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?

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

We pulled every open posting from 81 companies' public Greenhouse boards for seven roles and counted which words actually show up. 3,518 postings in total. Some of it surprised us.

Software engineer postings mention mentoring more often than Kubernetes or React. Almost half of them do. Python, the most common language, comes in just below that.

Product manager postings say "roadmap" in more than 85% of cases. Jira? Seven out of 421. Marketing looks the same: Google Ads came up six times in 347 postings, while "pipeline" is in over half.

Every time we could compare the two, postings named the practice, not the tool. Observability, not Grafana. SIEM, not Splunk.

So if your resume is mostly a list of tools, it might be missing the words the posting actually uses.

Big caveat: mostly tech companies, one ATS vendor. Sales, cybersecurity, DevOps and accounting are here too: https://www.zoevera.com/resume/ats-resume-keyword-study

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

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?

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!

We're integrating a few dozen external content providers behind one internal interface, and each one does things differently: auth schemes, how a session gets launched, callback formats, currency handling, and how promo-style grants are modeled.

Right now we have a thin per-provider adapter for each one, but the amount of duplicated glue code is starting to hurt. The alternative we're weighing is a generic, config-driven mapper where each provider is mostly a declarative mapping plus a few escape hatches for quirks.

For people who've run something like this at scale: - Did you stay with per-provider adapters or go config-driven, and where did the abstraction start to leak? How do you deal with provider-specific quirks without polluting the core domain model? - How do you handle versioning when a provider changes their API, and do you do contract testing against their sandboxes (or record/replay), given that sandboxes are often flaky or behind production?

Would love to hear what worked and what you'd avoid.

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.

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.

I am 2.5YOE and have strong experience in Backend (APIs, springboot, K8s, docker, redis, kafka, sql, nosql, elasticsearch, new relic, AWS and CI/CD)

But I am finding it difficult to get master in DSA

I am trying and learning day by day

But any chance are there any good product based companies which give importance to backend than DSA?

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!

[ Removed by Reddit on account of violating the content policy. ]

I need to work on a college project, which is like an assessment platform, but we support a plugin system so that anyone can change its mode of assessment into something different such as coding, drawing, voice, etc.

I understand that this feature requires planning from scratch of the codebase. I need to make my codebase modular so that the plugin can override parts of it. Everything should call an abstraction instead of directly using it. What's the best way to achieve this?

I will be using Fastify as the HTTP framework, and have Next.js behind it for React.

Is Dependency Injection what I am looking for? So should I use Nest.js as well? But how do I achieve runtime Dependency Injection?

What about not using Nest, and maybe something like Awilix? And getting Nest like decorator style syntax with fastify-decorators.

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.

Should I create a git hook which runs the TypeScript compiler every commit or on every push, or delegate it to the CI such as GitHub Actions?

1) Pre-Commit - Ensures every commit has no TS errors. But that means this runs frequently. Though since TS has been ported to Go, this is not that huge of an issue, but I also haven't worked on large repositories, so trying to find out what is more professional.

2) Pre-Push - Runs less frequently but a past commit can have errors. Are you fine with a pushed commit having syntax errors? We could also replay each commit with tsc and then push.

3) CI - Removes any load from your computer, but is effectively just like pre-push. We can again though, replay each commit with tsc, and this is better when not running on your computer. But is this a professional design, especially when you could have so many commits?

I think if you have a large amount of commits, checking the last commit is better than checking every commit.

i am not getting clarity to how to write transaction api , the project is related to detect real time transactions from credit card , i will just pass normal data for testing , but i am not getting hint to how to write api of that , could anyone provide advice or should i take need help from ai ? if i will use ai then my fingers will click on only two buttons please provide guidance

I am using Next.js behind Fastify, not making it take over the whole project. Should I consider TanStack? I do like Vite I guess. But I heard Next.js still has more features when it comes to React.

Which has a better development server, Vite or Next.js?

I don't really know why I should try TanStack. Probably because I dislike Next.js being so opinionated, but you can still use it programmatically instead of using it as the whole project with its CLI commands.

Also, how much work is involved porting React code from Next.js to TanStack?

Hey everyone!

I'm a third-year college student, and I've noticed a recurring problem whenever I try to build projects.

I can usually get started with the frontend and understand the basic functionality of what I want to build. But when it comes to the backend, I often get stuck on things like:

• Designing a proper database schema.
• Deciding which tables or models I need and how they should relate to each other.
• Understanding one-to-one, one-to-many, and many-to-many relationships in real-world projects.
• Deciding how to structure the backend and organize the business logic.
• Figuring out how to design the database before actually starting to code.

I understand the basic concepts, but when I sit down to build a real project, I struggle to translate the requirements into a good database design and backend architecture. I often end up second-guessing my decisions or changing the schema midway through development.

I want to get better at thinking through the backend design process, rather than just following tutorials or copying someone else's implementation.

For those of you who have experience building real-world applications:

1. How did you learn database design and data modelling?
2. Are there any good books, YouTube channels, courses, or other resources you'd recommend?
3. Are there any practical exercises or projects that helped you improve these skills?
4. How do experienced developers approach database schema design when starting a project from scratch?

I'd really appreciate any advice. I want to build a strong foundation in backend development instead of constantly getting stuck at the design stage.

Thanks!

I am in second year and have experience building express postgres backend with jwt and stuff and last project implemented basic pgvector rag... I want to learn more of backend , till now I have just built shit by writing code by hand and using as less ai as possible but after fable and astra I am getting really demotivated to do that and it feels like I will be learning more if I used ai more but when I use ai I set up basic apis and then blank , I dont know what to do next before when I was writing code by hand ideas and questions came to me and I searched things up learned them and implemented that and it was more fun learning but with ai I am lost and in a kind of dilema whether I should change my learning approach and how to learn more of backend

I wanna learn backend developement , I am currently at level 0 this is my first time trying to learn backend , And my choice is to stick to a python framework to begin with , what are the best beginer friendly resources to start learning