[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6HAMD5GDGTXGRPRZD4PWYFZ":3,"skill-same:01M6HAMD5GDGTXGRPRZD4PWYFZ":53},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":18,"publishedAt":24,"linkOnly":25,"markdownContent":26,"markdownBody":27,"frontMatter":28,"refName":31,"commitSha":32,"skillDirectory":33,"forksCount":14,"repositoryHtmlUrl":34,"repositoryHomepageUrl":6,"ownerHtmlUrl":35,"ownerBlogUrl":36,"ownerDescription":37,"updatedAt":38,"install":39,"resources":52},"01M6HAMD5GDGTXGRPRZD4PWYFZ","serverless",null,"Serverless computing architecture","NeuralBlitz\u002FMito","NeuralBlitz","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F79354388?v=4","01M6H8T2TFH477HRS0KTSTKR2E","David Riggs","01M6H8T2YQQDXPYM092P670Z21",0,"MIT","https:\u002F\u002Fgithub.com\u002FNeuralBlitz\u002FMito\u002Fblob\u002Fmain\u002F.opencode\u002Fskills\u002Fserverless\u002FSKILL.md",[],[5,19,20,21,22,23],"architecture","developer","devops","opencode","engineer","2026-11-10 10:12:30",false,"---\nname: serverless\ndescription: Serverless computing architecture\nlicense: MIT\ncompatibility: opencode\nmetadata:\n  audience: developer, devops-engineer\n  category: devops\n---\n\n## What I do\n\n- Design serverless architectures\n- Build functions-as-a-service applications\n- Implement event-driven systems\n- Configure serverless databases and storage\n- Optimize function performance and costs\n- Build serverless CI\u002FCD pipelines\n\n## When to use me\n\n- When building event-driven applications\n- When scaling is unpredictable\n- When minimizing operational overhead\n- When implementing microservices\n- When building data processing pipelines\n- When creating APIs quickly\n\n## Key Concepts\n\n### AWS Lambda\n\n```python\n# Lambda handler\nimport json\nimport boto3\n\ndef lambda_handler(event, context):\n    # Parse the event\n    http_method = event['httpMethod']\n    path = event['path']\n    \n    # Business logic\n    if http_method == 'GET' and path == '\u002Fusers':\n        return {\n            'statusCode': 200,\n            'body': json.dumps({'users': []}),\n            'headers': {'Content-Type': 'application\u002Fjson'}\n        }\n    \n    return {\n        'statusCode': 404,\n        'body': json.dumps({'error': 'Not found'})\n    }\n\n# Lambda layers for dependencies\n# Layer structure:\n# python\u002Flib\u002Fpython3.11\u002Fsite-packages\u002F\n```\n\n### Serverless Framework\n\n```yaml\n# serverless.yml\nservice: my-serverless-app\n\nprovider:\n  name: aws\n  runtime: python3.11\n  stage: ${opt:stage, 'dev'}\n  region: ${opt:region, 'us-east-1'}\n  \n  environment:\n    TABLE_NAME: !Ref UsersTable\n    STRIPE_KEY: ${env:STRIPE_KEY}\n    \n  iam:\n    role:\n      statements:\n        - Effect: Allow\n          Action:\n            - dynamodb:Query\n            - dynamodb:Scan\n          Resource: !GetAtt UsersTable.Arn\n\nfunctions:\n  users:\n    handler: handler.get_users\n    events:\n      - http:\n          path: \u002Fusers\n          method: get\n          cors: true\n      - http:\n          path: \u002Fusers\u002F{userId}\n          method: get\n          cors: true\n          \n  processOrder:\n    handler: handler.process_order\n    events:\n      - sqs:\n          arn: !GetAtt OrdersQueue.Arn\n          batchSize: 10\n          \n  uploadHandler:\n    handler: handler.handle_upload\n    events:\n      - s3:\n          bucket: uploads-${self:provider.stage}\n          event: s3:ObjectCreated:*\n          rules:\n            - prefix: images\u002F\n\nresources:\n  Resources:\n    UsersTable:\n      Type: AWS::DynamoDB::Table\n      Properties:\n        TableName: users-${self:provider.stage}\n        BillingMode: PAY_PER_REQUEST\n        AttributeDefinitions:\n          - AttributeName: userId\n            AttributeType: S\n        KeySchema:\n          - AttributeName: userId\n            KeyType: HASH\n```\n\n### Azure Functions\n\n```javascript\n\u002F\u002F Azure Function with triggers\nmodule.exports = async function (context, req) {\n    context.log('JavaScript HTTP trigger function processed a request.');\n    \n    const name = (req.query.name || (req.body && req.body.name));\n    \n    if (name) {\n        context.res = {\n            status: 200,\n            body: { message: `Hello, ${name}` }\n        };\n    } else {\n        context.res = {\n            status: 400,\n            body: { error: \"Please pass a name\" }\n        };\n    }\n};\n\n\u002F\u002F bindings.json\n{\n  \"bindings\": [\n    {\n      \"name\": \"req\",\n      \"type\": \"httpTrigger\",\n      \"direction\": \"in\",\n      \"authLevel\": \"function\"\n    },\n    {\n      \"name\": \"$return\",\n      \"type\": \"http\",\n      \"direction\": \"out\"\n    }\n  ]\n}\n```\n\n### GCP Cloud Functions\n\n```javascript\n\u002F\u002F Cloud Function 2nd Gen\nconst { CloudEvent, CloudFunction } = require('@google-cloud\u002Ffunctions-framework');\n\nexports.processEvent = CloudEvent(async (cloudEvent) => {\n  const data = cloudEvent.data;\n  \n  console.log('Event ID:', cloudEvent.id);\n  console.log('Event Type:', cloudEvent.type);\n  console.log('Data:', data);\n  \n  \u002F\u002F Process the event\n  await processData(data);\n  \n  return { success: true };\n});\n\n\u002F\u002F HTTP Function\nexports.httpFunction = async (req, res) => {\n  const name = req.query.name || req.body.name || 'World';\n  res.send(`Hello, ${name}!`);\n};\n```\n\n### Event-Driven Architecture\n\n```\n┌─────────────┐     ┌─────────────┐     ┌─────────────┐\n│    S3       │────►│   Lambda    │────►│   DynamoDB  │\n│  (Upload)    │     │  (Process)  │     │   (Store)   │\n└─────────────┘     └─────────────┘     └─────────────┘\n                          │\n                          ▼\n                   ┌─────────────┐\n                   │    SNS     │\n                   │  (Notify)  │\n                   └─────────────┘\n```\n\n### Serverless Databases\n\n```python\n# AWS DynamoDB access\nimport boto3\nfrom boto3.dynamodb.conditions import Key\n\ndynamodb = boto3.resource('dynamodb')\ntable = dynamodb.Table('users')\n\ndef get_user(user_id):\n    response = table.get_item(Key={'user_id': user_id})\n    return response.get('Item')\n\ndef query_users_by_org(org_id):\n    response = table.query(\n        KeyConditionExpression=Key('org_id').eq(org_id)\n    )\n    return response['Items']\n```\n\n### Cold Start Mitigation\n\n- Provisioned concurrency\n- Keep functions warm with scheduled invocations\n- Use lighter dependencies\n- Minimize function code size\n- Pre-compile dependencies\n- Use ARM\u002FGraviton2 for better performance\n\n### Cost Optimization\n\n- Right-size memory allocation\n- Use reserved capacity\n- Optimize execution time\n- Remove unnecessary dependencies\n- Use native libraries instead of AWS SDK\n- Batch operations where possible\n","## What I do\n\n- Design serverless architectures\n- Build functions-as-a-service applications\n- Implement event-driven systems\n- Configure serverless databases and storage\n- Optimize function performance and costs\n- Build serverless CI\u002FCD pipelines\n\n## When to use me\n\n- When building event-driven applications\n- When scaling is unpredictable\n- When minimizing operational overhead\n- When implementing microservices\n- When building data processing pipelines\n- When creating APIs quickly\n\n## Key Concepts\n\n### AWS Lambda\n\n```python\n# Lambda handler\nimport json\nimport boto3\n\ndef lambda_handler(event, context):\n    # Parse the event\n    http_method = event['httpMethod']\n    path = event['path']\n    \n    # Business logic\n    if http_method == 'GET' and path == '\u002Fusers':\n        return {\n            'statusCode': 200,\n            'body': json.dumps({'users': []}),\n            'headers': {'Content-Type': 'application\u002Fjson'}\n        }\n    \n    return {\n        'statusCode': 404,\n        'body': json.dumps({'error': 'Not found'})\n    }\n\n# Lambda layers for dependencies\n# Layer structure:\n# python\u002Flib\u002Fpython3.11\u002Fsite-packages\u002F\n```\n\n### Serverless Framework\n\n```yaml\n# serverless.yml\nservice: my-serverless-app\n\nprovider:\n  name: aws\n  runtime: python3.11\n  stage: ${opt:stage, 'dev'}\n  region: ${opt:region, 'us-east-1'}\n  \n  environment:\n    TABLE_NAME: !Ref UsersTable\n    STRIPE_KEY: ${env:STRIPE_KEY}\n    \n  iam:\n    role:\n      statements:\n        - Effect: Allow\n          Action:\n            - dynamodb:Query\n            - dynamodb:Scan\n          Resource: !GetAtt UsersTable.Arn\n\nfunctions:\n  users:\n    handler: handler.get_users\n    events:\n      - http:\n          path: \u002Fusers\n          method: get\n          cors: true\n      - http:\n          path: \u002Fusers\u002F{userId}\n          method: get\n          cors: true\n          \n  processOrder:\n    handler: handler.process_order\n    events:\n      - sqs:\n          arn: !GetAtt OrdersQueue.Arn\n          batchSize: 10\n          \n  uploadHandler:\n    handler: handler.handle_upload\n    events:\n      - s3:\n          bucket: uploads-${self:provider.stage}\n          event: s3:ObjectCreated:*\n          rules:\n            - prefix: images\u002F\n\nresources:\n  Resources:\n    UsersTable:\n      Type: AWS::DynamoDB::Table\n      Properties:\n        TableName: users-${self:provider.stage}\n        BillingMode: PAY_PER_REQUEST\n        AttributeDefinitions:\n          - AttributeName: userId\n            AttributeType: S\n        KeySchema:\n          - AttributeName: userId\n            KeyType: HASH\n```\n\n### Azure Functions\n\n```javascript\n\u002F\u002F Azure Function with triggers\nmodule.exports = async function (context, req) {\n    context.log('JavaScript HTTP trigger function processed a request.');\n    \n    const name = (req.query.name || (req.body && req.body.name));\n    \n    if (name) {\n        context.res = {\n            status: 200,\n            body: { message: `Hello, ${name}` }\n        };\n    } else {\n        context.res = {\n            status: 400,\n            body: { error: \"Please pass a name\" }\n        };\n    }\n};\n\n\u002F\u002F bindings.json\n{\n  \"bindings\": [\n    {\n      \"name\": \"req\",\n      \"type\": \"httpTrigger\",\n      \"direction\": \"in\",\n      \"authLevel\": \"function\"\n    },\n    {\n      \"name\": \"$return\",\n      \"type\": \"http\",\n      \"direction\": \"out\"\n    }\n  ]\n}\n```\n\n### GCP Cloud Functions\n\n```javascript\n\u002F\u002F Cloud Function 2nd Gen\nconst { CloudEvent, CloudFunction } = require('@google-cloud\u002Ffunctions-framework');\n\nexports.processEvent = CloudEvent(async (cloudEvent) => {\n  const data = cloudEvent.data;\n  \n  console.log('Event ID:', cloudEvent.id);\n  console.log('Event Type:', cloudEvent.type);\n  console.log('Data:', data);\n  \n  \u002F\u002F Process the event\n  await processData(data);\n  \n  return { success: true };\n});\n\n\u002F\u002F HTTP Function\nexports.httpFunction = async (req, res) => {\n  const name = req.query.name || req.body.name || 'World';\n  res.send(`Hello, ${name}!`);\n};\n```\n\n### Event-Driven Architecture\n\n```\n┌─────────────┐     ┌─────────────┐     ┌─────────────┐\n│    S3       │────►│   Lambda    │────►│   DynamoDB  │\n│  (Upload)    │     │  (Process)  │     │   (Store)   │\n└─────────────┘     └─────────────┘     └─────────────┘\n                          │\n                          ▼\n                   ┌─────────────┐\n                   │    SNS     │\n                   │  (Notify)  │\n                   └─────────────┘\n```\n\n### Serverless Databases\n\n```python\n# AWS DynamoDB access\nimport boto3\nfrom boto3.dynamodb.conditions import Key\n\ndynamodb = boto3.resource('dynamodb')\ntable = dynamodb.Table('users')\n\ndef get_user(user_id):\n    response = table.get_item(Key={'user_id': user_id})\n    return response.get('Item')\n\ndef query_users_by_org(org_id):\n    response = table.query(\n        KeyConditionExpression=Key('org_id').eq(org_id)\n    )\n    return response['Items']\n```\n\n### Cold Start Mitigation\n\n- Provisioned concurrency\n- Keep functions warm with scheduled invocations\n- Use lighter dependencies\n- Minimize function code size\n- Pre-compile dependencies\n- Use ARM\u002FGraviton2 for better performance\n\n### Cost Optimization\n\n- Right-size memory allocation\n- Use reserved capacity\n- Optimize execution time\n- Remove unnecessary dependencies\n- Use native libraries instead of AWS SDK\n- Batch operations where possible\n",{"name":5,"license":15,"metadata":29,"description":7,"compatibility":22},{"audience":30,"category":21},"developer, 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