Results for “monitoring”

Analyze AWS CloudTrail logs for security monitoring, threat detection, and forensic investigation using Athena, CloudWatch Logs Insights, and SIEM integration.

Audits deployment readiness across CI/CD, containers, monitoring, IaC, secrets, CDN, and DNS, scoring each area and identifying critical gaps, with optional auto-fix via chained sub-skills.

Builds operational monitoring dashboards for Grafana, SigNoz, and similar platforms, focusing on answering operator questions about health, bottlenecks, and changes rather than displaying every metric.

Configures dynamic threshold alerting policies for Google Cloud Vertex AI Agent Platform agents, monitoring latency, error rates, and quality metrics using Terraform and PromQL.

Deploys a secure, enterprise-grade Google Cloud landing zone foundation with organization policies, resource hierarchy, billing association, and centralized logging and monitoring.

Manages NS1 DNS zones, records, filter chains, monitoring jobs, and traffic steering via the NS1 API, with a discovery-first workflow for inspection and troubleshooting.

Deploy kernel-level runtime security monitoring on Linux hosts or Kubernetes clusters using eBPF and Cilium Tetragon for process execution tracking, network observability, file access auditing, and runtime enforcement.

Comprehensive DevOps skill for CI/CD, infrastructure automation, containerization, and cloud platforms (AWS, GCP, Azure). Includes pipeline setup, infrastructure as code, deployment automation, and monitoring. Use when setting up pipelines, deploying applications, managing infrastructure, implementing monitoring, or optimizing deployment processes.

Monitors cloud workloads for runtime threats by checking process lists, network connections, file integrity, and resource utilization anomalies on EC2 and GCE instances.

Deploys and configures Suricata IDS/IPS with Emerging Threats rulesets, EVE JSON logging, and custom rules for real-time network traffic inspection, threat detection, and integration with SIEM platforms.

ML pipeline design — data versioning, experiment tracking, deployment patterns, drift monitoring. Use when building an ML pipeline from data to deployment, setting up MLOps tooling (DVC, MLflow, model registry), choosing deployment patterns (shadow, canary, A/B), or designing monitoring for drift and degradation.

Deploys and manages Falco YAML rules for runtime threat detection in containers and Kubernetes, monitoring syscalls for shell spawns, file tampering, network anomalies, and privilege escalation. Parses Falco alerts for incident response.

Hardens serverless compute platforms (AWS Lambda, Azure Functions, Google Cloud Functions) by enforcing least privilege IAM roles, eliminating hardcoded secrets, scanning dependencies for vulnerabilities, validating input, securing function URLs, and enabling runtime monitoring.

DevOps & Infrastructure IA — Gère le VPS, Docker, déploiements, monitoring, sécurité, tunnels Cloudflare. Expert Hetzner + Coolify + self-hosting.

Deploy, monitor, and manage GCP services with battle-tested patterns.

World-class DevOps engineering - cloud architecture, CI/CD pipelines, infrastructure as code, and the battle scars from keeping production running at 3amUse when "devops, infrastructure, deployment, ci/cd, docker, kubernetes, aws, gcp, azure, terraform, cloudflare, vercel, monitoring, alerting, pipeline, container, scaling, downtime, incident, sre, devops, infrastructure, cloud, ci-cd, monitoring, reliability, sre, containers" mentioned.

Inspect Sentry issues, events, and production errors using the Sentry CLI for read-only observability queries.

Trace, evaluate, and monitor LLM applications with an open-source observability platform.

Implements multi-level caching with strategies for invalidation, stampede prevention, and performance monitoring.

Sets up the Manifest observability plugin for AI agents, including installation, API key configuration, and verification.

Debug, evaluate, and monitor LLM applications with tracing, datasets, and built-in evaluators.

Export OpenTelemetry traces, metrics, and logs to Azure Application Insights using Python.

Monitors OpenClaw model API usage and prompts for user confirmation before switching models when quota is low.

Runs and manages DNAnexus jobs and workflows, including monitoring, parallel execution, and error handling.

Archive non-actionable noise from the Sentry javascript project issue queue, using untilEscalating mode with documented categories.

Manage interactive tmux sessions from an agent, including spawning coding agents in parallel and monitoring their output.

Implements database replication, failover, backups, connection pooling, and monitoring for production PostgreSQL, MySQL, and MongoDB systems.

Diagnoses Qdrant production issues using metrics and observability tools, covering optimizer problems, memory spikes, and slow queries.

Sets up Datadog tracing for Node.js applications by installing the dd-trace library and linking to official documentation.

Continuously monitors system performance, identifies improvement opportunities, and orchestrates skill discovery and creation to autonomously evolve capabilities.

MLOps lead for deployment, monitoring, and scaling. Use when the user asks to talk to McGonagall, requests deployment help, or needs CI/CD for AI systems.

Captures and analyzes Windows debug output (OutputDebugString, DbgPrint/KdPrint) from the command line, with filtering, bounded execution, and remote monitoring.

Guides securing and deploying the Dify platform in production, covering SSRF protection, code sandboxing, Docker/Kubernetes deployment, monitoring, and recovery.

Executes Azure CLI commands with parallel background jobs for fast metric collection, using tsv output and read-only operations.

Installs and configures the Manifest observability plugin for AI agents, including API key setup, endpoint configuration, and connection verification.

Manage Azure Application Insights resources including components, web tests, workbooks, and API keys using the .NET SDK.