GitHub
observability
Distributed tracing with Jaeger, OpenTelemetry, and observability platforms for microservices insights
Skills IA Développement
Découvrez les skills Développement, comparez leurs dépôts et consultez leurs instructions.
Catégories: Développement
Développement Effacer les filtres
Explorer
GitHub
logging
Centralized logging with ELK Stack, Loki, Fluentd, and log analysis for distributed systems
GitHub
containers-skill
Docker and Kubernetes - containerization, orchestration, and production deployment.
GitHub
gitops
GitOps practices with ArgoCD, FluxCD, and declarative infrastructure management
GitHub
service-mesh
Service mesh technologies including Istio, Linkerd, Consul, and Envoy for microservices communication
GitHub
aws-security-best-practices
Implement comprehensive AWS security controls and compliance
GitHub
aws-rds-setup
Deploy and configure RDS/Aurora databases with HA and security
GitHub
aws-vpc-design
Design and implement production-grade VPC architectures
GitHub
aws-ec2-deployment
Launch, configure, and manage EC2 instances with best practices
GitHub
aws-iam-setup
Configure AWS IAM users, roles, policies, and identity federation
GitHub
aws-cost-optimization
Optimize AWS costs through resource rightsizing and savings strategies
GitHub
aws-s3-management
Configure S3 buckets with security, lifecycle, and replication policies
GitHub
aws-cloudformation
Infrastructure as Code with CloudFormation templates and stacks
GitHub
aws-cloudwatch
Implement monitoring, alerting, and observability with CloudWatch
GitHub
aws-ecs
Deploy and manage containerized applications on ECS/Fargate
GitHub
aws-lambda-functions
Build optimized serverless functions with Lambda
GitHub
aws-codepipeline
Build automated CI/CD pipelines with CodePipeline and CodeBuild
GitHub
rag-systems
Retrieval Augmented Generation systems with vector search, document processing, and hybrid retrieval.
GitHub
evaluation-metrics
LLM evaluation frameworks, benchmarks, and quality metrics for production systems.
GitHub
agent-frameworks
AI agent development with LangChain, CrewAI, AutoGen, and tool integration patterns.
GitHub
llm-basics
LLM architecture, tokenization, transformers, and inference optimization. Use for understanding and working with language models.
GitHub
vector-databases
Vector database selection, indexing strategies, and semantic search optimization.
GitHub
model-deployment
LLM deployment strategies including vLLM, TGI, and cloud inference endpoints.
GitHub
fine-tuning
LLM fine-tuning with LoRA, QLoRA, and instruction tuning for domain adaptation.
Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.