Hello, I'm confused on what type of projects a beginner should begin with and to continue the journey of learning backend dev.

Is there any good reliable roadmap of projects to follow, which will allow me at the end of the day, to gather the experience to land a job?

Especially the link I provided, since I cannot be the judge of deciding is it actually worth following it.

hi all! I am interested in becoming a backend dev as I like the logic side and problem solving aspects.

Is learning the JS, MySQL/PostgreSQL (or MongoDB), and Node/Express enough to get started in that field?
I have taken a bootcamp for full-stack web development and I really liked the backend side of things and would like to pursue that but I am not sure with junior roles becoming more scarce.

Thank you!

I'm a software developer working at a bank, and I feel like we're way behind when it comes to AI adoption.

Every time AI comes up, the conversation is mostly around security, compliance, data privacy, etc. I understand these are important, especially in banking, but it feels like we're moving extremely slowly.

For example, our bank deployed a GPT model through Azure AI Foundry and built an internal ChatGPT-like interface for employees. That's pretty much the extent of AI adoption I've seen so far.

Meanwhile, I keep seeing people talk about using Claude Code, Cursor, AI agents, and building AI-powered features using LLM APIs.

I'm curious how things work at other companies.

• Are you actually building AI-powered features using APIs from OpenAI, Anthropic, etc.?

• How does your company approach new AI initiatives? Do developers get to experiment and propose ideas, or does everything have to go through multiple approval processes?

• How are you handling security and compliance concerns when integrating AI into existing applications?

• Are companies actually using AI agents and automation in production, or is most of it still experimentation?

I'm especially interested in hearing from developers working at banks, fintech companies, or other large enterprises.

I want to understand what real-world AI adoption looks like beyond just building an internal ChatGPT wrapper.

How is your company approaching this? Are you seeing meaningful AI adoption, or is it mostly hype and internal chatbots?

Well the title says it all. I want to start learning backend and databases properly. Anyone has recommendations?

Hi builders,

I m a software engineer with 25 years coding experience, so i guess i have a deep understanding of software. Recently i start using claude code and cursor ai, it is amazing and give me 100x productivity, and i never need to code by hand anymore, and it open an opportunity for non technical users to start building thing, which is awesome.

Then i start wondering, is backend and database really necessary? I mean yes of course you need data, then you need backend logic to handle data, provide APIs or handling OAuth. But do we really need backend and database ?

Lots of vibe coder are not technical to handle server and database setup, https, ngnix….etc. And i think the current cloud services are built for scalability and still require infrastructure knowledge to setup and management , by eliminating backend and database we can make vibe coding more easy and enable more non technical users to deploy their project to live.

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Hi everyone,

I'm looking for a project idea that solves a genuine problem faced by developers, engineering teams, or businesses.

I want to build something beyond a standard CRUD application, with a strong focus on backend engineering.

I'm interested in exploring areas such as:

- API design and reliability

- Distributed systems and event-driven architecture

- Database performance and data consistency

- Developer productivity tools

- Monitoring, debugging, and automation

I'd particularly appreciate suggestions based on problems you've personally experienced at work or in your own projects.

Three questions:

1. What repetitive or frustrating technical problem do you face regularly?

2. What tool or workflow do you wish existed, or worked better?

3. If someone built a small, reliable solution to this problem, would you actually use it?

I'm open to using Java or another language if the problem calls for it.

Thanks!

We had a fun one on a mobile banking support project. Not fun at the time, obviously.

About 40 minutes after a release, transfers started slowing down. Then came the 502s. It was payday too, so traffic was already higher than normal.

First reaction was to restart the services.

Bad call.

Every restart dropped the warm database connections, and the load spiked again. We were basically making things worse while trying to fix them.

Turned out the release had changed the DB connection pool settings. Once we found that in the deployment logs and rolled back, things settled down within a few minutes.

The other mistake was communication. The engineer working on the incident was also trying to answer questions from the bank's operations team, which had support lines filling up.

We changed that afterward. One person handles the incident, another handles updates. Even if the update is just "still investigating."

Curious if anyone else has had a seemingly harmless recovery step make an outage worse.

With the recent PHP security vulnerability making headlines, I'm wondering how much impact this could have on the PHP job market in the long run.

I'm currently working as a PHP developer, and with all the AI disruption already happening in IT, news like this makes me question the future of the tech stack even more.

Could this push companies towards other technologies, or is it just another security issue that will eventually get patched and forgotten?

Would love to hear from experienced PHP developers and people involved in hiring. Are you seeing any changes in demand for PHP developers? Is it still worth investing in PHP/Laravel, or should developers seriously start preparing to switch stacks?

Hi my goal is to learn ml but i also want to learn backend with basics of frontend
I want suggestion from where i can learn good backend with frontend basics thanks
Also if there are stacks for backend also, please suggest(dont know anything about it yet)
Thanks

A small calculation that changed how I look at timeouts. Take a request that has to answer the user in 3 seconds.

Step 1. Your service calls another service, and you’ve set a 2-second timeout on that call. That looks safe, since 2 is less than 3.

Step 2. The call is wrapped in a retry, with up to 2 retries after the first attempt. A timed-out attempt is retried.

Step 3. Worst case, all three attempts time out:

worst case = timeout × (retries + 1)
           = 2s × (2 + 1)
           = 6s

The user’s budget was 3 seconds. In the worst case you spend twice that waiting on one dependency, and you haven’t started counting the rest of the request yet.

Step 4. Now add a second dependency with the same settings. If both are called one after the other and both are slow, the worst case is 12 seconds. Each setting looked reasonable on its own, and the total is nowhere near the budget.

A few things this seems to imply:

• timeouts and retries have to be chosen together, from the outside in: start with the budget the caller gave you, then divide it
• a retry is only useful if there’s time left to make it, so a deadline that is passed along and checked before each attempt works better than a fixed timeout per call (I believe gRPC propagates deadlines like this, but check your stack)
• retrying a call that’s already slow because the dependency is overloaded makes it worse. A small cap on retries, with a bit of random delay between them, helps avoid everyone hammering it at once
• retries are only safe for operations that can be repeated, so idempotency comes first

One more thing to check is what your HTTP client does by default. As far as I know, several common Java clients have no timeout at all unless you set one, which means the “worst case” can be unbounded. I’d look this up for the exact client and version you use, since defaults vary.

What I’m not sure about is how to split a budget across calls that run in parallel versus in sequence, and whether people set it by hand or compute it somewhere central.

How do you handle it in your services? Do you have a standard timeout and retry policy, or does each call get decided where it’s written?

So i Have just finished an backend assignment creation for a company they want me to build all this for an assessment in 2 :

Implement core workflows:

• User lifecycle (auth, roles)

• Doctor availability and booking

• Consultation lifecycle and prescriptions

Search and filtering

• Compliance and audit trails

• Admin analytics. System Requirements

• Scale: 100k daily consultations

• Latency: p95 <200ms reads, <500ms writes

• Availability: 99.95%

• Security: encryption, MFA, RBAC

• Observability: metrics, logs, traces

• CI/CD with containerized deployment. Architecture Tasks

1. High-level architecture and data flow

   1. Booking flow sequence diagram
   2. ER diagram
   3. API schema

2. Retry & backoff strategies

3. Data partitioning

4. Caching and concurrency handling

5. Transaction management and sagas

6. Backup and DR strategy.'

and build most of this thing in the repo below and skip most of thing cause i think its too much for a 2 day work like caching and backup in 2 day project

i build the role based auth , jwt , booking and cancling session , rate limiting , used dependency injection used prisma orm and postgresql in docker and also put all this inside the docker provided them with openapi and swagger api docs

this is my github repo link https://github.com/BADDEEP007/backend-assignment

how you think i did in this and tbh i am very aware that i want pass in this screening cause but i learned alot and i feel very empty to build all this and their a great chance they want even see it and reject me cause i havent build all the things anyway

i wanna have your all opinion about code quality and any tips and any thing i did wrong

I'm curious where backend folks draw the line between "best tool for each job" and just too much operational surface area.

A typical AI app can easily end up with Postgres/document DB + vector DB + auth + object storage + search + LLM gateway + OCR/document service + workers. Each component is reasonable by itself. Together, a small product suddenly has a platform team's architecture.

That pain is why I started Singlebase - one backend API for the common app + AI primitives. I'm not arguing everything should literally be one database/process. More that the developer-facing surface can be unified while implementations stay specialized underneath.

Would you rather have one opinionated backend abstraction, or keep each system explicit?

Yesterday we finally traced why 96000 model requests a day were costing more than the traffic suggested. About 6720 requests, or 7%, cross a 5 second client timeout. The original model request keeps running while 2 different middleware layers each launch their own fallback. Those timed out customer requests turn into over 20k billable model calls which leaves us paying for 13k duplicate calls every day. At an average 9000 tokens per call, the duplicate branches add nearly 121 million tokens daily.

The first fix was lowering the retry count. It barely moved anything because both middleware layers still believed they owned retry behavior. One layer handled the API boundary and the other wrapped the model client so each saw the timeout independently and started its own fallback. Cancellation propagation never reached the original provider request, either. We found 3 provider request IDs tied back to the same customer request during on-call review, which explained the request fanout much faster than the aggregate retry metric did.

I’ve been digging through prior incident notes and retry guidance because this also makes p95 cost look like a model pricing problem when it’s really retry amplification. Span level token attribution is useful for separating the original branch from duplicate work. One timeout should have one component deciding whether another model call is allowed.

We can centralize retries and propagate cancellation but I’m still worried about other wrappers introducing the same pattern later. 

Curious what patterns work best for catching duplicate branches early before they start pushing up p95 cost.

I am just a student and have only made college projects. I have another college project to work on, but I am aiming to take a professional software engineer approach. An approach like you are building a product for production and making money, which comes with actual responsibility.

My first question is how do professionals trust some open source tool to use in their project? Not just for security but also for reliability. For example, I previously used this tool called Varlock which greatly simplifies storing and retrieving secrets. It supports plugins for a lot of providers, so you don't have to code directly against a single secrets management provider. Most people just use the provider that comes with the platform they are going to host on, but since I could be juggling between different platforms to stay under the free tier, Varlock becomes useful.

But how can you trust it for production purposes, especially that it is relatively new? And how would you trust updating it? Would you manually go and examine the source code for every update? That work should be beyond your scope though. We don't think twice when using Node or Next.js because they are well established and needed projects.

Second, I previously used Clerk as the authentication service. I have never seen Clerk being used in any actual product. It could be possible that they are only using their backend instead of also using Clerk's account portal or their React pages, but why would they?

AI recommended that Auth0 is probably the more professionally used authentication service rather than focusing more on Developer Experience like Clerk. I am not sure if I have ever encountered Auth0 before. Auth0 also has a no-credit card free tier but only allows half as much users as Clerk. So should I still use Clerk? I am looking for professionalism but professionals have money to start with.

For a project with responsibility up to requiring users to pay, how would you rate maintaining your own authentication system (especially for someone who is new and inexperienced to web dev)? I am hosting on VPS, not serverless.

I am learning backend but uses ai for my projects but everyone says that you should use ai for assistance don't use it to write code.

But I am seeing my friends making quite good projects in 15 days using ai where as here it takes me 1 week for setup and implement basic crud operations and auth.they always tells me to let ai write code if you are able to understand the code it's enough.

I want some insights from experienced backend developers who uses ai everyday.

How should I use ai should I write code by myself

Or let ai write it with being able to understand it.

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.