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The system that's my benchmark to go up against has seen 6 seconds of downtime in 25 years. Does that give you a better perspective for my availability concern

The system that's my benchmark to go up against has seen 6 seconds of downtime in 25 years. Does that give you a better perspective for my availability concerns? I also don't have "on demand" infrastructure. I have to deploy to a fixed footprint of bare metal hardware. I'm "utterly blithe" about inconsistency being my best case for a variety of reasons: 1) I know my use case extremely well. 2) I know that within that use case there are several places where availability is the #1, #2, and #3 priority because the system being unavailable for any time at all has a non-trivial direct financial impact. 3) I know within that use case where there are necessary points of consistency and how to move them out of the critical path that requires extreme availability. 4) I know exactly the problem that CRDTs solve for me, and exactly why I need them in this case, and how to avoid them with simpler immutable/idempotent write patterns where possible. 5) I have to be able to tolerate very high proportion of the infrastructure experiencing temporary and/or permanent failure because the places I have to deploy into are no where near the level of reliability of even a low-mid tier data center in the US. Janky telcos, natural disasters, malicious operators, and flimsy power delivery are the norm.

jasonwatkinspdx 11y ago
And what consistency assurances does it provide? Edit: I see you edited in a longer comment after my question above. I was just curious, not looking to pick a fight. Suffice it to say we have very different perspectives on how to attack those requirements. I'm bowing out now, cheers!.
- im_down_w_otp 11y ago
  The problem is this: 1) Anything that is suggested which avoids data loss via consistency models is going to reduce my availability to unacceptable levels. 2) Anything that is suggested which keeps my availability up where it needs to be and doesn't use CRDTs, and/or a sufficiently similar semantic guarantee, is going to silently lose data due to "lost-updates" (ACK'd writes that get obliterated during conflict merges and are now gone forever). At a minimum I need sibling behavior for conflicting writes to ensure that some half-baked LWW strategy that's barely better than "pick at random" doesn't kill my data (which has very high regulatory and audit requirements around it), and then taking that a step further CRDTs, implemented correctly, provide me a nice interface for interacting with multiple version conflicts and resolving them in coherent ways without forcing me, or my other developers, to have to think up case-by-case resolution strategies and verify their correctness. There really isn't a tremendous amount of complexity to using CRDTs. That's the point of them. They're easy to use. The complexity I'd really like to avoid if possible by avoiding CRDTs is the cognitive burden my team needs to have around distributed data and all it's horrible nuances to satisfy our use case. The knowing when and why to use them, not so much the how. "At this kind of request rate I'd honestly just shove things in postgres and call it good." is very, very far away from a workable solution because my problem isn't request rate. The number of ops/sec could be hundreds or millions, and it doesn't really change my actual problem. No matter what the request rate is I could just write to a bunch of postgres instances that have a chash ring overlaid onto them... except now I have to deal with my actual problem still, which is redundancy, and local consistency in any postgres replica doesn't guarantee me much, I can't introduce a strong coordinator like a consensus protocol over the top of them, because it dumps my availability, and so I have to figure out how to safely deal with merge conflicts between the replicas... now I'm stuck figuring out how to build CRDTs on top of postgres anyway. So... what exactly did I win?

jasonwatkinspdx 11y ago

And what consistency assurances does it provide? Edit: I see you edited in a longer comment after my question above. I was just curious, not looking to pick a fight. Suffice it to say we have very different perspectives on how to attack those requirements. I'm bowing out now, cheers!.

im_down_w_otp 11y ago
The problem is this: 1) Anything that is suggested which avoids data loss via consistency models is going to reduce my availability to unacceptable levels. 2) Anything that is suggested which keeps my availability up where it needs to be and doesn't use CRDTs, and/or a sufficiently similar semantic guarantee, is going to silently lose data due to "lost-updates" (ACK'd writes that get obliterated during conflict merges and are now gone forever). At a minimum I need sibling behavior for conflicting writes to ensure that some half-baked LWW strategy that's barely better than "pick at random" doesn't kill my data (which has very high regulatory and audit requirements around it), and then taking that a step further CRDTs, implemented correctly, provide me a nice interface for interacting with multiple version conflicts and resolving them in coherent ways without forcing me, or my other developers, to have to think up case-by-case resolution strategies and verify their correctness. There really isn't a tremendous amount of complexity to using CRDTs. That's the point of them. They're easy to use. The complexity I'd really like to avoid if possible by avoiding CRDTs is the cognitive burden my team needs to have around distributed data and all it's horrible nuances to satisfy our use case. The knowing when and why to use them, not so much the how. "At this kind of request rate I'd honestly just shove things in postgres and call it good." is very, very far away from a workable solution because my problem isn't request rate. The number of ops/sec could be hundreds or millions, and it doesn't really change my actual problem. No matter what the request rate is I could just write to a bunch of postgres instances that have a chash ring overlaid onto them... except now I have to deal with my actual problem still, which is redundancy, and local consistency in any postgres replica doesn't guarantee me much, I can't introduce a strong coordinator like a consensus protocol over the top of them, because it dumps my availability, and so I have to figure out how to safely deal with merge conflicts between the replicas... now I'm stuck figuring out how to build CRDTs on top of postgres anyway. So... what exactly did I win?