BagelHole
Showing 1–60 of 163 skills · Page 1 of 3
BagelHole / ai-coding-agent-guardrails
1.1kSecure AI coding agents (Claude Code, Cursor, Codex, Copilot) with permission boundaries, secret protection, code review gates, and safe sandbox configurations for team environments.
BagelHole / ai-inference-service-mesh
1.1kUse service mesh patterns for AI inference traffic management, mTLS, canary releases, policy enforcement, and cross-cluster resilience.
BagelHole / ai-pipeline-orchestration
1.1kOrchestrate AI/ML pipelines for data ingestion, model training, batch inference, and RAG indexing using Prefect, Airflow, or Dagster. Build reliable, observable, and retriable workflows for production AI systems.
BagelHole / ai-red-teaming
1.1kRun structured AI red team exercises for jailbreak resistance, data exfiltration risk, harmful output controls, and agent tool abuse resilience.
BagelHole / ai-security-hardening
1.1kHarden AI/LLM deployments against prompt injection, data exfiltration, model theft, and supply chain attacks. Covers input validation, output filtering, access control, model API security, and compliance controls for production AI systems.
BagelHole / ai-sre-incident-response
1.1kBuild AI-focused SRE incident response practices for LLM outages, degraded quality, runaway cost events, and safety regressions.
BagelHole / alerting-oncall
1.1kSet up alerting rules, configure on-call rotations, and manage incident response workflows. Integrate with PagerDuty, Opsgenie, or Grafana OnCall for alert routing and escalation
BagelHole / argocd-gitops
1.1kImplement GitOps with ArgoCD for declarative Kubernetes deployments. Configure applications, manage sync policies, implement progressive delivery, and automate deployments from Git repositories
BagelHole / aws-secrets-manager
1.1kStore and rotate secrets in AWS Secrets Manager. Configure automatic rotation, access policies, and application integration
BagelHole / azure-devops
1.1kSet up Azure Pipelines for CI/CD, configure build and release pipelines, manage Azure DevOps projects, and integrate with Azure services
BagelHole / azure-keyvault
1.1kManage secrets and certificates in Azure Key Vault. Configure access policies, integrate with Azure services, and implement secure secret management
BagelHole / blue-green-deploy
1.1kConfigure zero-downtime deployment strategies including blue-green, canary, and rolling deployments. Implement traffic shifting, health checks, and rollback procedures
BagelHole / circleci
1.1kConfigure CircleCI workflows and orbs for continuous integration and deployment. Create config.yml pipelines, use orbs for reusable configurations, and optimize build performance
BagelHole / cis-benchmarks
1.1kAudit and remediate CIS benchmark violations. Use automated tools to assess compliance and implement hardening recommendations
BagelHole / container-hardening
1.1kSecure Docker images and container runtime configurations. Implement non-root users, read-only filesystems, and security contexts
BagelHole / container-registries
1.1kManage container registries including ECR, ACR, GCR, and Docker Hub. Push and pull images, configure authentication, set up repository policies, and implement image lifecycle management
BagelHole / container-scanning
1.1kScan container images for vulnerabilities using Trivy, Grype, and cloud-native tools. Identify security issues in base images, packages, and configurations
BagelHole / dast-scanning
1.1kPerform dynamic application security testing with OWASP ZAP, Burp Suite, and Nikto. Test running applications for security vulnerabilities through automated and manual testing
BagelHole / datadog
1.1kImplement Datadog monitoring and APM for infrastructure and applications. Configure agents, create dashboards, set up alerts, and implement distributed tracing
BagelHole / dependency-scanning
1.1kScan package dependencies for known vulnerabilities using Snyk, Dependabot, and OWASP Dependency-Check. Identify and remediate vulnerable libraries in your software supply chain
BagelHole / devcontainers-nix
1.1kCreate reproducible development environments with Dev Containers, Nix flakes, and Devbox for consistent toolchains across teams
BagelHole / docker-compose
1.1kDefine and run multi-container Docker applications using Docker Compose. Create compose files, manage service dependencies, configure networks and volumes, and orchestrate local development environments
BagelHole / docker-management
1.1kBuild, optimize, and troubleshoot Docker containers and images. Create efficient Dockerfiles, manage container lifecycle, configure networking and volumes, and debug container issues
BagelHole / ebpf-observability
1.1kUse eBPF for deep kernel-level observability — trace syscalls, network flows, and application behavior without code changes using Cilium, Tetragon, and bpftrace.
BagelHole / elk-stack
1.1kDeploy and manage the ELK Stack (Elasticsearch, Logstash, Kibana) for log aggregation and analysis. Configure log pipelines, create visualizations, and implement log-based monitoring
BagelHole / feature-flags
1.1kImplement feature flags for progressive feature rollout using LaunchDarkly, Unleash, or custom solutions. Control feature visibility, perform A/B testing, and enable trunk-based development
BagelHole / git-workflow
1.1kImplement Git branching strategies, PR workflows, and release management patterns. Configure GitFlow, trunk-based development, or GitHub Flow for team collaboration
BagelHole / github-actions
1.1kBuild, test, and deploy applications using GitHub Actions workflows. Create CI/CD pipelines, configure runners, manage secrets, and automate software delivery
BagelHole / gitlab-ci
1.1kConfigure GitLab CI/CD pipelines and runners for automated building, testing, and deployment. Create .gitlab-ci.yml configurations, manage runners, and implement DevOps workflows
BagelHole / gpu-kubernetes-operations
1.1kOperate GPU-backed Kubernetes clusters for AI inference and training with scheduling, autoscaling, node health, MIG partitioning, and cost controls.
BagelHole / gpu-server-management
1.1kSet up and manage NVIDIA GPU servers for AI workloads — driver installation, CUDA toolkit, container toolkit, MIG partitioning, GPU health monitoring, and multi-GPU configuration for LLM inference and training.
BagelHole / helm-charts
1.1kCreate, manage, and deploy Helm charts for Kubernetes package management. Build reusable chart templates, manage releases, configure values, and use Helm repositories
BagelHole / incident-management
1.1kImplement incident management processes and escalation procedures. Configure on-call schedules and post-incident reviews
BagelHole / incident-response
1.1kHandle security incidents with IR playbooks and procedures. Implement detection, containment, eradication, and recovery processes
BagelHole / kubernetes-hardening
1.1kImplement Kubernetes security contexts, Pod Security Standards, and network policies. Secure cluster components and workloads
BagelHole / kubernetes-ops
1.1kDeploy, scale, and manage Kubernetes workloads. Create deployments, services, and configurations, manage cluster resources, troubleshoot pods, and implement production-ready Kubernetes patterns
BagelHole / kustomize
1.1kCustomize Kubernetes manifests without templating using Kustomize. Create base configurations with environment overlays, manage configuration variants, and patch resources declaratively
BagelHole / linux-hardening
1.1kApply CIS benchmarks and secure Linux servers. Configure SSH, manage users, implement firewall rules, and enable security features
BagelHole / llm-caching
1.1kImplement multi-layer LLM caching with exact match, semantic similarity, and provider-side prompt caching. Reduce API costs by 30–70%, cut latency, and improve throughput using Redis, GPTCache, and provider caching APIs.
BagelHole / llm-cost-optimization
1.1kReduce LLM API and infrastructure costs through model selection, prompt caching, batching, caching, quantization, and self-hosting strategies. Track spend by team and model, set budgets, and implement cost-aware routing.
BagelHole / llm-fine-tuning
1.1kSet up infrastructure for fine-tuning LLMs with QLoRA, LoRA, and full fine-tuning using Hugging Face TRL, Axolotl, and distributed training with DeepSpeed or FSDP. Covers dataset prep, training runs, and model export.
BagelHole / llm-gateway
1.1kDeploy an API gateway for LLM traffic with load balancing, rate limiting, key management, semantic caching, fallback routing, and cost tracking. Covers LiteLLM Proxy, OpenRouter-compatible setup, and custom Nginx/Traefik patterns.
BagelHole / llm-inference-scaling
1.1kAuto-scale LLM inference clusters on Kubernetes using KEDA, custom GPU metrics, and horizontal pod autoscaling. Handle traffic spikes, implement queue-based scaling, and optimize cost with spot instances for AI workloads.
BagelHole / llmops-platform-engineering
1.1kBuild production LLMOps platforms with CI/CD, model promotion workflows, evaluation gates, rollback, and governance across cloud and self-hosted inference.
BagelHole / loki-logging
1.1kConfigure Grafana Loki for log aggregation and analysis. Set up Promtail for log collection, write LogQL queries, and integrate with Grafana for visualization
BagelHole / mcp-server-security
1.1kSecure Model Context Protocol (MCP) servers with transport encryption, tool authorization, input validation, and audit logging for safe AI agent integrations.
BagelHole / mdm-device-management
1.1kManage and secure company devices with MDM solutions — enroll macOS, Windows, iOS, and Android devices, enforce security policies, and automate software deployment
BagelHole / model-registry-governance
1.1kEstablish model registry standards, governance controls, metadata schemas, approvals, and lifecycle policies for enterprise AI deployments.
BagelHole / model-serving-kubernetes
1.1kDeploy ML models on Kubernetes with KServe (formerly KFServing) and NVIDIA Triton Inference Server. Includes canary deployments, autoscaling, model versioning, A/B testing, and GPU resource management for production model serving.
BagelHole / model-supply-chain-security
1.1kSecure the AI model supply chain with artifact signing, provenance attestation, SBOM workflows, dependency controls, and trusted model promotion.
BagelHole / multi-tenant-llm-hosting
1.1kDesign secure, multi-tenant LLM hosting platforms with tenant isolation, quotas, billing attribution, noisy-neighbor protection, and per-tenant policy controls.
BagelHole / new-relic
1.1kConfigure New Relic observability platform for infrastructure and application monitoring. Set up APM agents, create dashboards, configure alerts, and implement distributed tracing
BagelHole / openclaw-deployment-hardening
1.1kSecure OpenClaw deployments with preflight hardening checks, CI/CD guardrails, container runtime restrictions, and post-deploy verification
BagelHole / openclaw-security-hardening
1.1kHarden OpenClaw self-hosted environments with baseline host controls, auth tightening, secret handling, network segmentation, and safe update/rollback workflows
BagelHole / openshift
1.1kManage Red Hat OpenShift clusters and deployments. Configure projects, routes, builds, and deploy applications using OpenShift-specific features
BagelHole / penetration-testing
1.1kPerform basic penetration testing and security assessments. Use reconnaissance, vulnerability discovery, and exploitation techniques
BagelHole / platform-engineering
1.1kBuild internal developer platforms (IDPs) with self-service infrastructure, golden paths, and developer portals using Backstage, Crossplane, and score.
BagelHole / podman
1.1kManage containers using Podman, the daemonless container engine. Run rootless containers, create pods, manage images, and use Docker-compatible commands
BagelHole / prometheus-grafana
1.1kSet up metrics collection and visualization with Prometheus and Grafana. Configure scrape targets, create PromQL queries, build dashboards, and implement alerting
BagelHole / prompt-injection-defense
1.1kDefend AI systems against prompt injection and indirect prompt attacks using input controls, tool permissions, output validation, and isolation boundaries.