4 ms·

I work fairly regularly with our mainframe team, and the general reasoning boils down to massive parallelism and consistency when processing critical data. The

I work fairly regularly with our mainframe team, and the general reasoning boils down to massive parallelism and consistency when processing critical data. The number of rows our mainframe can process and write with perfect accuracy is leagues ahead of what similarly priced commodity hardware could achieve. There’s a reason the world still pretty much runs on COBOL/Natural and a hardware design from the 70s, it worked well then and has worked well ever since. Slightly related but I’d describe most of my role being getting data from our micro-services down into the mainframe in a format it understands so we can do ‘something’ with it.

bubblethink 7y ago
Interesting. So something like google bigquery (or any of the various saas offerings by others) would not be a good match for this problem space ? For massive parallelism, we have GPUs, accelerators, and database products built on these things (admittedly, still somewhat new). By consistency, do you mean tolerance to transient errors and the like ? i.e. Beyond whatever you get with ECC ? Or are you talking about memory consistency models ? I am just constantly surprised that on the one hand FAANG+ which run so much of the internet economy do not use mainframes, and yet banks do.
- bendbro 7y ago
  The promise of the cloud is that it provides you with "trivially", "infinitely", "cost-efficiently" scalable infrastructure. Banks don't need any of that. They can buy a $100k (?) mainframe, a hundred or so devs, and leave that part of the business on autopilot for 20+ years. Why even bother futzing around in the cloud?
  - rbanffy 7y ago
    > They can buy a $100k (?) mainframe, You'll find those on e-Bay. A new one will be significantly more expensive.
    - wongarsu 7y ago
      Compared to the cost of software engineers a few million every few decades for a mainframe aren't that significant either way.
      - rbanffy 7y ago
        Also, reaching the same kind of capabilities would require a substantial investment in R&D. IBM has been developing zOS for more than 50 years now.
- PebblesHD 7y ago
  In addition to what bendbro suggests, which is actually quite close to reality if oversimplified, banks also have sovereignty concerns with data that may have additional classification and regulatory strings attached. In Australia where I’m based, ‘material’ data such as financial and audit information must be kept in country and its veracity attested to, which is why so many large banks here at least still have big iron in managed data centres for most of their core transactional systems. Edited to specify which sibling I was referring to.
- unionpivo 7y ago
  Banks used to store peoples gold, now they store data. I don't think any serious bank will consider trusting outsider with their core business. And mainframes are essentially early on premises clouds. And today's, cloud offerings still don't do what mainframes did as easily. (and there are several things that cloud does offer that mainframes can't do)
  - Merrill 7y ago
    Outsourcing of financial services processing has been a big business for decades. However it is usually provided to small/medium banks or credit unions by specialized firms or by big banks. A big bank will usually do its own ledger processing. A good configuration is to process in two pairs of data centers more than 200 miles apart in different electric utility interconnection regions, e.g. Arlington/Fort Worth and Dayton/Springfield. Archival storage of transactions may involve additional centers. https://en.wikipedia.org/wiki/IBM_Parallel_Sysplex#Geographically_Dispersed_Parallel_Sysplex https://en.wikipedia.org/wiki/IBM_Parallel_Sysplex#Geographi...
- hcarvalhoalves 7y ago
  Getting distributed systems correct is very hard. Mainframe architecture allows one to program and deploy as if you had a giant computer with consistent transactions for the most part. Since banks were the early adopters of computation in large scale it’s clear why most still run on mainframe - the transition to cloud architecture isn’t a simple translation, you need to glue a lot of things together to the same levels of parallelism, and probably sacrifice some consistency that you get “for free” on mainframe architecture. Cloud is cheaper ($ per cycle) at the expense of human brain power to glue it all together.
- 0815test 7y ago
  > (admittedly, still somewhat new) That's the whole explanation right there. "Move fast and break things" is not the way that sort of business works.
- deleted 7y ago
  [deleted]
- wongarsu 7y ago
  Give me a message queue that guarantees exactly-once-delivery to coordinate a cluster of transaction processing mashines and we can talk about banks using commodity hardware.

bubblethink 7y ago

Interesting. So something like google bigquery (or any of the various saas offerings by others) would not be a good match for this problem space ? For massive parallelism, we have GPUs, accelerators, and database products built on these things (admittedly, still somewhat new). By consistency, do you mean tolerance to transient errors and the like ? i.e. Beyond whatever you get with ECC ? Or are you talking about memory consistency models ? I am just constantly surprised that on the one hand FAANG+ which run so much of the internet economy do not use mainframes, and yet banks do.

bendbro 7y ago
The promise of the cloud is that it provides you with "trivially", "infinitely", "cost-efficiently" scalable infrastructure. Banks don't need any of that. They can buy a $100k (?) mainframe, a hundred or so devs, and leave that part of the business on autopilot for 20+ years. Why even bother futzing around in the cloud?
- rbanffy 7y ago
  > They can buy a $100k (?) mainframe, You'll find those on e-Bay. A new one will be significantly more expensive.
  - wongarsu 7y ago
    Compared to the cost of software engineers a few million every few decades for a mainframe aren't that significant either way.
    - rbanffy 7y ago
      Also, reaching the same kind of capabilities would require a substantial investment in R&D. IBM has been developing zOS for more than 50 years now.
PebblesHD 7y ago
In addition to what bendbro suggests, which is actually quite close to reality if oversimplified, banks also have sovereignty concerns with data that may have additional classification and regulatory strings attached. In Australia where I’m based, ‘material’ data such as financial and audit information must be kept in country and its veracity attested to, which is why so many large banks here at least still have big iron in managed data centres for most of their core transactional systems. Edited to specify which sibling I was referring to.
unionpivo 7y ago
Banks used to store peoples gold, now they store data. I don't think any serious bank will consider trusting outsider with their core business. And mainframes are essentially early on premises clouds. And today's, cloud offerings still don't do what mainframes did as easily. (and there are several things that cloud does offer that mainframes can't do)
- Merrill 7y ago
  Outsourcing of financial services processing has been a big business for decades. However it is usually provided to small/medium banks or credit unions by specialized firms or by big banks. A big bank will usually do its own ledger processing. A good configuration is to process in two pairs of data centers more than 200 miles apart in different electric utility interconnection regions, e.g. Arlington/Fort Worth and Dayton/Springfield. Archival storage of transactions may involve additional centers. https://en.wikipedia.org/wiki/IBM_Parallel_Sysplex#Geographically_Dispersed_Parallel_Sysplex https://en.wikipedia.org/wiki/IBM_Parallel_Sysplex#Geographi...
hcarvalhoalves 7y ago
Getting distributed systems correct is very hard. Mainframe architecture allows one to program and deploy as if you had a giant computer with consistent transactions for the most part. Since banks were the early adopters of computation in large scale it’s clear why most still run on mainframe - the transition to cloud architecture isn’t a simple translation, you need to glue a lot of things together to the same levels of parallelism, and probably sacrifice some consistency that you get “for free” on mainframe architecture. Cloud is cheaper ($ per cycle) at the expense of human brain power to glue it all together.
0815test 7y ago
> (admittedly, still somewhat new) That's the whole explanation right there. "Move fast and break things" is not the way that sort of business works.
deleted 7y ago
[deleted]
wongarsu 7y ago
Give me a message queue that guarantees exactly-once-delivery to coordinate a cluster of transaction processing mashines and we can talk about banks using commodity hardware.