⚠️ Common API Done Right pitfalls to avoid New comprehensive guide covering: ✨ Core concepts 🔧 Practical examples ⚡ Performance tips 🎯 Best practices Dive in 👇 🔗 kubaik.github.io/api-done-ri… #VectorDB #API #APIDesign #GraphQL #Microservices

The Truth About Async Feign in Spring Boot Microservices by PraveenCodes medium.com/p/the-truth-about…

Hehe @__karnati this is good ;) Funny thing is that even in microservices you have similar situation with all the layers of integration you touch one method signature and you need to change controllers, DTOs number of clients, and calling code etc... Wonder your opinion on new integration model that we are striving to deliver based on interfaces distribution through package managers ensuring always up to date clients for any public methods without the need to implement integration layer graftcode.com You think it could simplify companies move from monolith to microservices? isnt it?

wait is this about microservices?

Why most microservices projects fail: Not because of tech. Because of missing discipline.

Microservices don’t fix bad engineering. They amplify it. Start simple. Earn complexity.

Real reason: the switch isn't free. Going from monolith to microservices means months of new integration code, separate repos, coordinated deploys for every change, and a whole new layer of error handling per service call. None of that ships features. @syssignals is right about the operational tax but that's the cost after you switch. The bigger problem for most companies is the cost of switching. Every interface between modules has to become an API. Every function call becomes a network call with retries, timeouts, and versioning. You don't just redeploy you rewrite. Monoliths keep running not because nobody wants to scale. They keep running because the engineering effort required to move is too large to justify without a burning platform. The real fix is making the transition incremental: module boundaries that work identically in-process and as remote services. Split one module at a time, no big bang rewrite. That's the architecture decision that actually costs nothing to change later. academy.graftcode.com/quick-…

why ask one LLM when you can ask four and make them argue? built a Claude Code plugin around @karpathy's llm-council: /council "microservices or monolith?" stage 1: 4 models answer independently stage 2: each model anonymously ranks the others (no favoritism) stage 3: a chairman synthesizes the best answer 30 seconds → deliberated consensus github.com/genesis-ship-it/c…

LMAO… 🤣 have you tried microservices? 😂

Unpopular opinion: most startups die from building too much, not too little. You don't need twelve microservices. You need one customer.

Smart pattern. Separate filesystems + message bus is basically microservices for agents. We're doing something similar on the marketing side: each agent owns its data domain, passes enriched context downstream. Zero shared state, zero race conditions. How do you handle the cold start problem when a new agent needs historical context from another?

Every engineer thinks they need microservices. I run an entire company on SQLite and cron jobs. We are not the same.

Exciting launch! Planning to use GLM-5-Turbo for autonomous 'Backend Agents' in my all-in-one business app. That 200k context + 128k output means generating entire microservices in one go. Real 'Agentic Engineering' is here.

It's like microservices but actually worse.

Backend Engineers (C#) Needed Contract: 1-month Must have experience in C# and Microservices Architecture. Pay: ₦500k Word mode: Hybrid(3 days onsite 2 says remote) Location: Victoria Island Resumption: Immediate (same-day for successful candidates) Send CV to oaina@sbsc.com

Your 3 AM alerts aren't resilience, they're a #DistributedMonolith. Amazon's video team cut costs 90% reverting to monolith. Validate if #OperationalReadiness supports overhead before extraction. Often, a #ModularMonolith beats premature distribution. banandre.com/blog/microservi…

Forget "learn to code." Learn systems architecture and distributed computing *first*. Understanding how complex systems fail at scale is more valuable than any single language on day one. Start by building simple microservices and intentionally breaking them.

Hear me out.. AI powered... Wait for it.. Microservices... On blockchain, and yes nobody uses NFT stupid, that's a bubble.

Great timing on this series. As an IT architect running Python+PHP microservices, the Gordon agent + sandboxed execution angle is huge. Docker becoming the standard runtime for AI agents in CI/CD is exactly where this is heading. Queued for tonight.

Microservice Architecture Patterns for Scalable Machine Learning Systems Sowjanya Karanam, Jayanth Bhargav arxiv.org/abs/2603.13672 [𝚌𝚜.𝚂𝙴]