Results for “data-lake-storage-gen2”

Configures GKE storage including PVCs, PersistentVolumes, Filestore, and GCS FUSE with best practices for production workloads.

Provides guidance on enabling and optimizing GKE Cluster Autoscaler, including Node Auto Provisioning, troubleshooting scale-up/down issues, and best practices for capacity management.

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

Protects stateful GKE workloads by configuring backup plans, restore workflows, and disaster recovery using Backup for GKE.

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.

Chunked, compressed N-dimensional arrays for cloud storage with Zarr — parallel I/O, S3/GCS integration, and NumPy/Dask/Xarray compatibility. Use when storing or reading large N-D scientific arrays, streaming chunked data to/from cloud object stores, or building large-scale scientific computing pipelines. Part of the AlterLab Academic Skills suite.

Design and operate Azure Storage services for durability, performance, and secure access. Use this skill when users ask about Blob, Files, Queues, Tables, or Data Lake storage patterns. Covers redundancy, tiering, access models, lifecycle policies, and compliance.

Manage AWS EC2 virtual machines — instances, security groups, key pairs, AMIs, EBS volumes, Auto Scaling Groups, Spot Instances, Session Manager, placement groups, and instance lifecycle automation.

**Trigger**: Use when working with GKE Storage — Google Kubernetes Engine configuration and management.

Manage Azure Cache for Redis instances via the Azure Resource Manager .NET SDK, including creation, firewall rules, access keys, patch schedules, geo-replication, and private endpoints.

Provides reference information and CLI commands for Azure Storage services including Blob, File Shares, Queue, Table, and Data Lake, along with guidance on access tiers, redundancy options, and SDK usage.

Builds Retrieval-Augmented Generation pipelines with vector stores, chunking strategies, and reranking

ByteDance's open-source super agent harness — spawns parallel sub-agents, Docker sandbox execution, persistent long-term memory, modular skills (research/report/slides). Built on LangChain + LangGraph. Triggers on: 'deerflow', 'deer-flow', 'bytedance agent', 'super agent harness', 'LangGraph agent orchestration', 'multi-hour agent tasks', 'spawn sub-agents', 'agent sandbox docker', 'persistent agent memory', 'agent skills system', 'AI research orchestrator', 'long-running agent tasks', 'agent with memory', 'langgraph orchestrator', 'IM channel agent integration'.

Deploy web applications, APIs, and background services on AWS using CDK, covering EC2, ECS Fargate, Lambda, API Gateway, CloudFront, Route 53, RDS, ElastiCache, IAM, and monitoring.