My tech stack is java springbooot postgres, what are other essentials that a backend dev should know

heyhey,

during the prev railway accident there is more and more comments thoughout the community to migrate and it feels people even worry about their hobby projects to be moved to gcp, aws or other alternatives.

on the other hand, I would like to hear from people who have relatively big systems deployed on railway, what's your take?

in my case i've started company with other founders as tech lead, I had to do not only development, product, support and other parts that I just wanted to get rid of devops overhead.

railway looked like ideal case for me, with proper tools around it on about 60-80$ budget we have millions of requests, multiple crons, services, redis etc. and for me it runs pretty good. (if we ignore the last leak and few incidents in the past, but in reality even cloudlfare had their downtimes, so no one is protected) so we can think that thunder doesn't hit the same place twice lol.

I'm curious if anyone here is running something at a similar or larger scale, and whether you've hit any limitations or started considering alternatives.

Iam beginner at backend I need a road map.

I have basics of python. I feel confused about all backend resources

I am looking to build a CRUD application, which can store and authenticate users, preferably in large amounts. I have so far somewhat felt like I would be benefiting from using Laravel, since I have some PHP and SQL experience, but I am a bit worried that I am approaching this from a sense of comfortability rather than choosing the better framework.

What thoughts are there generally in the backend community with regards to which framework is considered the "better ones"? Is there any attitude towards something like Laravel that would speak against using it?

I am early in my backend career and learning APIs, databases, authentication, system design, and production debugging. For people who have been doing backend work for a while, which skill made the biggest difference early on, and why?

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So I’ve learned Python and Django, although I’m still a beginner. I’ve also learned C++ through courses, and I’ve learned what algorithms and data structures are. Sometimes, I build small projects with the help of AI. It gives me the complete plan, and I follow it and write the code myself. If there’s an error, I ask AI to give me hints about where the problem is instead of fixing everything for me. I also try to solve problems on LeetCode every day.

So, my question is: Am I on the right path?

I feel like I’m stuck in a loop, and there’s something missing that I’m supposed to learn, but I don’t know what it is.

I’ve never done an internship or worked in programming before. I’ve also never read any books except one that I used to learn Python.

So, yes, I honestly don’t know what to do next. Are there any books I should read to become a better backend developer?

Hello all. I am a hobbyist coder with 3 years of Java experience mixed with some Kotlin and a bit of C, currently pursuing a degree in software engineering. I would like to make a career in backend development and I was wondering if an IRC server that I could build with Spring (Boot), and the perhaps deploy in a free tier Oracle server with docker would be a nice project to get myself familiarized with the required knowledge. Any suggestions are welcome.

I wrote a practical guide to load balancing—how traffic gets distributed, what happens when servers fail, and how deployments fit in. Give it a read and let me know what you think. Anything unclear or missing?

Hey everyone 👋

I'm a final-year Computer Science student learning backend development with Node.js, Express.js, MongoDB, and REST APIs.

I've built projects using the MERN stack, and I'm now trying to go beyond CRUD operations and understand how real backend systems work.

I'm particularly interested in learning more about:

• Authentication and authorization (JWT, refresh tokens, sessions)
• Database design, indexing, and query optimization
• Redis, caching, and performance
• WebSockets and real-time communication
• Error handling, logging, testing, and security
• System design and scalability

I don't want to just follow tutorials and copy code. I want to understand why things are designed a certain way and how to make better engineering decisions.

For developers working in backend engineering:

1. What skills made the biggest difference when you moved beyond beginner-level backend development?
2. What mistakes should beginners avoid?
3. Which projects would you recommend to develop real backend engineering skills?

I'd appreciate honest advice, learning resources, and lessons from your own experience. Thanks! 🙌

I'm building a football intelligence web app, and I'd appreciate some advice from developers who've operated similar systems in production.

I launched v1.0 as a closed beta earlier this year. Users had to register and be granted access, and 25 people signed up to test it.

The beta ran for approximately five weeks.

One of the biggest lessons was that building a working application and keeping it running reliably are two very different challenges.

In v1.0, I had all the automated jobs running through one cron job. Initially, things worked reasonably well, but over time the automation became increasingly unreliable.

Jobs started failing more frequently, and failures could affect the wider application. By the final week, parts of the platform weren't behaving as intended.

Interestingly, the betting model finished profitable during the beta. But that wasn't enough. The underlying application was becoming unreliable, and a profitable model isn't much use if the system supporting it can't operate consistently.

I decided to take v1.0 down and rebuild the application from the ground up as tactica. 2.0, using what I'd learned from operating the beta.

The goal is a reliable, publicly available application that can operate unattended, recover safely from failures and keep its different responsibilities isolated.

The 2.0 build is currently deployed privately on Render and Vercel while I develop and test it in a real hosted environment. It isn't publicly launched yet.

The new architecture

I'm using one canonical PostgreSQL database hosted on Render, with separate background workers responsible for different stages of the application's lifecycle.

1. Football Data (operational)

Acquires football data from external APIs, validates observations and maintains the factual records used throughout the application.

This includes fixtures, results, team data, player data and match statistics.

2. Match Intelligence (planned)

Consumes the authoritative football data and produces pre-match intelligence, including model expectations across different football markets.

The intention is to preserve published intelligence rather than continually rewriting previous conclusions.

3. Betting Intelligence (planned)

Consumes Match Intelligence alongside bookmaker odds and market information.

It evaluates whether the football opinion qualifies as a betting recommendation, including situations where the correct decision is to make no recommendation.

4. Performance Intelligence (planned)

Evaluates completed intelligence and recommendation decisions against actual match results.

This includes model performance, recommendation quality, system integrity and financial outcomes.

Each worker has its own responsibilities, execution controls and database permissions.

They're not four identical queue consumers. They perform different stages of a connected process, and downstream workers depend on authoritative outputs from earlier stages.

The Football Data worker is operational. The other three are still being built and qualified.

What I'd like advice on

1. PostgreSQL and deployment compatibility

With multiple independently deployed workers depending on the same populated PostgreSQL database, how do you safely evolve the schema?

Have you found particular migration strategies, compatibility windows or deployment sequences reliable in practice?

2. Worker reliability and recovery

What problems have you encountered when moving from one automation process to several independently running workers?

I'm particularly interested in duplicate processing, idempotency, interrupted jobs, graceful shutdown, retries and preventing downstream workers from acting on incomplete upstream data.

3. Render and production operations

If you've run multiple workers against a shared PostgreSQL database on Render or a similar managed platform, what surprised you?

Database connections, memory usage, deployments, monitoring, recovery, resource consumption and costs are all areas I'm thinking about.

What I'm trying to avoid

My biggest concern is repeating the v1.0 experience in a more complicated form.

I don't want four independent workers that look architecturally cleaner but introduce new failure modes that I haven't properly anticipated.

I'm not looking for a wholesale redesign or a recommendation to migrate everything to Kubernetes. The separation of responsibilities is deliberate.

I'd particularly appreciate hearing from people who've experienced similar failures, what caused them, and what they would test before activating the additional workers.

I'm trying to build something that can operate reliably without needing constant manual intervention.

What would you be most concerned about with this setup?

After how many years of experience did you become Senior Software Engineer and how can I reach that level? What courses or books do you recomend? What skills are most needed?

CS Junior here. I am late but better late than never. For the last 2 years I was juggling between 3 fields, learning very little about them with no internships. Now I have decided to focus one of them. I have decided to focus on Full Stack. and possible towards AI and DevOps if got time. Because I have been told fullstack is just a tool and you need "uniqueness" with it (not sure if it true).
My Current Stack:

• Frontend/State: JavaScript, React, Redux Toolkit, Zod
• Backend/DB: Node.js, Express, MongoDB, REST APIs, Supabase, FlaskAPI
• Other/DevOps: Docker, C++, Python, Rust and deployments (vercel, render).

In the AI portion, I know basic Data handling and Classic ML Algos. In terms of projects I have made some smaller common ones but is not able to make portfolio heavy ones. I will spent next 6 months learning and making a profile based on it so that i can land my first internship.

My Questions:

1. What are some unique, non-generic project ideas that would make a senior engineer actually want to look at my GitHub code? The reason I didn't even try making projects is because everyone has everything.
2. What is the biggest gap between a beginner MERN developer and someone ready for a production-level backend internship?
3. What kind of intermediate/advanced backend architectures should I implement to stand out? ( microservices, event-driven, or combining my C++ foundation with Node)?
4. Is there a need to learn to add more to tech stack ?

I am confused right now as i have no idea how to proceed. So Need Advice and suggestions.

Thanks !

I recently migrated a production relationship from one-to-many to many-to-many.

The challenging part wasn't creating the junction table. It was maintaining backward compatibility while introducing the new relationship, migrating existing data, and keeping different API consumers working during the transition.

I documented the approach, including the migration strategy and the lessons learned.

I'm curious how other backend engineers approach this. Do you prefer temporary dual writes, versioned APIs, or another migration strategy?

I'm curious how other backend developers experiment with system performance beyond local testing.

How do you explore bottlenecks, queue buildup, database saturation, or what happens when a downstream service slows down?

Do you use tools like k6, Locust, or something else? I'm especially interested in tools that help visualize how traffic moves through a system without setting up a full environment.

What works well for you, and what's missing?

I feel a bit overwhelmed when learning new things, am at the point where I am moving out from the basics and i know that it is natural to feel overwhelmed in this step but that doesn't make it easier, each time i learn something new i feel like i forgot previous things, i remember the general idea but forget the syntax

Has this happened to you before and how did you move past it?

I am building a real time app that also has a group chat. I will need a websocket connection for this, which introduces complexity at the system level for scaling, but that's not the point of this post.

From what I've read, websocket gives low latency bidirectional byte channel between a client and server with no protocol. REST gives you a request response protocol with status codes and integration with infra that has been using it for a long time.

I will have to open a websocket connection for my app to work. So I am tempted to use websocket for CRUD operations on my app as well that are outside of the group chat. Like when user changes settings or changes profile picture I might as well send a websocket message which has lower latency compared to an HTTP request which will create a new connection on each request. For some reason I think this is not the best practice. Do other apps do it this way? I see apps like reddit or insta where when you change your user settings they are instant, like toggling a setting on/off. It doesn't look like a POST request.

iam learning backend in .net core
i not the best at remembering syntax
like for example to make a db :
builder.Services.AddDbContext<DbContextClassName>(
options => { options.UseSqlServer( "ConnectionString "));}

i understand the concept but not the syntax when i make a project i look at the syntax from my notes is it ok?

Hey everyone! 👋

I'm Mohaned, a software developer and the creator of the MOHANED YouTube channel.

I enjoy building backend systems and understanding what happens when things go wrong.

I've been creating practical backend engineering videos focused on problems developers actually encounter, not just following tutorials or writing basic CRUD endpoints.

Some of the things I've been working on:

• Building microservices with Spring Boot, Kafka, PostgreSQL, and Docker.
• Optimizing an API from 92 seconds down to 5ms.
• Testing what happens when 1,000 users hit a backend.
• Debugging database bottlenecks and connection limits.
• Building secure authentication, webhooks, and real-world APIs.
• Exploring distributed systems, queues, caching, and production failures.

Java and Spring Boot are my main tools, but the goal is broader: understanding how to build backend systems that are secure, efficient, and reliable.

I'm here to learn from other developers, share what I'm building, and get feedback on the technical challenges worth exploring next.

I'm curious: what's one backend problem you wish more tutorials covered with real examples?
Peace

i have competed the JDBC ORM and Hibernate and spring data jpa what should learn next