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Agentic AI Atlas · API Gateway & Microservices (Kong/Envoy + gRPC + Kubernetes + Go)
stack-profile:api-gateway-microservicesa5c.ai
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API Gateway & Microservices (Kong/Envoy + gRPC + Kubernetes + Go) overview

A microservices architecture with Kong or Envoy as the API gateway handling routing, rate limiting, authentication, and observability at the edge; gRPC for strongly-typed inter-service communication with Protocol Buffers; Kubernetes for container orchestration; PostgreSQL for per-service data stores; and Go as the primary service language. The gateway centralizes cross-cutting concerns (TLS termination, JWT validation, request transformation) so individual services remain focused on business logic. gRPC provides efficient binary serialization, bidirectional streaming, and automatic client/server code generation. Kubernetes handles service discovery, scaling, and health management. OpenTelemetry instruments distributed traces across service boundaries. This stack suits organizations breaking a monolith into services or building platform APIs consumed by multiple teams. The primary tradeoff is operational complexity: service mesh, distributed tracing, and per-service databases require mature DevOps practices.

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displayName
API Gateway & Microservices (Kong/Envoy + gRPC + Kubernetes + Go)
description
A microservices architecture with Kong or Envoy as the API gateway handling routing, rate limiting, authentication, and observability at the edge; gRPC for strongly-typed inter-service communication with Protocol Buffers; Kubernetes for container orchestration; PostgreSQL for per-service data stores; and Go as the primary service language. The gateway centralizes cross-cutting concerns (TLS termination, JWT validation, request transformation) so individual services remain focused on business logic. gRPC provides efficient binary serialization, bidirectional streaming, and automatic client/server code generation. Kubernetes handles service discovery, scaling, and health management. OpenTelemetry instruments distributed traces across service boundaries. This stack suits organizations breaking a monolith into services or building platform APIs consumed by multiple teams. The primary tradeoff is operational complexity: service mesh, distributed tracing, and per-service databases require mature DevOps practices.
composes
  • tool:kong
  • tool:kubernetes
  • language:go
  • language:protobuf
  • library:grpc-js
  • library:pgx
  • tool:helm
  • tool:opentelemetry
  • tool:docker

Outgoing edges

applies_to2
  • domain:platform-engineering·DomainPlatform Engineering
  • domain:backend·DomainBackend
composed_of9
  • tool:kong·ToolKong Gateway
  • tool:kubernetes·ToolKubernetes
  • language:go·LanguageGo
  • language:protobuf·LanguageProtocol Buffers
  • library:grpc-js·Library@grpc/grpc-js
  • library:pgx·Librarypgx
  • tool:helm·ToolHelm
  • tool:opentelemetry·ToolOpenTelemetry
  • tool:docker·ToolDocker
follows_workflow2
  • workflow:microservice-decomposition·WorkflowMicroservice Decomposition
  • workflow:api-design-review·WorkflowAPI Design Review
requires_skill_area5
  • skill-area:backend-api-design·SkillAreaBackend API Design
  • skill-area:k8s-operator-development·SkillArea
  • skill-area:service-mesh-config·SkillAreaService Mesh Configuration
  • skill-area:observability-instrumentation·SkillAreaObservability Instrumentation
  • skill-area:event-driven-architecture·SkillAreaEvent-Driven Architecture
used_by_role3
  • role:platform-engineer·Role
  • role:backend-engineer·RoleBackend Engineer
  • role:architect·RoleArchitect

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