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By secondsky
Deploy ML models to production by generating FastAPI servers for prediction serving, Docker containers for packaging, and Kubernetes configurations for orchestration. Monitor performance with drift detection, resolve latency issues, health checks, and version conflicts in a unified workflow.
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Deploy ML models to production
Use this agent when setting up CI/CD pipelines, configuring Docker containers, deploying applications to cloud platforms, setting up Kubernetes clusters, implementing infrastructure as code, or automating deployment workflows. Examples: <example>Context: User is setting up a new project and needs deployment automation. user: "I've built a FastAPI application and need to deploy it to production with proper CI/CD" assistant: "I'll use the deployment-engineer agent to set up a complete deployment pipeline with Docker, GitHub Actions, and production-ready configurations."</example> <example>Context: User mentions containerization or deployment issues. user: "Our deployment process is manual and error-prone. We need to automate it." assistant: "Let me use the deployment-engineer agent to design an automated CI/CD pipeline that eliminates manual steps and ensures reliable deployments."</example>
AI/ML development: LLM architecture, prompt engineering, ML ops, and NLP with production deployment focus
Automate ML workflows with Airflow, Kubeflow, MLflow. Use for reproducible pipelines, retraining schedules, MLOps, or encountering task failures, dependency errors, experiment tracking issues.
DigitalOcean cloud deployment plugin for App Platform, Droplets, Kubernetes, Functions, Managed Databases, Spaces storage, and infrastructure management with official MCP server integration
Expert Modal.com serverless cloud platform system with comprehensive Modal 1.0 SDK (May 2025) features, GPU functions (T4/L4/A10G/L40S/A100/H100/H200/B200), autoscaler configuration, @modal.concurrent/@modal.batched decorators, Sandboxes for isolated code execution, CloudBucketMount for S3/GCS, and production deployment patterns. PROACTIVELY activate for: (1) ANY Modal.com task, (2) GPU configuration with fallbacks and multi-GPU, (3) Autoscaler settings (min/max/buffer containers, scaledown_window), (4) Web endpoints (FastAPI, ASGI, WSGI, custom servers), (5) @modal.concurrent for request concurrency, (6) @modal.batched for dynamic batching, (7) Sandboxes for untrusted code execution, (8) Scheduling (Cron with timezone, Period), (9) Storage (Volumes with commit(), Dict with TTL, Queue, CloudBucketMount), (10) Parallel processing (.map(), .starmap(), .spawn(), .for_each()), (11) Container lifecycle (@modal.enter, @modal.method, @modal.exit), (12) Image building (uv_pip_install, run_function for model downloads), (13) Secrets and environment management, (14) Deployment and CI/CD with GitHub Actions, (15) Cost optimization and 2025 pricing. Provides: Modal 1.0 stable API patterns, GPU selection guide with per-second pricing, autoscaler tuning strategies, concurrency and batching for ML inference, Sandbox security patterns, CloudBucketMount for external data, complete CLI reference, debugging workflows, and production-ready configurations.
This skill provides comprehensive guidance for SAP Cloud Logging service on SAP BTP. Use when setting up Cloud Logging instances, configuring log ingestion from Cloud Foundry or Kyma runtimes, implementing OpenTelemetry observability, analyzing logs/metrics/traces in OpenSearch Dashboards, configuring SAML authentication, managing certificates, or troubleshooting ingestion issues. Covers service plans (dev/standard/large), all 4 instance creation methods (BTP Cockpit, CF CLI, BTP CLI, Service Operator), all 4 ingestion methods (Cloud Foundry, Kyma, OpenTelemetry, JSON API), and security best practices.
This skill provides comprehensive guidance for SAP BTP Job Scheduling Service development, configuration, and operations. It should be used when creating, managing, or troubleshooting scheduled jobs on SAP Business Technology Platform. The skill covers service setup, REST API usage, schedule types and formats, OAuth 2.0 authentication, multitenancy, Cloud Foundry tasks, Kyma runtime integration, and monitoring with SAP Cloud ALM and Alert Notification Service. Keywords: SAP BTP, Job Scheduling, jobscheduler, cron, schedule, recurring jobs, one-time jobs, Cloud Foundry tasks, CF tasks, Kyma, OAuth 2.0, XSUAA, @sap/jobs-client, REST API, asynchronous jobs, action endpoint, run logs, SAP Cloud ALM, Alert Notification Service, multitenancy, tenant-aware, BC-CP-CF-JBS
SAP HANA Machine Learning Python Client (hana-ml) development skill. Use when: Building ML solutions with SAP HANA's in-database machine learning using Python hana-ml library for PAL/APL algorithms, DataFrame operations, AutoML, model persistence, and visualization. Keywords: hana-ml, SAP HANA, machine learning, PAL, APL, predictive analytics, HANA DataFrame, ConnectionContext, classification, regression, clustering, time series, ARIMA, gradient boosting, AutoML, SHAP, model storage
Develops and administers SAP Build Work Zone, advanced edition digital workplace solutions. Use when creating workspaces, workpages, and collaborative sites, developing UI Integration Cards in SAP Business Application Studio, building content packages and workspace templates, integrating with Microsoft 365/Teams/SharePoint/Google Drive, configuring chatbots and webhooks, implementing SCIM API user provisioning, setting up OData business records, managing themes and branding, configuring role-based access and SSO, troubleshooting deployment issues, or working with the Administration Console. Keywords: SAP Build Work Zone advanced edition, digital workplace, UI Integration Cards, content packages, workspace templates, SAP Business Application Studio, SAP Conversational AI, SCIM API, OData, Microsoft Teams integration, SSO, theming, Administration Console
This skill provides comprehensive knowledge for SAP Service Manager on SAP Business Technology Platform (BTP). It should be used when managing service instances, bindings, brokers, and platforms across Cloud Foundry, Kyma, Kubernetes, and other environments. Use when provisioning services via SMCTL CLI, BTP CLI, or REST APIs, configuring OAuth2 authentication, working with the SAP BTP Service Operator in Kubernetes, troubleshooting service consumption issues, or implementing cross-environment service management. Keywords: SAP Service Manager, BTP, service instances, service bindings, SMCTL, service broker, OSBAPI, Cloud Foundry, Kyma, Kubernetes, service-manager, service-operator-access, subaccount-admin, OAuth2, X.509, service marketplace, service plans, rate limiting, cf create-service, btp create services/instance, ServiceInstance CRD, ServiceBinding CRD
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