When I started building a news aggregator, I honestly thought it would be straightforward. Pull some articles, show them in a feed, maybe add filters later. Nothing fancy.
I was wrong.
The UI came together quickly. The real challenges were all in the background - where the data comes from, how often it updates, and what happens when things quietly stop working.
Scraping felt clever… at first
My first approach was scraping. It felt flexible and fast. The news was public anyway, so why not just grab it directly?
For a short time, it worked.
Then small things started breaking. Not in obvious ways. A missing article here. A delayed update there. Sometimes a whole source would silently stop working because a layout changed.
That was the worst part - failures did not scream. They whispered. And by the time I noticed, the data was already incomplete.
More sources didn’t make things better
At one point, I thought the solution was adding more sources. More coverage, more news, better product. That assumption did not hold up.
What I actually got was messy data. Different formats, inconsistent timestamps, repeated stories with slightly different titles. Cleaning all of that took more time than I expected.
I learned pretty quickly that clean data beats more data. A smaller, well-structured feed was far more useful than a noisy one.
“Real-time” is not as clear as it sounds
Every tool claims to be real-time. In practice, that word is vague.
Some updates were fast. Others lagged behind. And users noticed. Even a small delay made the app feel slow, especially when the same story was already trending elsewhere.
I stopped trusting labels and started measuring actual update behavior. That told me more than any feature page ever did.
Deduplication is a real problem
One breaking story can show up from ten different publishers within minutes. Without proper handling, your feed becomes unreadable.
At first, I underestimated this. Simple matching did not work. Slight wording changes created duplicates, and the feed filled up with the same story over and over.
Good aggregation is not just about collecting news. It is about deciding what not to show.
Maintenance quietly eats your time
This part surprised me the most.
Each workaround felt small. Each fix felt temporary. But over time, maintaining scrapers and custom logic started consuming more effort than building new features.
That is when I started looking at managed options. Using a structured News API reduced a lot of friction. In my case, tools like Newsdata.io helped by handling multiple sources through a single, predictable interface.
It was not about adding features. It was about removing stress.
Users don’t care how you built it
This sounds obvious, but it took me a while to internalize it.
Users don’t care whether news comes from scraping, RSS, or an API. They care that it shows up on time and does not randomly disappear. Every missed update slowly chips away at trust.
Once I started optimizing for reliability instead of control, my decisions got simpler.
What I’d do differently next time
If I were starting again, I would plan for failure earlier. I would assume things will break and choose inputs that break less often. I would also think about maintenance from day one, not as a future problem.
Building a news aggregator taught me that data reliability is a feature, even if users never see it directly.
Final thought
A news aggregator looks simple from the outside. On the inside, it is a constant balancing act between speed, accuracy, and sanity.
The biggest lesson I learned is this - once your product depends on news every day, stability matters more than clever solutions. Accepting that early would have saved me a lot of time.
Hopefully, it saves you some too.
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