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aws-messaging-and-streaming

Guides selection and use of AWS messaging and streaming services.

1|Updated Aug 1, 2024
Search Tags:#messaging#aws#eventbridge#sqs#sns#kinesis#msk
One-click install
npx skills add https://github.com/obispobruno/dotfiles --skill aws-messaging-and-streaming-obispobruno
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: aws-messaging-and-streaming
Source: https://github.com/obispobruno/dotfiles/tree/main/dot_agents/skills/aws-messaging-and-streaming
Command: npx skills add https://github.com/obispobruno/dotfiles --skill aws-messaging-and-streaming-obispobruno

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Choosing between AWS messaging and streaming services is confusing because SQS, SNS, EventBridge, Amazon MQ, Kinesis Data Streams, Data Firehose, Managed Service for Apache Flink, and MSK overlap in capability. This Skill explains the messaging versus streaming patterns, maps workloads to the right service, and routes customer communication questions (email, SMS, WhatsApp, voice, push) to the correct specialized skill. ## Core Features & Use Cases - Pattern Selection: Explains the differences between messaging (decoupled, consumed-once) and streaming (durable, replayable, ordered) so you can match the pattern to your workload. - Service Comparison Tables: Compares SQS, SNS, EventBridge, Amazon MQ, Kinesis Data Streams, Data Firehose, Managed Flink, and MSK by best-fit use case and key differentiator. - Customer Communication Routing: Identifies which AWS service owns each application-to-person channel (Amazon SES for email, End User Messaging for SMS/WhatsApp/voice/push) and defers to the specialized skill. - Integration Gotchas: Documents common pitfalls such as SQS system vs. user message attributes, SNS-to-Firehose newline handling, DLQ queue policies, and Secrets Manager credential requirements. - Use Case: When designing an event-driven architecture, ask which service fits a fan-out notification workload and receive a grounded recommendation with integration caveats. ## Quick Start Ask which AWS service to use for decoupling microservices with a task queue and how it differs from Kinesis streaming.

Frequently Asked Questions about aws-messaging-and-streaming

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I choose between SQS, SNS, and EventBridge?▼

Use SQS for task queues and decoupling with competing consumers, SNS for fan-out pub/sub notifications to multiple subscribers, and EventBridge for content-based event routing with schema registry and 200+ AWS source integrations.

What is the difference between messaging and streaming on AWS?▼

Messaging deletes messages after consumption and distributes work among competing consumers, while streaming retains records for replay with strict per-partition ordering and independent readers. Messaging fits task queues; streaming fits event sourcing, analytics, and change data capture.

Which AWS service should I use for Kafka workloads?▼

Use Amazon MSK for Kafka-native workloads requiring Apache Kafka API compatibility and ecosystem connectors. Its Express brokers offer higher throughput and faster scaling than Standard brokers.

Which AWS service owns SMS and WhatsApp customer messaging?▼

AWS End User Messaging owns application-to-person channels: End User Messaging SMS handles SMS, MMS, RCS, and voice, while End User Messaging Social handles WhatsApp. Amazon SES owns email. These are separate from application-to-application messaging services.

Why is my EventBridge DLQ silently dropping messages?▼

Attaching a DLQ alone is not enough; the DLQ needs a queue policy allowing sqs:SendMessage for the events.amazonaws.com service principal scoped with aws:SourceArn to the rule ARN. The same pattern applies to SNS subscription DLQs.

When should I not use this skill for MSK or Flink questions?▼

For detailed MSK or Managed Service for Apache Flink questions, use the service-specific skills or official AWS documentation instead. This skill covers general pattern selection and defers detailed service configuration to specialized sources.

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