Results for “da”

Diagnose and observe an Oxla distributed analytical database using system catalog tables, Prometheus metrics, runtime log-level changes, and troubleshooting workflows for slow queries, node health, and memory/OOM pressure. Also covers debugging Oxla's external data sources, including the Redpanda/Kafka ingestion path.

Runs a three-phase AOI training pipeline: AutoML HPO baseline, DEFT iterative data improvement, and AutoML refinement on the augmented dataset.

Convert per-page styled HTML prototypes into Edge Delivery Services blocks and content pages, then deploy via DA.

Deploy DefectDojo as a centralized vulnerability management dashboard with scanner integrations, deduplication, metrics tracking, and Jira ticketing workflows.

Convert books into supervised fine-tuning datasets and train style-transfer models that replicate an author's voice.

Generates a single-page engineering runbook template with service overview, alerts table, dashboards, common procedures, on-call rotation, and incident response checklist.

Operate Hugging Face Hub repositories, models, datasets, and Spaces via the hf CLI, including downloads, uploads, authentication, and compute jobs.

Turns model work into a production ML system with data contracts, reproducible training, quality gates, deployable artifacts, and monitoring.

Self-hosted observability platform for LLM applications, providing tracing, evaluation, datasets, experiments, and real-time monitoring to debug and improve AI systems.

Evaluates a containerized framework for deploying distributed big data workloads, measuring execution time and cloud cost scaling from four to eight nodes.

Criar projetos, serviços e bancos de dados no Railway com configuração adequada. Use quando o usuário disser "setup", "deploy to railway", "initialize", "create project", "create service", ou quiser fazer deploy do GitHub. Gerencia setup inicial E adição de serviços a projetos existentes. Para bancos de dados, use a skill railway-railway-database em vez disso.

Plan and execute zero-downtime migrations for databases, services, and infrastructure with automated compatibility validation and rollback strategy generation.

Provides CRUD operations for Azure Cosmos DB NoSQL API from Rust, including document management, container operations, and globally distributed data access.

Manage Azure AI Foundry projects with .NET SDK: create and run agents, manage connections, datasets, deployments, evaluations, and indexes.

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

Provides code examples and best practices for using Pinecone, a managed vector database for production RAG, recommendation, and semantic search applications.

Build streaming data pipelines with Redpanda Connect using declarative YAML configs, Bloblang mappings, and component discovery. Covers running, linting, and dry-running pipelines.

Guides backend development across API design, authentication, databases, performance, security, scalability, and testing, with quick decision guides and defaults for production-ready systems.

Manage Azure Machine Learning resources including workspaces, jobs, models, data, compute, and pipelines using the SDK v2 for Python.

Diagnoses and resolves slow Qdrant indexing and data ingestion by optimizing batching, sharding, HNSW parameters, and payload indexing strategies.

Automate New Relic operations including APM, alerts, dashboards, NRQL queries, and infrastructure monitoring via Composio's New Relic toolkit through Rube MCP.

Streams change data capture from PostgreSQL into Redpanda or Kafka using Redpanda Connect's postgres_cdc input, covering setup, snapshotting, and troubleshooting.

Turn model work into a production ML system with data contracts, reproducible training, quality gates, deployable artifacts, and monitoring.

Analyzes AWS Glue ETL jobs, crawlers, Data Catalog, and schema registry using parallel AWS CLI queries with anti-hallucination guardrails.

Fine-tune models on Azure AI Foundry using SFT, DPO, or RFT, covering dataset preparation, training job submission, deployment, and evaluation.

Store and process large N-dimensional arrays with chunking, compression, and parallel I/O, integrating with NumPy, Dask, and Xarray for cloud-native scientific computing.

Guides users through installing, configuring, and verifying the DAWN voice assistant, covering system dependencies, building, models, configuration, admin account, SSL, and optional features.

Automated security auditing covering SAST, DAST, dependency scanning, secret detection, container hardening, and compliance checks before deployments or when integrating new dependencies.

Manage Kuma service mesh by discovering meshes, dataplanes, and policies via the Kuma API, then analyzing configuration and producing structured reports.

Implements production LLM operations: RAG pipelines, embeddings, vector databases, fine-tuning, advanced prompt engineering, cost estimation, quality evals, semantic caching, streaming, and agents.

Data Version Control for ML projects. Track large datasets and models alongside Git, build reproducible ML pipelines, and run experiments with metric comparison. Works with any storage backend including S3, GCS, Azure, and local filesystems.

Use when running analytical SQL over Parquet/CSV/JSON without a warehouse, replacing pandas for data wrangling, joining S3 data in-place, building local data marts, or embedding OLAP into an app. Triggers: read_parquet/read_csv setup, partitioned dataset queries, hive partitioning, glob patterns for S3, COPY TO export, attach Postgres/MySQL, UDFs in Python/R, MotherDuck cloud sync, columnar performance vs row stores. NOT for OLTP workloads (concurrent writes), distributed analytics at petabyte scale (use Spark/Trino), or vector search (use pgvector/Lance).

Plans, configures, and manages GKE networking including private clusters, VPC-native configurations, Gateway API, DNS, ingress/egress, Dataplane V2, and IP planning.

Send custom logs to Azure Monitor Log Analytics workspace using the Logs Ingestion API and Python SDK.

Integrates SAST, DAST, and SCA security scanning into CI/CD pipelines using open-source tools like Semgrep, Trivy, OWASP ZAP, and Gitleaks.

Streams Salesforce change data capture and platform events into Redpanda or Kafka using Redpanda Connect's salesforce_cdc input, covering setup, configuration, and operational details.