Kratos
Go microservices framework with AI agent support via Blades
A solid choice for experienced Go teams who want a production-tested microservices foundation with first-class Protobuf support and the flexibility to add AI agents via Blades. Beginners or teams needing a managed platform should look elsewhere.
- Go developers building cloud-native microservices with HTTP and gRPC
- Platform engineers creating a standardized service skeleton for their team
- Teams adopting distributed tracing and observability best practices
- Developers exploring AI agent architectures in Go using LLMs
- Beginners unfamiliar with Go, gRPC, or microservices concepts
- Teams needing a managed PaaS with built-in hosting and scaling
- Projects requiring a full-stack web framework with frontend support
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In short
Kratos — Go microservices framework with AI agent support via Blades. Best for Go developers building cloud-native microservices with HTTP and gRPC, Platform engineers creating a standardized service skeleton for their team, Teams adopting distributed tracing and observability best practices. Free to use.
What's new in Kratos
Checked 14 days agoAcross the latest 1 update: 1 feature update.
What independent users actually report about Kratos
We ran a structured research pass across product reviews, community discussions, and post-purchase forum threads to surface the patterns vendors won't publish themselves. Below: the recurring strengths, the hidden costs people mention most, and the cohort that consistently regrets adopting this tool.
88 mentions across 5 sources (Hacker News, YouTube, Bluesky, GitHub, Lemmy).
- +Protobuf-defined APIs with automatic HTTP/gRPC generation reduces boilerplate.
- +Pluggable middleware and service registry gives teams full infrastructure control.
- +Built-in OpenTelemetry and Prometheus metrics simplify observability in production.
- +Blades AI agent framework offers rare Go-native LLM workflow capabilities.
- +Interface-driven design and code generation improve testability and consistency.
- −Community feedback is extremely sparse and mostly off-topic for the framework.
- −Critical bug with etcd service discovery (context deadline exceeded) unresolved.
- −Docker deployment examples may require significant modification to work.
- −Learning curve is steep even for experienced Go developers due to abstractions.
- −Support channels are unclear—no dedicated forum, chat, or response guarantees.
- • No managed service or support—costs come from infrastructure and debugging time.
- • Potential operational overhead from configuring service registries and observability stack.
Viability Score
How likely is Kratos to still be operational in 12 months? Based on 4 signals — momentum (how recently it shipped), wrapper dependency, revenue model, and web presence.
Last calculated: July 2026
How we score →Key Features
- Protobuf-defined APIs with automatic HTTP and gRPC generation
- Pluggable middleware system for auth, logging, rate limiting, tracing
- Built-in OpenTelemetry distributed tracing support
- Prometheus metrics integration
- Structured logging with multiple backends (e.g., Fluentd)
- Dynamic configuration with multiple data sources
- Pluggable service registry (etcd, Consul, etc.)
- Error code generation from Protobuf enums
- Uniform metadata transfer across HTTP and gRPC
- Blades agent framework for AI workflows (OpenAI provider, GPT-5 model support)
- Toolchain: code generation, linting, cache layer generation
- High testability with interface mocking support
- Fault-tolerant design following SRE principles
- Voice mode not supported
- Mobile app not available
About Kratos
Kratos is a Go microservices framework designed for teams building production-ready, cloud-native services. It combines a lightweight, pluggable architecture with built-in support for HTTP and gRPC through Protobuf-defined APIs. The framework offers a flexible middleware pipeline for logging, authentication, rate limiting, and tracing, plus integrated OpenTelemetry and Prometheus metrics for observability. Its modular service discovery and configuration management let engineers choose their own infrastructure components. The standout feature is Blades, a modular agent framework for building LLM-powered AI agents in Go. With Blades, developers can compose agents that use models like GPT-5 to make dynamic decisions, or build predefined workflows for deterministic tasks. This makes Kratos uniquely positioned among Go microservices frameworks for teams exploring AI agent architectures. Kratos emphasizes interface-driven design and code generation, making services highly testable with mocking support. It follows SRE principles for fault tolerance and scales independently. Compared to heavyweight frameworks like Go-kit or Micro, Kratos offers a simpler, more Go-idiomatic approach with less boilerplate and stronger opinionation on API contracts.
Behind the Verdict
Kratos is a pragmatic framework for Go developers who know what they're doing. Its Protobuf-first design enforces type-safe contracts across HTTP and gRPC, which is a strong win for teams with multiple services. The middleware stack is straightforward and extensible, and the built-in observability hooks (OpenTelemetry, Prometheus) save setup time. We'd reach for this when building a cloud-native service mesh from scratch, especially if you want to avoid the complexity of Go-kit. The new Blades agent framework is what truly sets Kratos apart. It offers a clear architecture with agents, runners, tools, and providers, and supports models like GPT-5 out of the box. The distinction between Agents (LLM-driven decisions) and Workflows (predefined paths) caters to different AI use cases. This is rare in the Go microservices world and makes Kratos attractive for teams experimenting with LLM-powered automation. Where it bites: Kratos has a learning curve. If you're not comfortable with Protobuf, gRPC, and Go interfaces, you'll struggle. The framework is also opinionated about code generation and structure — fine for consistency, but feels rigid if you prefer minimal scaffolding. There's no managed hosting or built-in CI/CD, so you'll need your own deployment pipeline. Compared to alternatives, Go-kit offers more granular control but more boilerplate; Micro provides a more batteries-included experience but is heavier. Kratos sits in a sweet spot for teams that want structure without full lock-in. For pure AI agent work, you might consider LangChain in Python, but if you're committed to Go, Blades is a solid bet. In short: Kratos is a capable framework for Go microservices with a unique AI agent twist. It's not for everyone, but if you fit the profile, it delivers.
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Use Cases
- Build a production-ready Go microservice with Protobuf-defined APIs and gRPC.
- Integrate OpenTelemetry tracing into your microservices for full observability.
- Implement a rate-limiting middleware across HTTP and gRPC endpoints.
- Create an AI agent using Blades that autonomously calls external tools via LLM.
- Set up dynamic configuration with atomic updates using Kratos config.
- Generate service scaffolding with Kratos toolchain for rapid development.
Models Under the Hood
as of 2026-07-16
Limitations
- Kratos is a microservices framework, not a full platform; users handle deployment, CI/CD, and infrastructure themselves.
- The AI Blades framework is relatively new (Nov 2025) and may have limited community resources.
- There is no official hosted service — you run your own services.
Integrations
Resources & Guides
Official links
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