#go #alpinejs #clean_architecture #consul_connect #ddd #echo_framework #event_driven_architecture #event_driven_microservices #golang #grpc_gateway #microservices #nomad #postgresql #rabbitmq #terraform #vertical_slice_architecture

https://github.com/thangchung/go-coffeeshop

#csharp #architecture #aspnetcore #clean_architecture #cqrs #ddd #dotnet #dotnetcore #event_driven_architecture #event_sourcing #kubernetes #masstransit #messaging #microservice #microservices #oauth2 #opentelemetry #software_architecture #software_design #software_engineering #vertical_slice_architecture

Migrating from a monolithic architecture to a cloud-native microservices architecture offers several benefits. It improves scalability, allowing different parts of the application to grow independently. This approach also enhances reliability by isolating faults, so if one service fails, others continue to work. Additionally, microservices enable faster deployment and updates, as each service can be developed and deployed separately. This flexibility allows teams to use the best technology for each service, making development more efficient and agile[2][3][5].

https://github.com/meysamhadeli/monolith-to-cloud-architecture

#go #cli #event_driven #event_driven_architecture #queues #serverless #serverless_functions #workflow_engine #workflows

Inngest lets you write reliable, long-running background functions called durable workflows that automatically handle retries, scheduling, and state management without needing to manage infrastructure like queues or servers. You write functions in your preferred language using their SDKs, run and test them locally with the Inngest Dev Server, then deploy them on your own infrastructure or Inngest’s platform. It supports complex workflows with steps that retry on failure, concurrency control, and event triggers. This saves you time and effort by simplifying event-driven app development, improving reliability, and scaling automatically without extra setup. It also offers tools for monitoring and managing workflows easily.

https://github.com/inngest/inngest

#elixir #agent #ai #artificial_intelligence #elixir #event_driven_architecture #functional_programming #orchestration #workflow

Jido is a pure functional framework for Elixir to build autonomous multi-agent workflows. Agents are immutable data with a simple `cmd/2` function that transforms state purely and outputs directives for effects like signals or spawning, handled by OTP runtime. It formalizes patterns like standard signals, reusable actions, and hierarchies over raw GenServer, adding AI tools, strategies (ReAct, FSM), and supervision. You benefit by creating scalable, testable, fault-tolerant agent systems easily for production AI apps, saving reinvented code.

https://github.com/agentjido/jido