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Use when working with Apache Flink, Managed Service for Apache Flink, streaming, stream-processing, real-time data, Kafka, or Kinesis.\"\n---\n\n\u003C!-- Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.\n     SPDX-License-Identifier: Apache-2.0 -->\n\n# Managed Service for Apache Flink Skill\n\n## Overview\n\nThis skill provides comprehensive guidance for developing, optimizing, and operating Apache Flink applications on AWS Managed Service for Apache Flink. It is designed to improve Apache Flink onboarding and improve operational excellence.\n\n## Disclaimer\n\nAll code generated by this skill is AI-assisted and should be thoroughly reviewed, tested, and validated by users before being used in production environments. AI-generated code may contain errors, security vulnerabilities, or suboptimal patterns that require human judgment to identify and correct. Any code changes adopted from this skill should be tagged with `generated by Managed Service for Apache Flink Kiro Power` in code comments or commit messages to clearly indicate when generated changes were adopted.\n\n## Key Problems Solved\n\n1. **New Customer Onboarding**: Overcome the steep learning curve for Flink's Java-centric development model\n2. **Existing Customer Optimization**: Systematic review and improvement of Flink applications to align to best practices\n3. **Operational Excellence**: Integrated troubleshooting and monitoring using automated tools with CloudWatch and Managed Service for Apache Flink APIs\n4. **Migrating \u002F upgrading to Flink 2**: Systematic review and upgrade from Flink 1.x apps to Flink 2.x apps to handle migrations to 2.x with breaking changes\n\n## Reference Files\n\nLoad these files as needed based on the user's task:\n\n- [Core Managed Service for Apache Flink Development Workflow](steering\u002Fcore-workflow.md) — how to approach user interaction, development, and testing\n- [Environment Setup](steering\u002Fenvironment-setup.md) — set up a local dev environment\n- [Dependency Management](steering\u002Fdependency-management.md) — Maven pom.xml dependencies for new projects\n- [Best Practices](steering\u002Fbest-practices.md) — Flink best practices for new apps\n- [Managed Service for Apache Flink Overview and Concepts](steering\u002Fmsf-overview.md) — Managed Service for Apache Flink-specific optimizations and constraints\n- [Flink 2.x Migration Guide](steering\u002Fflink-2x-migration.md) — upgrading from Flink 1.x to 2.x, including state compatibility\n- [Resource Optimization](steering\u002Fresource-optimization.md) — KPU sizing, operator parallelism tuning, configuration overrides, and checkpoint resource impact\n- [Job Graph Architecture](steering\u002Fjob-graph-architecture.md) — job graph optimization, monolith anti-pattern, high fan-out, and operator-to-task-slot mapping\n- [Monitoring and Metrics](steering\u002Fmonitoring-and-metrics.md) — CloudWatch metrics analysis, recommended alarms, and custom metrics emission\n- [Logging Configuration](steering\u002Flogging-configuration.md) — logging best practices, Log4j2 configuration, and rate-limited logging patterns for Managed Service for Apache Flink\n- [Kinesis Source \u002F Sink Development](steering\u002Fkinesis-connector-guide.md) — Kinesis connector-specific guidance\n\n## General Guidance\n\n- Don't get started until you confirm the user's goals and use case\n- Don't make changes unless the user asks you to\n- When developing code, use this skill's reference files as guidance first, followed by general knowledge\n\n## CRITICAL: Required Reading for All Flink Development\n\n**BEFORE writing ANY Flink code, you MUST read these files:**\n\n0. **ALWAYS read [core-workflow.md](steering\u002Fcore-workflow.md) first** — Contains essential steps for development\n1. **ALWAYS read [best-practices.md](steering\u002Fbest-practices.md) second** — Contains essential Managed Service for Apache Flink patterns, anti-patterns, serialization guidance, state management, and configuration separation\n\n**These are NOT optional — you must read them before generating any code.**\n\n### Working with Multiple Reference Files\n\nWhen creating Flink applications, **always reference multiple relevant files together**:\n\n1. **Start with best-practices.md** — Read this FIRST for all development work\n2. **Then read dependency-management.md** — For correct Maven dependencies when building new Flink apps\n3. **Then read connector-specific guides** (e.g., kinesis-connector-guide.md) for API usage whenever making changes to or evaluating app's source\u002Fsink configs or making new apps\n4. **For resource sizing and scaling** — Read resource-optimization.md for KPU sizing, parallelism tuning, and checkpoint impact on resources\n5. **For job graph design** — Read 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Covers IAM auth, multi-tenant patterns, MySQL-to-DSQL and PostgreSQL-to-DSQL schema conversion, FK replacement code generation, OCC retry patterns, ORM migration (Django\u002FHibernate\u002FRails), DDL operations, query plan explainability, SQL compatibility validation, and bulk data loading. Triggers on phrases like: DSQL, Aurora DSQL, create DSQL table, DSQL schema, migrate to DSQL, distributed SQL database, serverless PostgreSQL-compatible database, DSQL query plan, DSQL EXPLAIN ANALYZE, why is my DSQL query slow, DSQL foreign key, DSQL OCC retry, DSQL multi-region, load into DSQL, load CSV into DSQL, bulk load DSQL, aurora-dsql-loader.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[551,554,555,558,561],{"name":552,"slug":553,"type":16},"Aurora","aurora",{"name":24,"slug":25,"type":16},{"name":556,"slug":557,"type":16},"Database","database",{"name":559,"slug":560,"type":16},"Serverless","serverless",{"name":562,"slug":563,"type":16},"SQL","sql","2026-07-12T08:36:45.053393",{"slug":566,"name":567,"fn":547,"description":548,"org":568,"tags":569,"stars":541,"repoUrl":542,"updatedAt":574},"aurora-dsql","aurora dsql",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[570,571,572,573],{"name":24,"slug":25,"type":16},{"name":556,"slug":557,"type":16},{"name":559,"slug":560,"type":16},{"name":562,"slug":563,"type":16},"2026-07-12T08:36:42.694299",{"slug":576,"name":577,"fn":547,"description":548,"org":578,"tags":579,"stars":541,"repoUrl":542,"updatedAt":587},"aws-dsql","aws dsql",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[580,581,582,585,586],{"name":24,"slug":25,"type":16},{"name":556,"slug":557,"type":16},{"name":583,"slug":584,"type":16},"Migration","migration",{"name":559,"slug":560,"type":16},{"name":562,"slug":563,"type":16},"2026-07-12T08:36:38.584057",{"slug":589,"name":590,"fn":547,"description":548,"org":591,"tags":592,"stars":541,"repoUrl":542,"updatedAt":600},"distributed-postgres","distributed postgres",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[593,594,595,598,599],{"name":24,"slug":25,"type":16},{"name":556,"slug":557,"type":16},{"name":596,"slug":597,"type":16},"PostgreSQL","postgresql",{"name":559,"slug":560,"type":16},{"name":562,"slug":563,"type":16},"2026-07-12T08:36:46.530743",{"slug":602,"name":603,"fn":547,"description":548,"org":604,"tags":605,"stars":541,"repoUrl":542,"updatedAt":610},"distributed-sql","distributed sql",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[606,607,608,609],{"name":24,"slug":25,"type":16},{"name":556,"slug":557,"type":16},{"name":559,"slug":560,"type":16},{"name":562,"slug":563,"type":16},"2026-07-12T08:36:48.104182",{"slug":612,"name":612,"fn":547,"description":548,"org":613,"tags":614,"stars":541,"repoUrl":542,"updatedAt":620},"dsql",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[615,616,617,618,619],{"name":24,"slug":25,"type":16},{"name":556,"slug":557,"type":16},{"name":583,"slug":584,"type":16},{"name":559,"slug":560,"type":16},{"name":562,"slug":563,"type":16},"2026-07-12T08:36:36.374512",{"slug":622,"name":622,"fn":623,"description":624,"org":625,"tags":626,"stars":639,"repoUrl":640,"updatedAt":641},"cost-efficiency-analyzer","analyze cost efficiency and expenses","Analyzes cost structure, cost efficiency, and expense management from P&L data. Use when the user asks about costs, expenses, COGS, operating expenses, cost ratios, cost control, spending efficiency, margin compression from cost side, or wants to understand where money is going. Also use for \"are we spending too much\", \"cost breakdown\", \"expense analysis\", or \"how efficient are our operations\". NOT for revenue or top-line analysis.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[627,630,633,636],{"name":628,"slug":629,"type":16},"Accounting","accounting",{"name":631,"slug":632,"type":16},"Analytics","analytics",{"name":634,"slug":635,"type":16},"Cost Optimization","cost-optimization",{"name":637,"slug":638,"type":16},"Finance","finance",3176,"https:\u002F\u002Fgithub.com\u002Fawslabs\u002Fagentcore-samples","2026-07-12T08:40:03.29555",{"slug":643,"name":643,"fn":644,"description":645,"org":646,"tags":647,"stars":639,"repoUrl":640,"updatedAt":656},"executive-financial-briefing","generate executive financial briefings","Generates a concise executive-level financial briefing or summary suitable for a CEO, CFO, or board presentation. Use when the user asks for a summary, briefing, executive summary, board update, financial overview, financial health check, or \"how is the business doing\". Covers the full P&L picture in one page. Also use for \"give me the highlights\", \"what do I need to know\", or \"quick financial update\".",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[648,649,650,653],{"name":24,"slug":25,"type":16},{"name":637,"slug":638,"type":16},{"name":651,"slug":652,"type":16},"Management","management",{"name":654,"slug":655,"type":16},"Reporting","reporting","2026-07-12T08:40:02.066471",{"slug":658,"name":658,"fn":659,"description":660,"org":661,"tags":662,"stars":639,"repoUrl":640,"updatedAt":671},"multi-quarter-trend-analysis","analyze multi-quarter financial trends","Analyzes financial trends across multiple quarters by comparing P&L metrics over time. Use when the user wants to see trends, patterns, trajectories, or directional movement across 3 or more quarters. Also use for \"how are we trending\", \"show me the trend\", \"track performance over time\", \"quarter over quarter comparison across all quarters\", or any multi-period longitudinal analysis.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[663,664,665,668],{"name":631,"slug":632,"type":16},{"name":637,"slug":638,"type":16},{"name":666,"slug":667,"type":16},"Financial Statements","financial-statements",{"name":669,"slug":670,"type":16},"Variance Analysis","variance-analysis","2026-07-12T08:40:00.79141",{"slug":673,"name":673,"fn":674,"description":675,"org":676,"tags":677,"stars":639,"repoUrl":640,"updatedAt":686},"pdf","process and manipulate PDF documents","Use this skill whenever the user wants to do anything with PDF files. This includes reading or extracting text\u002Ftables from PDFs, combining or merging multiple PDFs into one, splitting PDFs apart, rotating pages, adding watermarks, creating new PDFs, filling PDF forms, encrypting\u002Fdecrypting PDFs, extracting images, and OCR on scanned PDFs to make them searchable. If the user mentions a .pdf file or asks to produce one, use this skill.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[678,681,684],{"name":679,"slug":680,"type":16},"Automation","automation",{"name":682,"slug":683,"type":16},"Documents","documents",{"name":685,"slug":673,"type":16},"PDF","2026-07-12T08:41:44.135656",{"slug":688,"name":688,"fn":689,"description":690,"org":691,"tags":692,"stars":639,"repoUrl":640,"updatedAt":701},"quarterly-kpi-calculator","calculate quarterly financial KPIs","Calculates quarterly financial KPIs from P&L data. P&L figures can be provided directly by the user or fetched from the financial data MCP server. Use when the user wants KPI calculations such as Gross Margin %, EBITDA Margin %, Operating Expense Ratio, or Revenue Growth % QoQ. Also use for quarterly performance review, P&L analysis, or interpreting financial ratios against benchmarks.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[693,694,697,698],{"name":628,"slug":629,"type":16},{"name":695,"slug":696,"type":16},"Data Analysis","data-analysis",{"name":637,"slug":638,"type":16},{"name":699,"slug":700,"type":16},"KPI","kpi","2026-07-12T08:39:59.54971",150,{"items":704,"total":712},[705],{"slug":4,"name":4,"fn":5,"description":6,"org":706,"tags":707,"stars":26,"repoUrl":27,"updatedAt":28},{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[708,709,710,711],{"name":24,"slug":25,"type":16},{"name":18,"slug":19,"type":16},{"name":21,"slug":22,"type":16},{"name":14,"slug":15,"type":16},1]