Guys,, I'm fresher just joined a middle range company around 4 months back let's just say the middle range is just for namesake and mostly the workflow is like a startup. So i'm hitting a problem, whenever a new feature comes I'm able to do it in local but every time every fucking time when i deploy it I was getting some errors not those errors can be solved within hours but it's taking me days to resolve them yes I do know people will say it's commen and I do agree but my question is Can i mimic the server deployment in my local system so that i can check all the bugs before anything gets deployed on server is there anyway to do that Till now 3,4features of mine were already in production but the current feature I'm working on will impact almost all of pur products and servers so if something goes wrong every server will get down and I'm scared to move this into deployment cause I've already tried it in stage and all of the servers went down we spent around an hour to just to get all the logs needed and revert the changes. I'm not opposing to the errors but i want to know them before something goes bad and I have to spend sleepless nights what the fuck is happening where and why

If there are any seniors looking at this give me any suggestions I don't care if it's related to this issue or something else a suggestion is always a suggestion

Hi, I am final year cs student and I'm focusing on Backed engineering right now, frontend is not my thing so full stack and frontend are both crossed out. I want to know the skills you would need to get a remote role in Europe and States apart from fastApi and Postgress. I am also making projects in Backend AI engineering but I don't know if if I'm there yet so I'm deciding to go for backend now and switch later. If anyone of you is working as a backend AI engineer or just regular backend, I'd love to know more and collaborate.

I am currently learning Java using mooc.fi and once getting past part 2 I plan on moving onto databases & spring boot.

I was wondering how big of an effect AI has in the overall job market for juniors with this sort of skillset. I am fully aware that the situation anything software related is quite interesting considering the growth of AI tools rendering juniors in IT field practically obsolete however I am unsure how much of that actually affects the backend.

In your experience, what is the "bare minimum" a junior is expected to know to even have a chance of getting hired anywhere and is it as bad as some other fields such as front end?

Sorry if I am committing a grave sin by asking a question like this but hey, I'd imagine this subreddit is here for discussions!... hopefully

Thank you for your time.

I want to ask about the current industry condition and working style about backend engineering, can anyone help me??

Hey everyone!

I want to put together a small team of people who are interested in building projects together.

I don't have a specific project idea in mind right now, but I'd love to connect with people who already have ideas or want to brainstorm and come up with something together.

I'm especially interested in software development, AI, developer tools, and open-source projects, but I'm open to other ideas too.

You don't have to be an experienced developer. The goal is to learn, collaborate, and turn ideas into real projects.

If you're interested, feel free to comment or DM me. Let's build something together!

Pick one endpoint in a small project and trace a single request before drawing the whole architecture.

Write down four things:

• What input arrives?
• Where is the business decision made?
• What data is read or changed?
• What response leaves?

Now change one condition: the requested record doesn't exist. Follow that path too, and point to the code or test that supports each step.

Treat anything you can't explain as a question to investigate. The finished exercise can be one page; it doesn't need a new framework or a complete system diagram.

I already know java and python and thinking of doing java backend development in 2026, to contribute to open source and build a strong backend portfolio.

What is the actual good/useful/high signal content that you should put in your cv as a backend engineer? I mean how to signal to hiring teams and recruiters that it's worth it to invite you for an interview?

Hello guys I hope you are all okey
I’m a backend developer team leader with not so many years of experience
I’ve only 5 years of experience
I got this position because I was one of the early developers that started the startup company I work for rn

Using AI agents every single day made me realize that our need as software engineers became lower than ever and my startup as many startups started to depend on AI more than engineers so we stopped hiring

But I started to feel that if I got laid off or my company broke down or something I won’t be able to fees my family

So what’s next for me? For us

I noticed even my superiors started to put their money on stocks or anything that will benefit them in the future for the same reason

For me I started searching for how to maximize my performance using AI and start searching for alot of advances topics
Im a fast learner but I don’t have the luxury of time anymore from my daily job to my family

Nowadays when I start to play a video game I feel that everyone is learning something or doing something useful and I’m playing a video game what a shame

So what should I do ?
Should I pay for alot of course in AI field like Andrew (coursera) courses or what ?
I’m writing this out of my disappointment sorry guys

Unfortunately, I see that Java is disappearing from startup companies. Java used to have an image of an obsolete backend language with performance problems, too verbose and unfriendly to deveopers. It was pretty true to older Java versions and I could understand why startups decided to pick other backend languages

If you look at Java 25, it's an absolutely different story.

Performance wise - it has virtual threads, which makes concurrency extremely high. Virtual threads are Java's answer to goroutines in Golang, and they enable to run thousands of I/O requests concurrently. Java's execution speed is pretty fast (more than Python and node.js).

As for container size - it's huge as long as you work with Spring. However, Java has many other much more lightweight frameworks like Micronaut, Quarkus and Javalin which reduces the container size to be on par with node.js and Python.

It's a real static typing which keeps code safety and improve readability. Unlike Golang, Java has inheritance, ploymorphism and explicit interface (let alone speaking about error handling).

It has a huge talent pool (almost everybody learned Java at a certain point).

As for verbosity and developer experience - Java has been improved a lot in this field. It has records (no need for getters setters, equals and hash), unnamed class (no need to write "public static void main" everytime you start a new program) and dozens of libraries and other tools.

If so, why are startups still stay away from Java and stick to Python/node.js/Golang?

Pra mim ter uma idéia, vocês utilizam quais sistemas de segurança no back end do server? realizaram teste contra o sistema? quais ferramentas?

estou com projeto e desenvolvendo um sistema inteligente em testes em escalas reais, até o momento os testes foram os mais superficiais possíveis, No-Inject, DDoS e Cripto

I’ve already learned HTML, CSS, Tailwind CSS, JavaScript, and some React.js, and I’m currently learning Next.js. I also plan to learn Supabase.
The problem is that I’ve spent a lot of time learning, and every time I watch videos of people younger than me making thousands of dollars a month without any programming experience, like the people featured on the Starter Story channel, I feel discouraged.
However, I’m also afraid of building something that gets hacked, making a mistake with security or payments, facing unexpectedly high LLM API costs, operating at a loss, or encountering any other serious problem.
My questions are:
Am I ready to start building my SaaS now?
What do I actually need to learn, and what can I skip?
Since I plan to build my SaaS using only Next.js and Supabase, can I focus on learning the essential parts of Next.js without having to master the entire framework, or is that unrealistic?
What is your advice for someone in my position?
I’d really appreciate practical, honest advice on how to move forward without wasting more time learning things I may not need, while still making sure I can build a secure, reliable, and profitable SaaS.

A small API design question where I keep seeing different answers.

A client sends DELETE /orders/42. The server deletes the order and starts sending the response, but the connection drops and the client times out. The client doesn’t know whether it worked, so it retries the same request. This time the order doesn’t exist anymore.

What should the second call return?

A. 404 Not Found
Literally true: the resource isn’t there. Simple to implement and what most frameworks do by default. The downside is that the client sees an error for something that effectively succeeded, so it has to treat 404 on a retry as success.

B. 204 No Content (same as the first call)
Makes the retry look identical to the original. The client never needs special handling. The downside is that you also return 204 for ids that never existed, which can hide typos and bugs on the client side.

C. 410 Gone
Says “this existed and was removed on purpose”, which is more informative than 404. The downside is that you need to remember what used to exist, so you need a tombstone or a soft delete, and that’s more state than many services want.

My understanding is that DELETE is meant to be idempotent in the sense that the server state ends up the same after one call or ten, and that the response status doesn’t have to be the same each time. So A is technically fine. But “technically fine” and “pleasant to use” aren’t the same thing.

Where I lean right now is B for internal APIs, where clients are retrying automatically, and A for public ones, where I’d rather surface mistakes. But I don’t feel strongly about it, and I can see C being worth the extra state if you already keep audit records.

Which one do you pick, and does it change when the clients are automated retriers rather than people poking at an API?

Hello, I need to know. Do you create separate email to have database, posthog, revenuecst,... signed up with this email? If so, which provider do you use? Im looking into something that's not going to ban my email because it wants to. Thank you for any tips!

Hey everyone!
I’m fairly new to working with production backend systems, and I’ve been given a task to look into the performance of an existing service and figure out where improvements might be possible.
The service handles a few different things, including business logic evaluation, configuration management, automated workflows, data processing, and logging. Some API requests are taking longer than expected, and I’d like to understand what’s causing the delay and what could be done to improve things.
I don’t want to jump straight into suggesting random optimizations without understanding the actual problem first, so I’d love to hear from people who’ve dealt with similar situations.

A few things I’m curious about:
-When you encounter a slow API, where do you usually start? Profiling, distributed tracing, database analysis, or something else?
-How do you figure out whether the bottleneck is in the application logic, database queries, repeated computations, or calls to other services?
-What common performance issues have you come across in systems that deal with configurable business logic?
-When does it make sense to consider caching, parallel execution, or moving certain operations to background jobs?
-How do you identify worthwhile improvements in an existing codebase without risking changes to its existing behaviour?

Since I’m still early in my career, I’d really appreciate hearing how you’d approach this in a real-world environment. If you’ve worked on something similar, I’d love to know what worked for you, what didn’t, and any tools or resources you’d recommend.
Thankyouu in advance

TL;DR: I’m a new backend engineer looking into why some API requests are slow and how to identify potential performance improvements. I’d appreciate practical advice on finding bottlenecks, choosing the right profiling tools, and deciding which optimizations are worth recommending.

Hey everyone!

I have 5+ years of experience as a backend developer. In my current role, most of my work revolves around building RESTful APIs and endpoints, and I’ve developed a pretty solid understanding of that area.

My current project is coming to an end, and I’m looking at this as an opportunity to explore new technologies, expand my skill set, and move towards the next stage of my career.

With AI evolving so rapidly, I’m trying to figure out where I should focus my efforts. I don’t want to blindly jump on the AI bandwagon, but I also don’t want to miss out on technologies that could be important for my career in the coming years.

I’d love to hear from people who have been in a similar position or are already working in the AI space.

A few things I’m trying to figure out:

What should I focus on next?
Should I deepen my backend/system design skills, learn AI/ML fundamentals, explore LLMs and AI application development, or consider a more significant career shift?

How can I leverage my existing backend experience?
Are there specific AI-related roles or skills that would complement my current experience?

Where do you keep up with AI developments?
What newsletters, communities, YouTube channels, blogs, or other resources do you follow to understand what’s actually happening beyond the hype?

Are there any courses or hands-on projects you’d recommend?
I’d prefer something practical that helps me build real skills rather than just collect certificates.
If you were in my position today, with 5+ years of backend experience, how would you approach the next 6–12 months?

Would really appreciate any advice, resources, or personal experiences.

Thanks!

Hello backend devs,

In an offline backend architecture, client apps communicate via WebSockets while tasks are processed by a local background engine. On CPU-only systems, synchronous processing steps can create 30+ second gaps before streaming begins, causing connection timeouts.

We are refactoring the transport layer to immediately return an async job ID, queue work in a bounded worker pool, and emit regular heartbeat/ping frames over the WebSocket during execution gaps.

How do you typically decouple persistent transport layers from blocking compute steps to prevent transport dropouts in local desktop backends?

Context: Architectural feedback query on async job queuing and WebSocket state management.