plugins/azure-to-docker-master/skills/azure-emulators-2025/SKILL.md
Azure service emulators for local development in Docker (2025). PROACTIVELY activate for: (1) Azurite for Storage (Blob, Queue, Table) emulation, (2) Cosmos DB Linux Emulator container, (3) Event Hubs emulator, (4) Service Bus emulator, (5) Azure Functions Core Tools image, (6) Azure SQL Edge container, (7) Azure App Configuration emulator, (8) connection-string conventions for emulators, (9) seeding emulators with fixtures, (10) running integration tests against emulators in CI. Provides: emulator selection matrix, docker-compose templates, well-known dev connection strings, seed-data patterns, and CI integration recipes.
npx skillsauth add JosiahSiegel/claude-plugin-marketplace azure-emulators-2025Install this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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This skill provides comprehensive knowledge of Azure service emulators available as Docker containers for local development in 2025.
Official replacement for Azure Storage Emulator (deprecated)
Image: mcr.microsoft.com/azure-storage/azurite:latest
Supported Services:
Configuration:
services:
azurite:
image: mcr.microsoft.com/azure-storage/azurite:latest
container_name: azurite
command: azurite --blobHost 0.0.0.0 --queueHost 0.0.0.0 --tableHost 0.0.0.0 --loose
ports:
- "10000:10000" # Blob service
- "10001:10001" # Queue service
- "10002:10002" # Table service
volumes:
- azurite-data:/data
restart: unless-stopped
Standard Development Connection String:
DefaultEndpointsProtocol=http;AccountName=devstoreaccount1;AccountKey=Eby8vdM02xNOcqFlqUwJPLlmEtlCDXJ1OUzFT50uSRZ6IFsuFq2UVErCz4I6tq/K1SZFPTOtr/KBHBeksoGMGw==;BlobEndpoint=http://azurite:10000/devstoreaccount1;QueueEndpoint=http://azurite:10001/devstoreaccount1;TableEndpoint=http://azurite:10002/devstoreaccount1;
Features:
--loose flag for relaxed validation (useful for local development)2025 API Version Support:
CLI Usage:
# Install via npm (alternative to Docker)
npm install -g azurite
# Run with custom location
azurite --location /path/to/data --debug /path/to/debug.log
Application Integration:
// Node.js with @azure/storage-blob
const { BlobServiceClient } = require('@azure/storage-blob');
const connectionString = process.env.AZURITE_CONNECTION_STRING;
const blobServiceClient = BlobServiceClient.fromConnectionString(connectionString);
// .NET with Azure.Storage.Blobs
using Azure.Storage.Blobs;
var connectionString = Environment.GetEnvironmentVariable("AZURITE_CONNECTION_STRING");
var blobServiceClient = new BlobServiceClient(connectionString);
Latest SQL Server with AI features
Image: mcr.microsoft.com/mssql/server:2025-latest
2025 Features:
Configuration:
services:
sqlserver:
image: mcr.microsoft.com/mssql/server:2025-latest
container_name: sqlserver
environment:
- ACCEPT_EULA=Y
- MSSQL_PID=Developer
- MSSQL_SA_PASSWORD_FILE=/run/secrets/sa_password
secrets:
- sa_password
ports:
- "1433:1433"
volumes:
- sqlserver-data:/var/opt/mssql
- ./init:/docker-entrypoint-initdb.d
healthcheck:
test: ["CMD-SHELL", "/opt/mssql-tools18/bin/sqlcmd -S localhost -U sa -P $$MSSQL_SA_PASSWORD -Q 'SELECT 1' -C || exit 1"]
interval: 10s
timeout: 3s
retries: 3
start_period: 10s
deploy:
resources:
limits:
cpus: '2'
memory: 4G
reservations:
cpus: '1'
memory: 2G
networks:
- backend
security_opt:
- no-new-privileges:true
restart: unless-stopped
secrets:
sa_password:
file: ./secrets/sa_password.txt
volumes:
sqlserver-data:
driver: local
Connection String:
Server=sqlserver;Database=MyApp;User Id=sa;Password=YourStrong!Passw0rd;TrustServerCertificate=True;
Important Notes:
mssql-tools18 for TLS 1.3 support (-C flag trusts certificate)Vector Search Example (2025 Feature):
-- Create vector index for AI similarity search
CREATE TABLE Documents (
Id INT PRIMARY KEY,
Content NVARCHAR(MAX),
ContentVector VECTOR(1536)
);
-- Perform similarity search
SELECT TOP 10 Id, Content
FROM Documents
ORDER BY VECTOR_DISTANCE(ContentVector, @queryVector);
2025 vnext-preview Features:
Image: mcr.microsoft.com/cosmosdb/linux/azure-cosmos-emulator:vnext-preview
NoSQL database emulator
Image: mcr.microsoft.com/cosmosdb/linux/azure-cosmos-emulator:vnext-preview
Configuration:
services:
cosmosdb:
image: mcr.microsoft.com/cosmosdb/linux/azure-cosmos-emulator:vnext-preview
container_name: cosmosdb
environment:
- AZURE_COSMOS_EMULATOR_PARTITION_COUNT=10
- AZURE_COSMOS_EMULATOR_ENABLE_DATA_PERSISTENCE=true
- AZURE_COSMOS_EMULATOR_IP_ADDRESS_OVERRIDE=127.0.0.1
ports:
- "8081:8081" # Data Explorer
- "10251:10251"
- "10252:10252"
- "10253:10253"
- "10254:10254"
volumes:
- cosmos-data:/data/db
deploy:
resources:
limits:
cpus: '2'
memory: 4G
networks:
- backend
restart: unless-stopped
Emulator Endpoint:
https://localhost:8081
Emulator Key (Standard):
C2y6yDjf5/R+ob0N8A7Cgv30VRDJIWEHLM+4QDU5DE2nQ9nDuVTqobD4b8mGGyPMbIZnqyMsEcaGQy67XIw/Jw==
Data Explorer:
Access at https://localhost:8081/_explorer/index.html
Application Integration:
// Node.js with @azure/cosmos
const { CosmosClient } = require('@azure/cosmos');
const endpoint = 'https://localhost:8081';
const key = process.env.COSMOS_EMULATOR_KEY;
const client = new CosmosClient({ endpoint, key });
// .NET with Microsoft.Azure.Cosmos
using Microsoft.Azure.Cosmos;
var endpoint = "https://localhost:8081";
var key = Environment.GetEnvironmentVariable("COSMOS_EMULATOR_KEY");
var client = new CosmosClient(endpoint, key);
Limitations:
2025 Official Azure Service Bus Emulator:
Official Emulator Image: mcr.microsoft.com/azure-messaging/servicebus-emulator:latest
Connection String:
Endpoint=sb://host.docker.internal;SharedAccessKeyName=RootManageSharedAccessKey;SharedAccessKey=SAS_KEY_VALUE;UseDevelopmentEmulator=true;
Message queue emulator
Note: Official emulator has limited Docker support. Use RabbitMQ as alternative.
Official Emulator (Preview):
services:
servicebus-sql:
image: mcr.microsoft.com/mssql/server:2025-latest
environment:
- ACCEPT_EULA=Y
- MSSQL_SA_PASSWORD=ServiceBus123!
volumes:
- servicebus-sql-data:/var/opt/mssql
servicebus:
image: mcr.microsoft.com/azure-messaging/servicebus-emulator:latest
depends_on:
- servicebus-sql
environment:
- ACCEPT_EULA=Y
- SQL_SERVER=servicebus-sql
- SQL_SA_PASSWORD=ServiceBus123!
ports:
- "5672:5672" # AMQP
networks:
- backend
RabbitMQ Alternative (Recommended):
services:
rabbitmq:
image: rabbitmq:3.14-alpine
container_name: rabbitmq
ports:
- "5672:5672" # AMQP
- "15672:15672" # Management UI
environment:
- RABBITMQ_DEFAULT_USER=admin
- RABBITMQ_DEFAULT_PASS=admin123
volumes:
- rabbitmq-data:/var/lib/rabbitmq
healthcheck:
test: ["CMD", "rabbitmq-diagnostics", "ping"]
interval: 30s
timeout: 10s
retries: 3
networks:
- backend
restart: unless-stopped
Image: postgres:16.6-alpine
Configuration:
services:
postgres:
image: postgres:16.6-alpine
container_name: postgres
environment:
- POSTGRES_USER=postgres
- POSTGRES_PASSWORD_FILE=/run/secrets/postgres_password
- POSTGRES_DB=myapp
secrets:
- postgres_password
ports:
- "5432:5432"
volumes:
- postgres-data:/var/lib/postgresql/data
- ./init:/docker-entrypoint-initdb.d
healthcheck:
test: ["CMD-SHELL", "pg_isready -U postgres"]
interval: 10s
timeout: 3s
retries: 3
deploy:
resources:
limits:
cpus: '1'
memory: 2G
networks:
- backend
security_opt:
- no-new-privileges:true
restart: unless-stopped
Extensions: Match Azure PostgreSQL Flexible Server extensions:
CREATE EXTENSION IF NOT EXISTS "uuid-ossp";
CREATE EXTENSION IF NOT EXISTS "pg_trgm";
CREATE EXTENSION IF NOT EXISTS "pgcrypto";
Image: mysql:9.2
Configuration:
services:
mysql:
image: mysql:9.2
container_name: mysql
environment:
- MYSQL_ROOT_PASSWORD_FILE=/run/secrets/mysql_root_password
- MYSQL_DATABASE=myapp
- MYSQL_USER=appuser
- MYSQL_PASSWORD_FILE=/run/secrets/mysql_password
secrets:
- mysql_root_password
- mysql_password
ports:
- "3306:3306"
volumes:
- mysql-data:/var/lib/mysql
- ./init:/docker-entrypoint-initdb.d
healthcheck:
test: ["CMD", "mysqladmin", "ping", "-h", "localhost", "-u", "root", "-p$$MYSQL_ROOT_PASSWORD"]
interval: 10s
timeout: 3s
retries: 3
deploy:
resources:
limits:
cpus: '1'
memory: 2G
networks:
- backend
security_opt:
- no-new-privileges:true
restart: unless-stopped
Image: redis:7.4-alpine
Configuration:
services:
redis:
image: redis:7.4-alpine
container_name: redis
command: >
redis-server
--appendonly yes
--requirepass ${REDIS_PASSWORD}
--maxmemory 512mb
--maxmemory-policy allkeys-lru
ports:
- "6379:6379"
volumes:
- redis-data:/data
healthcheck:
test: ["CMD", "redis-cli", "--raw", "incr", "ping"]
interval: 10s
timeout: 3s
retries: 3
deploy:
resources:
limits:
cpus: '0.5'
memory: 512M
networks:
- backend
security_opt:
- no-new-privileges:true
restart: unless-stopped
OpenTelemetry-compatible observability stack
services:
jaeger:
image: jaegertracing/all-in-one:latest
container_name: jaeger
ports:
- "16686:16686" # UI
- "14268:14268" # HTTP collector
- "4317:4317" # OTLP gRPC
- "4318:4318" # OTLP HTTP
environment:
- COLLECTOR_OTLP_ENABLED=true
networks:
- monitoring
restart: unless-stopped
grafana:
image: grafana/grafana:latest
container_name: grafana
ports:
- "3001:3000"
environment:
- GF_SECURITY_ADMIN_PASSWORD=admin
volumes:
- grafana-data:/var/lib/grafana
networks:
- monitoring
restart: unless-stopped
services:
# Application Services
frontend:
build: ./frontend
ports: ["3000:3000"]
networks: [frontend]
depends_on:
backend:
condition: service_healthy
backend:
build: ./backend
ports: ["8080:8080"]
networks: [frontend, backend]
depends_on:
sqlserver:
condition: service_healthy
redis:
condition: service_started
azurite:
condition: service_started
# Databases
sqlserver:
image: mcr.microsoft.com/mssql/server:2025-latest
environment:
- ACCEPT_EULA=Y
- MSSQL_PID=Developer
- MSSQL_SA_PASSWORD=${MSSQL_SA_PASSWORD}
ports: ["1433:1433"]
volumes: [sqlserver-data:/var/opt/mssql]
networks: [backend]
healthcheck:
test: ["CMD-SHELL", "/opt/mssql-tools18/bin/sqlcmd -S localhost -U sa -P $$MSSQL_SA_PASSWORD -Q 'SELECT 1' -C"]
interval: 10s
postgres:
image: postgres:16.6-alpine
environment:
- POSTGRES_PASSWORD=${POSTGRES_PASSWORD}
ports: ["5432:5432"]
volumes: [postgres-data:/var/lib/postgresql/data]
networks: [backend]
healthcheck:
test: ["CMD-SHELL", "pg_isready"]
interval: 10s
# Cache
redis:
image: redis:7.4-alpine
command: redis-server --requirepass ${REDIS_PASSWORD}
ports: ["6379:6379"]
volumes: [redis-data:/data]
networks: [backend]
# Storage
azurite:
image: mcr.microsoft.com/azure-storage/azurite:latest
command: azurite --blobHost 0.0.0.0 --queueHost 0.0.0.0 --tableHost 0.0.0.0 --loose
ports: ["10000:10000", "10001:10001", "10002:10002"]
volumes: [azurite-data:/data]
networks: [backend]
# NoSQL
cosmosdb:
image: mcr.microsoft.com/cosmosdb/linux/azure-cosmos-emulator:vnext-preview
ports: ["8081:8081"]
volumes: [cosmos-data:/data/db]
networks: [backend]
# Monitoring
jaeger:
image: jaegertracing/all-in-one:latest
ports: ["16686:16686", "4317:4317"]
networks: [monitoring]
networks:
frontend:
driver: bridge
backend:
driver: bridge
internal: true
monitoring:
driver: bridge
volumes:
sqlserver-data:
postgres-data:
redis-data:
azurite-data:
cosmos-data:
latestWhen moving from Azure to Docker emulators:
development
This skill should be used when the user asks to train, debug, scale, or improve ML models. PROACTIVELY activate for: (1) PyTorch, TensorFlow/Keras, JAX, Flax, Hugging Face Trainer/Accelerate training loops, (2) distributed training, DDP/FSDP/DeepSpeed, TPU/GPU setup, (3) mixed precision AMP/bf16, gradient accumulation, checkpointing, seeding, (4) overfitting, imbalance, loss functions, regularization, LR schedules, warmup, (5) memory optimization, gradient checkpointing, offloading, quantization-aware training. Provides: reproducible training best practices across deep learning and classical ML.
development
This skill should be used when the user asks to productionize, track, version, govern, monitor, or automate ML systems. PROACTIVELY activate for: (1) MLflow, Weights & Biases, Neptune, Comet, ClearML experiment tracking, (2) model registry, model versioning, artifact lineage, reproducibility, (3) Kubeflow, SageMaker Pipelines, Vertex AI Pipelines, Azure ML pipelines, Databricks workflows, (4) CI/CD, continuous training/evaluation, A/B tests, canary/shadow deployments, (5) drift detection, model monitoring, data validation, responsible AI governance. Provides: end-to-end MLOps architecture and operational safeguards.
development
This skill should be used when the user asks to optimize, export, serve, compress, or accelerate ML inference. PROACTIVELY activate for: (1) latency, throughput, p95/p99, batching, concurrency, KV cache, memory, or cost issues, (2) quantization INT8/INT4, GPTQ, AWQ, bitsandbytes, pruning, sparsity, distillation, (3) ONNX export, ONNX Runtime, TensorRT, TorchScript, torch.compile, XLA, OpenVINO, Core ML, TFLite, (4) Triton, TorchServe, TF Serving, BentoML, Seldon, KServe configuration, (5) edge deployment, CPU/GPU/TPU/Inferentia serving. Provides: hardware-aware inference optimization and safe benchmarking.
testing
This skill should be used when the user asks to tune hyperparameters, run sweeps, optimize search spaces, or use AutoML. PROACTIVELY activate for: (1) Optuna, Ray Tune, FLAML, AutoGluon, Hyperopt, Nevergrad, KerasTuner, W&B sweeps, (2) grid search, random search, Bayesian optimization, TPE, Gaussian processes, evolutionary search, (3) ASHA, Hyperband, successive halving, multi-fidelity optimization, population-based training, (4) learning-rate finder, batch-size search, early stopping, pruning, (5) reproducible sweep design and experiment analysis. Provides: budget-aware hyperparameter search strategy.