCanary, T-Pot, or Cowrie to detect unauthorized access, lateral movement, and attacker reconnaissance.

Expert knowledge for Azure Osconfig development including troubleshooting, security, configuration, and integrations & coding patterns. Use when running OSConfig via IoT for commands/networking, SSH Posture Control, agent health, or Windows security baselines, and other Azure Osconfig related development tasks. Not for Azure Update Manager (use azure-update-manager), Azure Automation (use azure-automation), Azure Policy (use azure-policy).

Orchestrate dynamic multi-agent workflows with parallel agents and adversarial verification via a local daemon, or fall back to native agent orchestration.

Routes agent turns through policy-based delegation, runtime status, and feedback loops using a TypeScript-first runtime layer for OpenClaw.

Stand up a self-hostable, typo-tolerant search environment with Typesense — the open-source Algolia / ElasticSearch alternative (single C++ binary, <50ms instant search, no runtime deps). One routing-first skill: pick a server mode (binary download, official Docker image, or managed Typesense Cloud), install an API client (Python/JS/PHP/Ruby official; Go/Dart/C# community), design a collection schema, index documents, and run searches with typo tolerance, faceting/filtering, geo-search, sorting, grouping, synonyms, curation, scoped API keys, and federated multi-search — then wire an InstantSearch.js UI and a Raft-based HA cluster for production. Use when the user wants to build or operate an installable search backend, add site/app/product search, or migrate off Algolia/Elasticsearch. Triggers on: typesense, search engine, typo-tolerant search, algolia alternative, elasticsearch alternative, instantsearch, faceted search, geo search, vector search, self-hosted search, site search, product search.

Run Comet's Opik — open-source LLM observability, evaluation, and optimization — from one routing-first skill: install the Python/TypeScript SDK, stand up a server (Comet.com cloud, Docker Compose via `./opik.sh`, or Kubernetes/Helm), wire tracing through `@opik.track` or one of 50+ framework integrations (OpenAI, Anthropic, LangChain, LangGraph, LlamaIndex, CrewAI, DSPy, Ollama, Bedrock, Vercel AI SDK, …), score outputs with LLM-as-a-judge metrics (Hallucination, Moderation, Answer Relevance, Context Precision), and run Datasets/Experiments evaluations including PyTest CI gates. Use when the user wants LLM tracing, prompt evaluation, production LLM monitoring, agent optimization, or guardrails with Opik. Triggers on: opik, comet opik, opik configure, opik.sh, llm observability, llm tracing, llm as a judge, hallucination metric, prompt evaluation, opik dashboard, opik guardrails, agent optimizer.