MicrocosmWorksื—ื“ืฉื ื•ืช ื•ืชื›ื ื•ืŸ ืงื•ืกืžื•ืก ื“ื™ื’ื™ื˜ืœื™
ืื•ื“ื•ืชืฆื•ืจ ืงืฉืจ
MicrocosmWorksืžื—ื“ืฉื™ื ื•ืžืชื›ื ื ื™ื ืงื•ืกืžื•ืก ื“ื™ื’ื™ื˜ืœื™

ืžืกืคืงื™ื ืคืชืจื•ื ื•ืช IT ื—ืฉื•ื‘ื™ื. ืื ื• ื ืœื”ื‘ื™ื ืžื˜ื›ื ื•ืœื•ื’ื™ื”, ืื‘ื˜ื—ื” ื•ืขื•ื–ืจื™ื ืœืขืกืงื™ื ืœืฆืžื•ื— ื‘ืืžืฆืขื•ืช ืชืฉืชื™ืช IT ืืžื™ื ื” ื•ื—ื“ืฉื ื™ืช.

[email protected]
+91 7011868196
New Delhi, India

ืžืจื›ื– ืฆืžื™ื—ื” AI

ืžืจื›ื– AIื—ื“ืฉื ื•ืช ืกื˜ืืจื˜ืืคืžืื™ืฅ ืืจื’ื•ื ื™

ืคืชืจื•ื ื•ืช

ื›ืœ ื”ืคืชืจื•ื ื•ืชืืคืœื™ืงืฆื™ื•ืช ื‘ืจื™ืื•ืช ื•ื›ื•ืฉืจืคืœื˜ืคื•ืจืžืช ื•ื™ื“ืื• AIืคื™ืชื•ื— ืกื•ื›ื ื™ AI

ืžืฉืื‘ื™ื

ืชื•ื‘ื ื•ืชืžื“ืจื™ื›ื™ ืชืขืฉื™ื™ื”ืชื•ื›ื ื™ื•ืช ืžืงืจื” ืฉื™ืžื•ืฉืชื‘ื ื™ื•ืช ืืจื›ื™ื˜ืงื˜ื•ืจื”ืžื—ืงืจื™ ืžืงืจื”

ื—ื‘ืจื”

ืื•ื“ื•ืชื™ื ื•ืฆื•ืจ ืงืฉืจื”ืขื‘ื•ื“ื” ืฉืœื ื•

ืฉื™ืจื•ืชื™ื

ื™ื™ืขื•ืฅ ื“ื™ื’ื™ื˜ืœื™ืชืฉืชื™ืช ืขื ืŸืคื™ืชื•ื— SaaSืคื™ืชื•ื— AIื˜ื›ื ื•ืœื•ื’ื™ื™ืช ื•ื™ื“ืื•
ืคื™ืชื•ื— ERPื”ืชืืžื” ืื™ืฉื™ืช ืฉืœ Zohoืคื™ืชื•ื— Odooืื™ื ื˜ื’ืจืฆื™ื” ืฉืœ Salesforceืคื™ืชื•ื— CRM ืžื•ืชืื ืื™ืฉื™ืช
ืื™ื ื˜ื’ืจืฆื™ื” ืฉืœ QuickBooksืคืชืจื•ื ื•ืช IoTืคื™ืชื•ื— ื‘ืœื•ืงืฆ'ื™ื™ืŸ
ื™ื™ืขื•ืฅ ืกื™ื™ื‘ืจืชืžื™ื›ื” ื˜ื›ื ื™ืช - L3

ยฉ 2026 MicrocosmWorks. ื›ืœ ื”ื–ื›ื•ื™ื•ืช ืฉืžื•ืจื•ืช.

ืžื“ื™ื ื™ื•ืช ืคืจื˜ื™ื•ืชืชื ืื™ ืฉื™ืจื•ืช
ื—ื–ืจื” ืœืชื‘ื ื™ื•ืช ืืจื›ื™ื˜ืงื˜ื•ืจื”
ApplicationEnterprise

ืžื™ืงืจื•-ืฉื™ืจื•ืชื™ื ืžื•ื ื—ื™ ืื™ืจื•ืขื™ื

ื ืชืง ื”ื›ืœ. ืชืŸ ืœืฉื™ืจื•ืชื™ื ืœืชืงืฉืจ ื‘ืืžืฆืขื•ืช ืื™ืจื•ืขื™ื, ืœื ืฆื™ืคื™ื•ืช ืœื’ื‘ื™ ื–ืžื™ื ื•ืช ื”ื“ื“ื™ืช.

June 22, 2026
|
3 topics covered
ื“ื™ื•ืŸ ื‘ืืจื›ื™ื˜ืงื˜ื•ืจื” ื–ื•
event-driven-microservices.webp
Application
Category
Enterprise
Complexity
ืฉื™ืจื•ืชื™ื ืคื™ื ื ืกื™ื™ื, ืžืกื—ืจ ืืœืงื˜ืจื•ื ื™
Industries
3+
Technologies

ืžืชื™ ื–ื” ื ื—ื•ืฅ ืœืš

ื”ืžื•ื ื•ืœื™ืช ืฉืœืš ื”ื•ืคืš ืœืฆื•ื•ืืจ ื‘ืงื‘ื•ืง ื‘ืคืจื™ืกื” โ€” ื›ืœ ืฉื™ื ื•ื™ ื“ื•ืจืฉ ืชื™ืื•ื ื‘ื™ืŸ ืฆื•ื•ืชื™ื, ื•ื‘ืื’ ื‘ื—ื™ื•ื‘ ืžืฉื‘ื™ืช ืืช ื›ืœ ื”ื™ื™ืฉื•ื. ืœื—ืœื•ืคื™ืŸ, ืืชื” ื‘ื•ื ื” ืžืขืจื›ืช ื—ื“ืฉื” ืฉื‘ื” ื™ื›ื•ืœื•ืช ืฉื•ื ื•ืช ืžืชืคืชื—ื•ืช ื‘ืงืฆื‘ื™ื ืฉื•ื ื™ื: ื ื™ื”ื•ืœ ื”ื–ืžื ื•ืช ืžืฉืชื ื” ืžื“ื™ ืฉื‘ื•ืข, ืืš ืœื•ื’ื™ืงืช ื”ืžืœืื™ ืžืฉืชื ื” ืžื“ื™ ืจื‘ืขื•ืŸ. ืืชื” ื–ืงื•ืง ืœืฉื™ืจื•ืชื™ื ืฉื ื™ืชืŸ ืœืคืชื—, ืœืคืจื•ืก ื•ืœื”ืจื—ื™ื‘ ื‘ืื•ืคืŸ ืขืฆืžืื™, ื”ืžืชืงืฉืจื™ื ื‘ืืžืฆืขื•ืช ืื™ืจื•ืขื™ื ื•ืœื ื‘ืืžืฆืขื•ืช ืงืจื™ืื•ืช API ืกื™ื ื›ืจื•ื ื™ื•ืช ืฉื™ื•ืฆืจื•ืช ืฉืจืฉืจื•ืช ื›ืฉืœื™ื ืžื“ื•ืจื’ื™ื.

ืกืงื™ืจืช ืชื‘ื ื™ืช

Related Architecture Patterns

Explore more design patterns and system architectures

multi-tenant-saas-architecture.webp
Application

ืืจื›ื™ื˜ืงื˜ื•ืจืช SaaS ืžืจื•ื‘ืช ื“ื™ื™ืจื™ื

ื‘ืกื™ืก ืงื•ื“ ืื—ื“, ืžืื•ืช ื“ื™ื™ืจื™ื, ืืคืก ื“ืœื™ืคืช ื ืชื•ื ื™ื โ€” ื”ื™ืกื•ื“ ืฉืœ ื›ืœ ืขืกืง SaaS ืกืงืœื‘ื™ืœื™.

AdvancedView
ai-ml-pipeline-architecture.webp

ื”ืื ืืชื” ื–ืงื•ืง ืœืขื–ืจื” ื‘ื”ื˜ืžืขืช ืืจื›ื™ื˜ืงื˜ื•ืจื” ื–ื•?

ืื“ืจื™ื›ืœื™ื ืฉืœื ื• ื™ื›ื•ืœื™ื ืœืขื–ื•ืจ ืœืš ืœืขืฆื‘ ื•ืœื‘ื ื•ืช ืžืขืจื›ื•ืช ืชื•ืš ืฉื™ืžื•ืฉ ื‘ื“ืคื•ืก ื–ื” ืœื“ืจื™ืฉื•ืช ื”ืกืคืฆื™ืคื™ื•ืช ืฉืœืš.

ืฆืจื• ืงืฉืจ

ืžื™ืงืจื•-ืฉื™ืจื•ืชื™ื ืžื•ื ื—ื™ ืื™ืจื•ืขื™ื ืžืคืจืงื™ื ืžืขืจื›ืช ืœืฉื™ืจื•ืชื™ื ื”ื ื™ืชื ื™ื ืœืคืจื™ืกื” ืขืฆืžืื™ืช ื”ืžืชืงืฉืจื™ื ื‘ืขื™ืงืจ ื‘ืืžืฆืขื•ืช ืื™ืจื•ืขื™ื ืืกื™ื ื›ืจื•ื ื™ื™ื. ื›ืœ ืฉื™ืจื•ืช ืžื—ื–ื™ืง ื‘ื ืชื•ื ื™ื ืฉืœื•, ืžืคืจืกื domain events ื›ืืฉืจ ื”ืžืฆื‘ ืžืฉืชื ื”, ื•ืžื’ื™ื‘ ืœืื™ืจื•ืขื™ื ืžืฉื™ืจื•ืชื™ื ืื—ืจื™ื. ื–ื” ืžื‘ื˜ืœ ืฆื™ืžื•ื“ ื–ืžื ื™ โ€” Service A ืื™ื ื• ื–ืงื•ืง ืœ-Service B ืฉื™ื”ื™ื” ืคื•ืขืœ ื›ื“ื™ ืœื‘ืฆืข ืืช ืขื‘ื•ื“ืชื•. ื”ืชื‘ื ื™ืช ืžืฉืœื‘ืช CQRS (Command Query Responsibility Segregation) ืœื”ืคืจื“ืช ืžื•ื“ืœื™ ื›ืชื™ื‘ื” ื•ืงืจื™ืื”, event sourcing ืœืœื›ื™ื“ืช ื”ื™ืกื˜ื•ืจื™ื™ืช ืฉื™ื ื•ื™ื™ ืžืฆื‘ ืžืœืื”, ื•-saga orchestration ืœื ื™ื”ื•ืœ ื˜ืจื ื–ืงืฆื™ื•ืช ืžืจื•ื‘ื•ืช ืฉื™ืจื•ืชื™ื ืœืœื ืžื ืขื•ืœื™ื ืžื‘ื•ื–ืจื™ื.

ืืจื›ื™ื˜ืงื˜ื•ืจืช ื™ื™ื—ื•ืก

ื”ืืจื›ื™ื˜ืงื˜ื•ืจื” ืžืชืจื›ื–ืช ืกื‘ื™ื‘ event backbone (Kafka, EventBridge, ืื• NATS) ื”ืžื ืชื‘ domain events ื‘ื™ืŸ ืฉื™ืจื•ืชื™ื. ืœื›ืœ ืฉื™ืจื•ืช ื™ืฉ ืฉืœื•ืฉื” ื’ื‘ื•ืœื•ืช: command handler ื”ืžืขื‘ื“ ื‘ืงืฉื•ืช ื ื›ื ืกื•ืช ื•ืคื•ืœื˜ ืื™ืจื•ืขื™ื, query handler ื”ืžื’ื™ืฉ ื”ื™ื˜ืœื™ื ืžืžื•ื˜ื‘ื™ื ืœืงืจื™ืื”, ื•-event processor ื”ืžื’ื™ื‘ ืœืื™ืจื•ืขื™ื ืžืฉื™ืจื•ืชื™ื ืื—ืจื™ื. saga orchestrator ืžืชืื ืชื”ืœื™ื›ื™ื ืขืกืงื™ื™ื ืžืจื•ื‘ื™ ืฉืœื‘ื™ื (ืœืžืฉืœ, ืžื™ืœื•ื™ ื”ื–ืžื ื”) ืขืœ ื™ื“ื™ ื”ืื–ื ื” ืœืื™ืจื•ืขื™ื ื•ื”ื•ืฆืืช compensating commands ื›ืืฉืจ ืฉืœื‘ื™ื ื ื›ืฉืœื™ื.

ืจื›ื™ื‘ื™ ืœื™ื‘ื”
  • Event Bus / Broker: Kafka (ืœืื™ืจื•ืขื™ื ื‘ืขืœื™ ืชืคื•ืงื” ื’ื‘ื•ื”ื” ื•ืกื“ืจ, replay), EventBridge (ืœื ื™ืชื•ื‘ AWS-native), ืื• NATS (ืœ-low-latency). ืžื˜ืคืœ ื‘ื ื™ื’ื•ื‘ ืื™ืจื•ืขื™ื, ื”ืคืขืœื” ืžื—ื“ืฉ (replay), ื•-dead-letter queuing
  • Domain Services: ื›ืœ ืื—ื“ ืžื—ื–ื™ืง ื‘-bounded context โ€” Order Service, Payment Service, Inventory Service, Notification Service. ืœื›ืœ ืื—ื“ ื™ืฉ ืžืกื“ ื ืชื•ื ื™ื ืžืฉืœื• (polyglot persistence) ื•ืžืคืจืกื domain events ื‘ืฉื™ื ื•ื™ ืžืฆื‘
  • Saga Orchestrator: ืžื ื”ืœ ื˜ืจื ื–ืงืฆื™ื•ืช ืขืกืงื™ื•ืช ืืจื•ื›ื•ืช ื˜ื•ื•ื—. ืžื™ื™ืฉื compensating transactions ืœื‘ื™ื˜ื•ืœ ืคืขื•ืœื•ืช (ืœืžืฉืœ, ืื ื”ืชืฉืœื•ื ื ื›ืฉืœ ืœืื—ืจ ื”ื–ืžื ืช ืžืœืื™, ืฉื—ืจืจ ืืช ื”ื”ื–ืžื ื”). ื™ื›ื•ืœ ืœื”ื™ื•ืช ืžื‘ื•ืกืก choreography (ืฉื™ืจื•ืชื™ื ืžื’ื™ื‘ื™ื ืœืื™ืจื•ืขื™ื) ืื• orchestration (ืžืชืื ืžืจื›ื–ื™)
  • Event Store: ื™ื•ืžืŸ ืžืกื•ื’ append-only ืฉืœ ื›ืœ ื”-domain events. ืžืืคืฉืจ audit trail ืžืœื, ืฉืื™ืœืชื•ืช ื–ืžื ื™ื•ืช ("ืžื” ื”ื™ื” ืžืฆื‘ ื”ื”ื–ืžื ื” ื‘ืฉืขื” 2 ื‘ืฆื”ืจื™ื™ื?"), ื•-event replay ืœื‘ื ื™ื™ื” ืžื—ื“ืฉ ืฉืœ ื”ื™ื˜ืœื™ื ืื• ื ื™ืคื•ื™ ื‘ืื’ื™ื

ื”ื—ืœื˜ื•ืช ืขื™ืฆื•ื‘ ื•ื™ืชืจื•ื ื•ืช/ื—ืกืจื•ื ื•ืช

Choreography ืžื•ืœ Orchestration ืขื‘ื•ืจ Sagas
Choreography (ื›ืœ ืฉื™ืจื•ืช ืžื’ื™ื‘ ืœืื™ืจื•ืขื™ื ื•ืคื•ืœื˜ ืื™ืจื•ืขื™ื ืžืฉืœื•) ืคืฉื•ื˜ ื™ื•ืชืจ ืขื‘ื•ืจ ื–ืจื™ืžื•ืช ืขื‘ื•ื“ื” ืฉืœ 2-3 ืฉืœื‘ื™ื, ืืš ื”ื•ืคืš ืœื‘ืœืชื™ ืืคืฉืจื™ ืœื”ื‘ื ื” ื‘-5 ืฉืœื‘ื™ื ื•ืžืขืœื”. Orchestration (ืžืชืื saga ืžืจื›ื–ื™ ืžื ืคื™ืง commands ื•ืขื•ืงื‘ ืื—ืจ ืžืฆื‘) ืžื•ืกื™ืฃ ืฉื™ืจื•ืช ืชื™ืื•ื ืืš ื”ื•ืคืš ืืช ื–ืจื™ืžืช ื”ืขื‘ื•ื“ื” ืœื’ืœื•ื™ ื•ืœื ื™ืชืŸ ืœื ื™ืคื•ื™ ื‘ืื’ื™ื. MicrocosmWorks ืžืฉืชืžืฉ ื‘-orchestration ื›ื‘ืจื™ืจืช ืžื—ื“ืœ ืœื›ืœ ื“ื‘ืจ ืฉืžืขื‘ืจ ืœื–ืจื™ืžื•ืช ืขื‘ื•ื“ื” ื˜ืจื™ื•ื•ื™ืืœื™ื•ืช โ€” ื”ื‘ื”ื™ืจื•ืช ื”ืชืคืขื•ืœื™ืช ืฉื•ื•ื” ืืช ื”ืฉื™ืจื•ืช ื”ื ื•ืกืฃ.
Event Sourcing: ืžืœื ืžื•ืœ ืกืœืงื˜ื™ื‘ื™
Event sourcing ืžืœื (ื›ืœ ืฉื™ื ื•ื™ ืžืฆื‘ ื”ื•ื ืื™ืจื•ืข, ืื™ืŸ ืžืฆื‘ ืžืฉืชื ื”) ื—ื–ืง ืืš ืชื•ื‘ืขื ื™ ืžื‘ื—ื™ื ื” ืชืคืขื•ืœื™ืช โ€” ืืชื” ื–ืงื•ืง ืœืืกื˜ืจื˜ื’ื™ื•ืช snapshot, ื ื™ื”ื•ืœ ื’ืจืกืื•ืช ืื™ืจื•ืขื™ื, ื•ืื‘ื•ืœื•ืฆื™ื” ื–ื”ื™ืจื” ืฉืœ ืกื›ื™ืžื”. MicrocosmWorks ืžื™ื™ืฉื event sourcing ืžืœื ื‘ืชื—ื•ืžื™ื ืฉื‘ื”ื audit trail ื•ืฉืื™ืœืชื•ืช ื–ืžื ื™ื•ืช ื”ื ื“ืจื™ืฉื•ืช ืขืกืงื™ื•ืช (ืคื™ื ื ืกื™ื, ืฆื™ื•ืช). ืขื‘ื•ืจ ืฉื™ืจื•ืชื™ื ืื—ืจื™ื, ืื ื• ืžืฉืชืžืฉื™ื ื‘ืชื‘ื ื™ืช "event notification" ืคืฉื•ื˜ื” ื™ื•ืชืจ: ืฉื™ืจื•ืชื™ื ืคื•ืœื˜ื™ื ืื™ืจื•ืขื™ื ืืš ืฉื•ืžืจื™ื ืขืœ ื”ืžืฆื‘ ื”ืžืฉืชื ื” ืฉืœื”ื.
Kafka ืžื•ืœ EventBridge ืžื•ืœ SQS/SNS
Kafka ื›ืืฉืจ ืืชื” ื–ืงื•ืง ืœ-event streams ืžืกื•ื“ืจื™ื, replay, ื•ืชืคื•ืงื” ื’ื‘ื•ื”ื” (ืžืขืœ 10K events/sec). EventBridge ื›ืืฉืจ ืืชื” AWS-native ื•ืจื•ืฆื” ื ื™ืชื•ื‘ ืžื‘ื•ืกืก ืชื•ื›ืŸ ืขื ืคืขื•ืœื•ืช ืžื™ื ื™ืžืœื™ื•ืช. SQS/SNS ื›ืืฉืจ ืืชื” ื–ืงื•ืง ืœ-pub/sub ืคืฉื•ื˜ ืœืœื event replay. MicrocosmWorks ื”ืฉืชืžืฉ ื‘ืฉืœื•ืฉืชื โ€” ื”ื‘ื—ื™ืจื” ืชืœื•ื™ื” ื‘ืชืคื•ืงื”, ื“ืจื™ืฉื•ืช ืกื“ืจ, ื•ื”ื™ื›ืจื•ืช ื”ืฆื•ื•ืช.
ืชืงืฉื•ืจืช ืขืงื‘ื™ื•ืช ื‘ืกื•ืคื• ืฉืœ ื“ื‘ืจ
ืžืขืจื›ื•ืช ืžื•ื ื—ื•ืช ืื™ืจื•ืขื™ื ื”ืŸ eventually consistent ื‘ื˜ื‘ืขืŸ. MicrocosmWorks ืžืชื›ื ืŸ ื’ื‘ื•ืœื•ืช ืขืงื‘ื™ื•ืช ืžืคื•ืจืฉื™ื: ื‘ืชื•ืš ืฉื™ืจื•ืช, ืขืงื‘ื™ื•ืช ื—ื–ืงื” (ACID transactions); ื‘ื™ืŸ ืฉื™ืจื•ืชื™ื, eventual consistency ืขื idempotent event handlers ื•ืกืžื ื˜ื™ืงืช at-least-once delivery. ืื ื• ื‘ื•ื ื™ื ืขื‘ื•ื“ื•ืช ื”ืชืืžื” ื”ืžื–ื”ื•ืช ื•ืžืคืชืจื•ืช ืกื˜ื™ื•ืช.

ื‘ื—ื™ืจื•ืช ื˜ื›ื ื•ืœื•ื’ื™ื•ืช

ืฉื›ื‘ื”ื˜ื›ื ื•ืœื•ื’ื™ื•ืช
ื—ื™ืฉื•ื‘Node.js (NestJS), Python (FastAPI), Go โ€” ืœื›ืœ ืฉื™ืจื•ืช ื‘ื”ืชืื ืœืžืืคื™ื™ื ื™ ื”ืขื•ืžืก
ื”ื•ื“ืขื•ืชApache Kafka (MSK), AWS EventBridge, NATS JetStream, RabbitMQ
ื ืชื•ื ื™ืPostgreSQL (ื˜ืจื ื–ืงืฆื™ื•ื ืœื™), DynamoDB (ืžืคืชื—-ืขืจืš), Redis (cache/ื ืขื™ืœื•ืช), EventStoreDB
ืชื–ืžื•ืจTemporal (ืชื–ืžื•ืจ ื–ืจื™ืžืช ืขื‘ื•ื“ื”), AWS Step Functions, saga coordinator ืžื•ืชืื ืื™ืฉื™ืช
ื™ื›ื•ืœืช ืชืฆืคื™ืชOpenTelemetry (distributed tracing), Datadog, Jaeger, ืจื™ืฉื•ื ืžื•ื‘ื ื” (structured logging) ืขื correlation IDs

ืžืชื™ ืœื”ืฉืชืžืฉ / ืžืชื™ ืœื”ื™ืžื ืข

ื”ืฉืชืžืฉ ื›ืืฉืจื”ื™ืžื ืข ื›ืืฉืจ
ืฆื•ื•ืชื™ื ืžืจื•ื‘ื™ื ืฆืจื™ื›ื™ื ืœืคืจื•ืก ื‘ืื•ืคืŸ ืขืฆืžืื™ ื‘ืงืฆื‘ื™ื ืฉื•ื ื™ืื”ืฆื•ื•ืช ืฉืœืš ืžื•ื ื” ืคื—ื•ืช ืž-5 ืžื”ื ื“ืกื™ื โ€” ืžื•ื ื•ืœื™ืช ืžื•ื‘ื ื” ื”ื™ื˜ื‘ ืคืฉื•ื˜ ื™ื•ืชืจ ืœืชืคืขื•ืœ
ื—ืœืงื™ื ืฉื•ื ื™ื ื‘ืžืขืจื›ืช ื‘ืขืœื™ ืžืืคื™ื™ื ื™ ืกืงืืœื™ื ื’ ืฉื•ื ื™ืืืชื” ื‘ื•ื ื” MVP ื•ืฆืจื™ืš ืœื”ืฉื™ืง ื‘ืžื”ื™ืจื•ืช โ€” ืžืขืจื›ื•ืช ืžื‘ื•ื–ืจื•ืช ืื™ื˜ื™ื•ืช ืœื‘ื ื™ื™ื”
ืืชื” ื–ืงื•ืง ืœ-audit trails ื—ื–ืงื™ื ื•ื™ื›ื•ืœื•ืช event replayื›ืœ ืคืขื•ืœื” ื“ื•ืจืฉืช ืชื’ื•ื‘ื•ืช ืกื™ื ื›ืจื•ื ื™ื•ืช ื•ืขืงื‘ื™ื•ืช ื‘ืื•ืคืŸ ื—ื–ืง
ืœืชื—ื•ื ื™ืฉ bounded contexts ื˜ื‘ืขื™ื™ื (ื”ื–ืžื ื•ืช, ืชืฉืœื•ืžื™ื, ืžืœืื™)ื”ืชื—ื•ื ืžืฆื•ืžื“ ื—ื–ืง โ€” ืคื™ืฆื•ืœื• ื™ื•ืฆืจ ืžื•ื ื•ืœื™ืช ืžื‘ื•ื–ืจ

ื”ื’ื™ืฉื” ืฉืœื ื•

MicrocosmWorks ืื™ื ื• ืžืคืจืง ืœืžื™ืงืจื•-ืฉื™ืจื•ืชื™ื ืœืคื™ ืฉื›ื‘ื” ื˜ื›ื ื™ืช (API service, data service, auth service). ืื ื• ืžืคืจืงื™ื ืœืคื™ ื’ื‘ื•ืœื•ืช ื“ื•ืžื™ื™ืŸ ื‘ืืžืฆืขื•ืช DDD (Domain-Driven Design) bounded contexts. ืœืคื ื™ ื›ืชื™ื‘ืช ืงื•ื“, ืื ื• ืžืจื™ืฆื™ื ืกื“ื ืช event storming ื›ื“ื™ ืœืžืคื•ืช domain events, commands, ื•-aggregates โ€” ื–ื” ืงื•ื‘ืข ืืช ื’ื‘ื•ืœื•ืช ื”ืฉื™ืจื•ืช, ืœื ื”ืขื“ืคื•ืช ื˜ื›ื ื•ืœื•ื’ื™ื•ืช. ื”ื’ืจื ื• ืžื•ื ื•ืœื™ืชื™ื ืœืืจื›ื™ื˜ืงื˜ื•ืจื•ืช ืžื•ื ื—ื•ืช ืื™ืจื•ืขื™ื ืขื‘ื•ืจ ืœืงื•ื—ื•ืช ืืจื’ื•ื ื™ื™ื, ื•ื”ืœืงื— ื”ื ืคื•ืฅ ื‘ื™ื•ืชืจ ื”ื•ื: ื”ืชื—ืœ ืขื ืคื—ื•ืช ืฉื™ืจื•ืชื™ื ื’ื“ื•ืœื™ื ื™ื•ืชืจ ื•ืคืฆืœ ืžืื•ื—ืจ ื™ื•ืชืจ, ืœื ืœื”ื™ืคืš.

ืชื•ื›ื ื™ื•ืช ืงืฉื•ืจื•ืช

  • ืื•ื˜ื•ืžืฆื™ื™ืช ื–ืจื™ืžืช ืขื‘ื•ื“ื” ืืจื’ื•ื ื™ืช ืขื AI Agents โ€” ืชื–ืžื•ืจ ืžื•ื ื—ื” ืื™ืจื•ืขื™ื ืฉืœ ื–ืจื™ืžื•ืช ืขื‘ื•ื“ื” ืฉืœ AI agent
  • ื˜ืจื ืกืคื•ืจืžืฆื™ื” ืฉืœ ืžื™ืงืจื•-ืฉื™ืจื•ืชื™ื Serverless โ€” ืคื™ืจื•ืง ืžื•ื ื•ืœื™ืชื™ื ืœืฉื™ืจื•ืชื™ื serverless ืžื•ื ื—ื™ ืื™ืจื•ืขื™ื
  • ื—ื‘ื™ืœืช ืื™ื ื˜ื’ืจืฆื™ื” ื•ืื•ื˜ื•ืžืฆื™ื” ืœ-CRM โ€” ืกื ื›ืจื•ืŸ ืžื•ื ื—ื” ืื™ืจื•ืขื™ื ื‘ื™ืŸ ืžืขืจื›ื•ืช CRM
  • ืคืœื˜ืคื•ืจืžืช ื ืจืื•ืช ืฉืจืฉืจืช ืืกืคืงื” โ€” ืžืขืงื‘ ืžื•ื ื—ื” ืื™ืจื•ืขื™ื ืขืœ ืคื ื™ ืฉืœื‘ื™ ืฉืจืฉืจืช ื”ืืกืคืงื”

ืžืงืจื™ ื‘ื•ื—ืŸ ืงืฉื•ืจื™ื

  • ืคืœื˜ืคื•ืจืžืช HR/ERP ืืจื’ื•ื ื™ืช โ€” ืคืœื˜ืคื•ืจืžื” ืืจื’ื•ื ื™ืช ืžืจื•ื‘ืช ืฉื™ืจื•ืชื™ื ืขื ืื™ื ื˜ื’ืจืฆื™ื•ืช ืžื•ื ื—ื•ืช ืื™ืจื•ืขื™ื
  • ืื™ื ื˜ื’ืจืฆื™ื™ืช CRM โ€” ืกื ื›ืจื•ืŸ Zoho CRM ืžื•ื ื—ื” ืื™ืจื•ืขื™ื ืขื idempotent event handlers
  • ื ื™ื”ื•ืœ ืžื ื•ื™ื™ื โ€” ืื™ืจื•ืขื™ ืžื ื•ื™ ืžืจื•ื‘ื™ ืคืœื˜ืคื•ืจืžื•ืช ืขื webhook orchestration
Related Technologies
ืคืชืจื•ื ื•ืช ืขื ืŸืคื™ืชื•ื— SaaSื™ื™ืขื•ืฅ ื“ื™ื’ื™ื˜ืœื™
AI / Data

ืืจื›ื™ื˜ืงื˜ื•ืจืช Pipeline ืฉืœ AI/ML

ืžื•ื“ืœื™ื ืœื ืžืจื™ืฆื™ื ืืช ืขืฆืžื. ื”-Pipeline ืฉืžื›ืฉื™ืจ, ืžืืžืช, ืคื•ืจืก ื•ืžื ื˜ืจ ืืช ื”ืžื•ื“ืœื™ื ืฉืœืš ื”ื•ื ื”ืžื•ืฆืจ ื”ืืžื™ืชื™ โ€“ ื”ืžื•ื“ืœ ื”ื•ื ืจืง ืชื•ืฆืจ ืื—ื“.

EnterpriseView
cloud-native-infrastructure.webp
Infrastructure

ืชืฉืชื™ืช Cloud-Native

ืชืฉืชื™ืช ืฉืžื ื•ื”ืœืช ื‘ื’ืจืกืื•ืช, ื ื‘ื“ืงืช ื•ื ืคืจืกืช ื›ืžื• ืงื•ื“ ื™ื™ืฉื•ื โ€” ื›ื™ ื”ืคืœื˜ืคื•ืจืžื” ืฉืœืš ืืžื™ื ื” ืจืง ื›ืžื• ืžื” ืฉื ืžืฆื ืžืชื—ืชื™ื”.

EnterpriseView

ืฉืืœื•ืช ื ืคื•ืฆื•ืช

MicrocosmWorks ืžืชื›ื ื ืช ืžืขืจื›ื•ืช ืžื•ื ื—ื•ืช ืื™ืจื•ืขื™ื ืขื Message Brokers ืขืžื™ื“ื™ื ื›ืžื• Apache Kafka ืื• Amazon EventBridge, ื”ืฉื•ืžืจื™ื ืื™ืจื•ืขื™ื ืขื“ ืฉื”ืฆืจื›ื ื™ื ืžืขื‘ื“ื™ื ืื•ืชื ื‘ื”ืฆืœื—ื”, ืžื” ืฉืžื‘ื˜ื™ื— ืื™-ืื•ื‘ื“ืŸ ื ืชื•ื ื™ื ื‘ืžื”ืœืš ื”ืคืกืงื•ืช ืคืขื™ืœื•ืช. ืื ื• ืžื™ื™ืฉืžื™ื Dead-Letter Queues, ืžื“ื™ื ื™ื•ืช ื ื™ืกื™ื•ืŸ ื—ื•ื–ืจ ืขื Exponential Backoff, ื•-Circuit Breakers ื›ื“ื™ ืฉ-Microservice ื›ื•ืฉืœ ืœื ื™ื—ืกื•ื ืืช ื›ืœ ืฆื ืจืช ื”ืื™ืจื•ืขื™ื. ื‘ืจื’ืข ืฉื”ืฉื™ืจื•ืช ื‘ืžื•ืจื“ ื”ื–ืจื ืžืชืื•ืฉืฉ, ื”ื•ื ืžื“ื‘ื™ืง ืคืขืจื™ื ืื•ื˜ื•ืžื˜ื™ืช ื‘ืื™ืจื•ืขื™ื ืฉืœื ืขื•ื‘ื“ื• ืœืœื ื”ืชืขืจื‘ื•ืช ื™ื“ื ื™ืช.

ืชืงืฉื•ืจืช ืžื•ื ื—ื™ืช ืื™ืจื•ืขื™ื ื”ื™ื ื”ื‘ื—ื™ืจื” ื”ืขื“ื™ืคื” ื›ืืฉืจ ื”ืฉื™ืจื•ืชื™ื ืฉืœืš ืื™ื ื ื–ืงื•ืงื™ื ืœืชื’ื•ื‘ื” ืžื™ื™ื“ื™ืช, ื›ืืฉืจ ื™ืฉ ืฆื•ืจืš ืœื ืชืง ืืช ืžื—ื–ื•ืจื™ ื”ืคืจื™ืกื”, ืื• ื›ืืฉืจ ืคืขื•ืœื” ื™ื—ื™ื“ื” ืžืคืขื™ืœื” ืžืกืคืจ ืชื”ืœื™ื›ื™ื ืขื•ืงื‘ื™ื (downstream). MicrocosmWorks ื‘ื“ืจืš ื›ืœืœ ืžืžืœื™ืฆื” ืขืœ ืชื‘ื ื™ื•ืช ืžื•ื ื—ื•ืช ืื™ืจื•ืขื™ื ืขื‘ื•ืจ ืขื™ื‘ื•ื“ ื”ื–ืžื ื•ืช, ืฆื™ื ื•ืจื•ืช ื”ื•ื“ืขื•ืช, ื•ื”ื–ืจืžืช ื ืชื•ื ื™ ืื ืœื™ื˜ื™ืงื”, ืชื•ืš ืฉืžื™ืจื” ืขืœ APIs ืกื™ื ื›ืจื•ื ื™ื™ื ืขื‘ื•ืจ ืฉืื™ืœืชื•ืช ื”ืžื™ื•ืขื“ื•ืช ืœืžืฉืชืžืฉ ื”ื“ื•ืจืฉื•ืช ืชื’ื•ื‘ื•ืช ืžื”ื™ืจื•ืช ื‘ืžื™ื•ื—ื“ (ืคื—ื•ืช ืžืฉื ื™ื™ื”). ืžืขืจื›ื•ืช ื™ื™ืฆื•ืจ ืจื‘ื•ืช ืฉืื ื• ื‘ื•ื ื™ื ืžืฉืชืžืฉื•ืช ื‘ื’ื™ืฉื” ื”ื™ื‘ืจื™ื“ื™ืช ืขื ืงืจื™ืื•ืช ืกื™ื ื›ืจื•ื ื™ื•ืช ื•ื›ืชื™ื‘ื•ืช ืืกื™ื ื›ืจื•ื ื™ื•ืช.

MicrocosmWorks ืžืฉืชืžืฉืช ื‘-partition-key-based ordering ื‘-Kafka topics ื›ื“ื™ ืœื”ื‘ื˜ื™ื— ืฉื›ืœ ื”ืื™ืจื•ืขื™ื ืขื‘ื•ืจ ื™ืฉื•ืช ื ืชื•ื ื” (ื›ืžื• ื”ื–ืžื ื” ืกืคืฆื™ืคื™ืช ืื• ืžืฉืชืžืฉ) ืžืขื•ื‘ื“ื™ื ื‘ืจืฆืฃ ืขืœ ื™ื“ื™ ืื•ืชื• consumer instance. ืขื‘ื•ืจ ืชืจื—ื™ืฉื™ื ื”ื“ื•ืจืฉื™ื cross-entity ordering, ืื ื• ืžื™ื™ืฉืžื™ื saga orchestrators ืขื idempotent event handlers ืฉื™ื›ื•ืœื™ื ืœืขื‘ื“ ืžื—ื“ืฉ ื‘ื‘ื˜ื—ื” ื”ื•ื“ืขื•ืช ืฉืื™ื ืŸ ื‘ืกื“ืจ. ืื ื• ื’ื ืžื˜ืžื™ืขื™ื vector clocks ืื• sequence numbers ื‘-event payloads ื›ื“ื™ ืฉื”ืฆืจื›ื ื™ื ื™ื•ื›ืœื• ืœื–ื”ื•ืช ื•ืœื™ื™ืฉื‘ ืงื•ื ืคืœื™ืงื˜ื™ื ื‘ืกื“ืจ.

MicrocosmWorks ืžื™ื™ืฉืžืช ืืช ืชื‘ื ื™ืช ื”-Saga ืขื ื˜ืจื ื–ืงืฆื™ื•ืช ืคื™ืฆื•ื™, ืฉื‘ื” ื›ืœ ืžื™ืงืจื•-ืฉื™ืจื•ืช ืžืคืจืกื ืื™ืจื•ืขื™ ื“ื•ืžื™ื™ืŸ ืœืื—ืจ ื”ืฉืœืžืช ื”ื˜ืจื ื–ืงืฆื™ื” ื”ืžืงื•ืžื™ืช ืฉืœื•, ื•ืฉื™ืจื•ืชื™ื ื‘ืžื•ืจื“ ื”ื–ืจื ืžื’ื™ื‘ื™ื ื‘ื”ืชืื ืื• ืžืคืขื™ืœื™ื ืคื™ืฆื•ื™ื™ ื‘ื™ื˜ื•ืœ ื‘ืžืงืจื” ืฉืœ ื›ืฉืœ. ืื ื• ืžืฉืœื‘ื™ื ื–ืืช ืขื ืชื‘ื ื™ืช ื”-outbox ืฉื›ื•ืชื‘ืช ืื™ืจื•ืขื™ื ื‘ืื•ืคืŸ ืื˜ื•ืžื™ ืœื˜ื‘ืœืช outbox ืžืงื•ืžื™ืช ืœืฆื“ ื ืชื•ื ื™ื ืขืกืงื™ื™ื, ื•ืœืื—ืจ ืžื›ืŸ ืžืคืจืกืžืช ืื•ืชื ื‘ืื•ืคืŸ ืืžื™ืŸ ืœ-message broker. ื–ื” ืžืฉื™ื’ ืขืงื‘ื™ื•ืช ืื•ืœื˜ื™ืžื˜ื™ื‘ื™ืช ืœืœื ืขื•ื ืฉื™ ื”ื‘ื™ืฆื•ืขื™ื ื•ื”ืืžื™ื ื•ืช ืฉืœ two-phase commits.

MicrocosmWorks ืžื‘ืฆืขืช ืื™ื ืกื˜ืจื•ืžื ื˜ืฆื™ื” ืœื›ืœ ืื™ืจื•ืข ืขื correlation IDs ื•-distributed tracing headers ื‘ืืžืฆืขื•ืช OpenTelemetry, ืžื” ืฉืžืืคืฉืจ ืœื ื• ืœื“ืžื™ื™ืŸ ืืช ืžื—ื–ื•ืจ ื”ื—ื™ื™ื ื”ืžืœื ืฉืœ business transaction ื‘ื›ืœ ื”-microservices ื”ืžืฉืชืชืคื™ื, ื‘ื›ืœื™ื ื›ืžื• Jaeger ืื• Grafana Tempo. ืื ื• ื’ื ื‘ื•ื ื™ื event flow dashboards ื‘ื–ืžืŸ ืืžืช ื”ืžืฆื™ื’ื™ื throughput, consumer lag, ื•-processing latency ืœื›ืœ ืฉื™ืจื•ืช, ืžื” ืฉืžืงืœ ืขืœ ืื™ืชื•ืจ bottlenecks. stack ื”-observability ื”ืกื˜ื ื“ืจื˜ื™ ืฉืœื ื• ื›ื•ืœืœ structured logging ืขื event metadata, ื›ืš ืฉื ื™ืชืŸ ืœืขืงื•ื‘ ืื—ืจ ื›ืœ ืื™ืจื•ืข ื‘ื•ื“ื“ ืž-producer ืœื›ืœ consumer ืชื•ืš ืฉื ื™ื•ืช.