observability
Distributed tracing with Jaeger, OpenTelemetry, and observability platforms for microservices insights
Discover Development skills, compare source repositories and read the instructions for each workflow.
Distributed tracing with Jaeger, OpenTelemetry, and observability platforms for microservices insights
Centralized logging with ELK Stack, Loki, Fluentd, and log analysis for distributed systems
Docker and Kubernetes - containerization, orchestration, and production deployment.
GitOps practices with ArgoCD, FluxCD, and declarative infrastructure management
Service mesh technologies including Istio, Linkerd, Consul, and Envoy for microservices communication
Implement comprehensive AWS security controls and compliance
Deploy and configure RDS/Aurora databases with HA and security
Design and implement production-grade VPC architectures
Launch, configure, and manage EC2 instances with best practices
Configure AWS IAM users, roles, policies, and identity federation
Optimize AWS costs through resource rightsizing and savings strategies
Configure S3 buckets with security, lifecycle, and replication policies
Infrastructure as Code with CloudFormation templates and stacks
Implement monitoring, alerting, and observability with CloudWatch
Deploy and manage containerized applications on ECS/Fargate
Build optimized serverless functions with Lambda
Build automated CI/CD pipelines with CodePipeline and CodeBuild
Retrieval Augmented Generation systems with vector search, document processing, and hybrid retrieval.
LLM evaluation frameworks, benchmarks, and quality metrics for production systems.
AI agent development with LangChain, CrewAI, AutoGen, and tool integration patterns.
LLM architecture, tokenization, transformers, and inference optimization. Use for understanding and working with language models.
Vector database selection, indexing strategies, and semantic search optimization.
LLM deployment strategies including vLLM, TGI, and cloud inference endpoints.
LLM fine-tuning with LoRA, QLoRA, and instruction tuning for domain adaptation.
The default order uses GitHub repository stars from our indexed data. Stars belong to the source repository and may be shared by multiple skills. They indicate repository interest, not skill installs or an independent quality score.