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Found 21 Skills
AWS cost optimization and FinOps workflows. Use for finding unused resources, analyzing Reserved Instance opportunities, detecting cost anomalies, rightsizing instances, evaluating Spot instances, migrating to newer generation instances, implementing FinOps best practices, optimizing storage/network/database costs, and managing cloud financial operations. Includes automated analysis scripts and comprehensive reference documentation.
Cloud & AI FinOps advisory skill. Structured cost optimization using the FinOps Foundation framework. Covers AWS, Azure, GCP, OCI, AI inference, and data platforms (Databricks, Snowflake). Use for: cloud costs, cost optimization, cloud spend, AI costs, cloud bill, FinOps assessment, GreenOps, right-sizing, commitment strategy, tagging governance.
Guides FinOps analysis on AWS, GCP, and Azure—cost visibility and allocation, tagging and showback/chargeback models, rightsizing and waste removal, RI/Savings Plan/CUD recommendations, budgets and forecasts, anomaly detection, unit economics (cost per service/customer), and FinOps cadence with engineering accountability. Use when optimizing cloud spend, analyzing CUR/billing exports, building cost dashboards, explaining bill spikes, or improving allocation—not for GL mapping, capex, depreciation, or month-end ledger close (compute-accounting-manager), enterprise EA negotiation (enterprise-cloud-architect), hands-on resource provisioning (cloud-engineer), or hardware supply efficiency (data-center-compute-supply-efficiency).
Compare FinOps metrics across multiple repositories in an organization
Analyze workflow runs - frequency, duration, success rates, and efficiency
Comprehensive infrastructure engineering covering DevOps, cloud platforms, FinOps, and DevSecOps. Platforms: AWS (EC2, Lambda, S3, ECS, EKS, RDS, CloudFormation), Azure basics, Cloudflare (Workers, R2, D1, Pages), GCP (GKE, Cloud Run, Cloud Storage), Docker, Kubernetes. Capabilities: CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins), GitOps, infrastructure as code (Terraform, CloudFormation), container orchestration, cost optimization, security scanning, vulnerability management, secrets management, compliance (SOC2, HIPAA). Actions: deploy, configure, manage, scale, monitor, secure, optimize cloud infrastructure. Keywords: AWS, EC2, Lambda, S3, ECS, EKS, RDS, CloudFormation, Azure, Kubernetes, k8s, Docker, Terraform, CI/CD, GitHub Actions, GitLab CI, Jenkins, ArgoCD, Flux, cost optimization, FinOps, reserved instances, spot instances, security scanning, SAST, DAST, vulnerability management, secrets management, Vault, compliance, monitoring, observability. Use when: deploying to AWS/Azure/GCP/Cloudflare, setting up CI/CD pipelines, implementing GitOps workflows, managing Kubernetes clusters, optimizing cloud costs, implementing security best practices, managing infrastructure as code, container orchestration, compliance requirements, cost analysis and optimization.
Expert cloud architect specializing in AWS/Azure/GCP multi-cloud infrastructure design, advanced IaC (Terraform/OpenTofu/CDK), FinOps cost optimization, and modern architectural patterns. Masters serverless, microservices, security, compliance, and disaster recovery. Use PROACTIVELY for cloud architecture, cost optimization, migration planning, or multi-cloud strategies.
Autonomous DevSecOps & FinOps Guardrails. Orchestrates Gemini 3 Flash to audit Linux Kernel patches, Terraform cost drifts, and K8s compliance.
Guides enterprise-scale cloud architecture—multi-BU landing zones and federation, cloud Center of Excellence governance, enterprise agreement and commit strategy, org-wide FinOps and chargeback, regulated-workload patterns (residency, segmentation), hybrid integration with identity and ERP, and architecture review board standards for large organizations. Use when designing cloud at hundreds of accounts, steering CCoE policy, EA/MACC optimization, sovereign or regulated cloud placement, or executive cloud governance—not for single-product cloud designs (cloud-architect), hands-on service config (cloud-engineer), SOC 2 evidence automation (compliance-engineer), general cross-domain ADRs (senior-system-architecture), or enterprise AI copilot architecture (applied-ai-architect-commercial-enterprise), or VP-level cloud program portfolio and board narratives (vp-of-cloud).
Use this skill when working on infrastructure, DevOps, CI/CD, Kubernetes, cloud deployment, observability, or cost optimization. Activates on mentions of Kubernetes, Docker, Terraform, Pulumi, OpenTofu, GitOps, Argo CD, Flux, CI/CD, GitHub Actions, observability, OpenTelemetry, Prometheus, Grafana, AWS, GCP, Azure, infrastructure as code, platform engineering, FinOps, or cloud costs.
Guides VP-level cloud program leadership—multi-year cloud strategy and migration/modernization portfolio, landing zone and CCoE operating model at org scale, hyperscaler enterprise agreement and commit governance, hybrid/multi-cloud posture, cloud center of excellence and talent, and board/CFO/CTO cloud narratives. Use when setting cloud direction, prioritizing migration waves, governing EA/MACC and cloud spend envelope, designing federated cloud org model, steering CCoE and standards adoption, preparing executive or board cloud updates, or adjudicating product vs platform vs security cloud trade-offs—not for Terraform/K8s implementation (cloud-engineer, infrastructure-engineer), landing zone technical design (enterprise-cloud-architect, cloud-architect), monthly CUR FinOps (finops-analyst), TCO/NPV modeling (cloud-economist), full infra portfolio including DC capex (vp-of-infrastructure), or GL close (compute-accounting-manager).
Guides cleaning and standardizing tabular datasets before analysis, modeling, or reporting—profiling, quality rules, missing values, duplicates, outliers, type coercion, encoding fixes, record linkage, deduplication, high-level PII handling (not legal advice), actuarial/insurance field scrubbing, reproducible scrub pipelines, validation checks, and sign-off. Distinct from warehouse ETL or statistical modeling. Use when the user asks for "data scrubbing", "clean this dataset", "scrub the data", "data cleaning", "dedupe records", "handle missing values", "outlier treatment", "standardize columns", "data quality rules", "profile this table", or "prepare data for modeling". Not warehouse pipelines (data-warehouse-engineer), ML modeling (data-scientist, actuary), privacy programs (compliance-engineer), FinOps only (finops-analyst), or assumption governance (assumption-setting).