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Comment by jeremyjh | Hacker News Reader

I think they still make a lot of money from their legacy business, z/OS & mainframes, DB/2 etc still run basically all large banks, insurance companies and many other types of businesses. IBM can charge whatever they want for the hardware and services to support these things because their customers have no alternative. So they have just been farming this for decades, and can afford not to succeed at anything else (so they don't).

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Just like Oracle.

No one talks about Oracle. But they're still around. We did a major tech project to migrate off of Oracle after an acquisition of a large org that was running it.

It was a year-long effort to migrate. But it was worth it since Oracle renewal costs were going to be nearly 50% of our IT budget.

a) Oracle is proven at scale.

b) Large global talent pool of Oracle experts.

c) First-class professional support.

Not everyone is looking to innovate on their database. Many just want something that is reliable and easily supported.

>c) First-class professional support

Ah, this was a sarcastic comment! It was, right?

Oracle is also arcane, buggy and poorly documented (the buggy really surprised me when I first started using it). And there are much less resources online compared to the other big databases.

This is hilarious.

I did a similar year long migration off Oracle. What helped were all the automated integration tests that had been built previously. It made it so much easier to verify that everything would work after the migration.

They also run th backed for major airline booking systems, and charge outrageous amounts.

The biggest airline booking system, Amadeus, can actually run on Kubernetes and some airlines are migrating to it.

Fun fact: a few years back Amadeus employees were in the top 15 of k8s contributors by company.

I’d love to see their architecture. Do they publish much?

Is airline booking software very complex? I don’t see why that software would necessitate the updating of k8s.

> Is airline booking software very complex?

If this is surprising to you, you have no idea.

It's a 24/7 business as a start. Multiple flights, multiple fares, multiple ways of booking a flight, airline agreements, etc

Yes, it is. Read up on the history of SABRE and you’ll get pretty much the entire history of digital computing, post-UNIVAC, in the process.

I’m not sure about the architecture, but airline booking is very complex. You basically need to support a traveling salesman algorithm. It’s also one of the original use cases for large scale computers. The Sabre airline booking program dates back to the 60’s so it’s also very legacy. The Arstechnica article (below) has a good history of the original military program and how it helped to spin out airline booking.

Modernization for these systems was probably long overdue.

https://www.ibm.com/ibm/history/ibm100/us/en/icons/sabre/

https://arstechnica.com/science/2022/01/the-most-important-c...

I recall talking to people who worked at a company that competed w/ Sabere/IBM

There was a project they did not want to do. To avoid saying "no" and risking the relationship they quoted what they thought was an outrageous price, expecting to loose. The customer said yes. They had underestimated how much IBM had been gouging them for so long.

It's kind of similar in some ways to the traveling salesman problem. Which is not considered np-hard.

"How do you get to tokyo from paris", the cheapest, the shortest time, the least layovers, add a stop in X, etc. Not that easy.

Then you have to remember all the stuff under the hood like how are you caching all that information, how do you actually register the sales of all those tickets. Are they in your flight alliance? Are they goign through your regional airline systems too?

I would never want to touch that stuff. Way too hard. Way too many legacy systems powering it too, probably.

Which is now owened by google and probably powering google flights lol

Every single airline they ingest probably has a phone book sized list of special cases and edge conditions that are distinct and unique. Multiply that by every airline on the platform and every consumer of the dataset and yeah… it’s incredibly complex.

Not to mention the uptime requirements and other SLAs in place (which probably are all different for each contract they sign)… yup. It’s probably a monster.

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