6 ms·

Challenges with distributed systems

188 points by fagnerbrack 7y ago

yamrzou 7y ago
Interesting read. Relatedly, FoundationDB has a distributed testing framework called “Simulation”, which can simulate distributed failures on a single machine (thread!). Quoting from https://pierrezemb.fr/posts/notes-about-foundationdb/ https://pierrezemb.fr/posts/notes-about-foundationdb/ : > We wanted FoundationDB to survive failures of machines, networks, disks, clocks, racks, data centers, file systems, etc., so we created a simulation framework closely tied to Flow. By replacing physical interfaces with shims, replacing the main epoll-based run loop with a time-based simulation, and running multiple logical processes as concurrent Flow Actors, Simulation is able to conduct a deterministic simulation of an entire FoundationDB cluster within a single-thread! Even better, we are able to execute this simulation in a deterministic way, enabling us to reproduce problems and add instrumentation ex post facto. This incredible capability enabled us to build FoundationDB exclusively in simulation for the first 18 months and ensure exceptional fault tolerance long before it sent its first real network packet. For a database with as strong a contract as the FoundationDB, testing is crucial, and over the years we have run the equivalent of a trillion CPU-hours of simulated stress testing.
- epdlxjmonad 7y ago
  Testing a distributed system using a single machine may look like an unorthodox approach. From our experience, however, when building a test framework for a distributed system, everyone would be automatically led to think about building it using a single machine for many benefits, especially saving a lot time. So, I would find it very inefficient to develop a distributed system using only system tests utilizing a cluster of machines, without exploiting integration tests. Nevertheless using just a single thread to simulate everything seems like a great approach.
- jffhn 7y ago
  >simulation of an entire FoundationDB cluster within a single-thread! Reminds me of an InfoQ post about simulating robot swarms in a single thread: https://www.infoq.com/articles/java-robot-swarms/ https://www.infoq.com/articles/java-robot-swarms/ (links to Java libraries for that in the comments) Being able to run everything in a single thread allows to: 1) Do a lot of tests quickly (with virtual time flowing as fast as possible), or arbitrarily slowly if you prefer slow-motion in some contexts. 2) Have determinism. Great for debugging: can reproduce bugs at will, even with full logs on (one trick is to enable them just some time before the bug occurs, when the bug is far from start time). 3) More easily figure out whether a bug is in domain code or a threading issue. 4) Use single-threaded execution as a bench of domain code, and see how much multi-threading/distribution can make them faster or do make them slower. One constraint is that it rules out some programming styles, since the code must never use waiting constructs, like futures (if the single thread starts to wait, it will wait forever since nothing happens outside of it).
  - sitkack 7y ago
    This is an excellent example of having time being a first class input to the evolution of a system. I believe this is fairly common in CEP [1] systems. Similar techniques can be used to handle randomness. I think anytime one writes code that is tied to the wall clock, that a mistake has been made. [1] https://en.wikipedia.org/wiki/Complex_event_processing https://en.wikipedia.org/wiki/Complex_event_processing
  - zzzcpan 7y ago
    > One constraint is that it rules out some programming styles, since the code must never use waiting constructs The constraint here is for testing/simulation to be able to supply their own implementation of waiting constructs, not that waiting constructs cannot be used, of course they can.
    - jffhn 7y ago
      I meant rules out for the domain code that you want to be able to run in a single thread, which should be by far most of the code (unless you ensure that whatever your code wants to wait for, has then necessarily already happened, but that seems brittle to me). Inside of the technical layers you use to run it in multiple threads, there are of course wait/notify mechanisms (or similar). Maybe you thought about wait implementations that would not wait but that would "help", and go on with other computations while the condition is not yet met? If not then I would like you to expand on what you mean, ideally with a few lines of code as a sample to make it clear.
      - zzzcpan 7y ago
        I mean wait implementation doesn't have to actually wait, it just has to register an event handler and store some context to continue with. In the simplest case if we assume there is nothing else to process the condition will be met right in the next iteration and will call back that event handler and continue from that point all without any waiting.
        7y ago
- drej 7y ago
  There is a great talk about this testing, it goes all the way to deterministic seeds and other basics. The level of determinism is admirable. https://youtu.be/4fFDFbi3toc https://youtu.be/4fFDFbi3toc
yamrzou 7y ago
> It’s almost impossible for a human to figure out how to handle UNKNOWN correctly. What does UNKNOWN really mean? Should the code retry? If so, how many times? How long should it wait between retries? It gets even worse when code has side-effects. Inside of a budgeting application running on a single machine, withdrawing money from an account is easy, as shown in the following example. > Figuring out how to handle the UNKNOWN error type is one reason why, in distributed engineering, things are not always as they seem. How are such UNKNOWN errors handled in practice? The article doesn’t talk much about it.
- finaliteration 7y ago
  In my experience designing systems like these: There are no hard and fast rules and you handle them in a way that’s been decided on a case-by-case basis for each system. Some messages may need to keep retrying with an exponential back off indefinitely. Others may need to retry only once and then send an email to someone because two failures in five minutes is a critical failure. You also have to design things so that if one failure occurs, maybe it stops the entire process, or maybe other messages can go through still and you just log the failure. It all comes down to the rules of your business and how critical these systems are. Maybe unknown means “failure” or maybe unknown means “someone should get an alert about this and check it out”. I think it’s hard because there is no highly visible “crash” that occurs like in a non-distributed system when an unexpected exception occurs and the entire program shuts down. Failures often happen silently and it’s difficult to tell where or why something failed. So you have to design each system with that in mind and figure out how each piece needs to deal with uncertainty.
  - stingraycharles 7y ago
    For what it’s worth, in my experience it’s very effective to add this information to the error context: is it a permanent failure (eg validation) or a retryable error. If it is retryable, also add to the error context when it should be retried. This will allow you to handle these errors appropriately without having to handle these things on a case by case basis.
marknadal 7y ago
Hmm, how I handle UNKNOWN in our distributed system (10M+ monthly users running on $0 cost infrastructure, https://github.com/amark/gun https://github.com/amark/gun ) is to say that originator is responsible for retries until satisfactorily ACKed. This means all other nodes in the network (routers, relays, security, storage, etc.) can safely error or not recurse or not retry, without any loss in redundancy guarantees. Either the operation did succeed silently, and it is OK for originator to try again (idempotency keeps this safe), or things never finished processing, and it is OK to try again despite being out of order (CRDTs keep this safe).
- Rapzid 7y ago
  This article brought to mind another article which I personally found a bit more profound: https://bravenewgeek.com/you-cannot-have-exactly-once-delivery/ https://bravenewgeek.com/you-cannot-have-exactly-once-delive...
tyingq 7y ago
Designing your software to work interchangeably with unix domain and regular sockets can also make initial testing much easier. Then you have a no hassle way to simulate lots of ip/port pairs via file names, without port clashes and creating virtual nw interfaces.
AkshatM 7y ago
I wonder if there are any advantages to using formal methods over thread-local simulation in this case. Eighteen months is a long time of development, and there are at least some benefits to catching bugs in the design phase before pursung implementation.
phtrivier 7y ago
Is there an article (in this "Amazon Builder Library" or elsewhere) that offers practical advices about handling such problems ? Or is there nothing else but "do it on a case by case basis ?"
ex_amazon_sde 7y ago
meh
fyp 7y ago
Did anyone else find their "eight failure modes of the apocalypse" incredibly arbitrary given the important sounding name?
tjchear 7y ago
I wonder what if we decide that 'fate sharing' is OK, i.e the client request flow (not the entire process) fails when a network step fails. How long can a system stay operational after it started before the whole thing grinds to a halt? Seconds? Hours? Days? Would there be a huge ding or small ding on the SLIs?

188 points by fagnerbrack 7y ago

Interesting read. Relatedly, FoundationDB has a distributed testing framework called “Simulation”, which can simulate distributed failures on a single machine (thread!). Quoting from https://pierrezemb.fr/posts/notes-about-foundationdb/ https://pierrezemb.fr/posts/notes-about-foundationdb/ : > We wanted FoundationDB to survive failures of machines, networks, disks, clocks, racks, data centers, file systems, etc., so we created a simulation framework closely tied to Flow. By replacing physical interfaces with shims, replacing the main epoll-based run loop with a time-based simulation, and running multiple logical processes as concurrent Flow Actors, Simulation is able to conduct a deterministic simulation of an entire FoundationDB cluster within a single-thread! Even better, we are able to execute this simulation in a deterministic way, enabling us to reproduce problems and add instrumentation ex post facto. This incredible capability enabled us to build FoundationDB exclusively in simulation for the first 18 months and ensure exceptional fault tolerance long before it sent its first real network packet. For a database with as strong a contract as the FoundationDB, testing is crucial, and over the years we have run the equivalent of a trillion CPU-hours of simulated stress testing.

epdlxjmonad 7y ago
Testing a distributed system using a single machine may look like an unorthodox approach. From our experience, however, when building a test framework for a distributed system, everyone would be automatically led to think about building it using a single machine for many benefits, especially saving a lot time. So, I would find it very inefficient to develop a distributed system using only system tests utilizing a cluster of machines, without exploiting integration tests. Nevertheless using just a single thread to simulate everything seems like a great approach.
jffhn 7y ago
>simulation of an entire FoundationDB cluster within a single-thread! Reminds me of an InfoQ post about simulating robot swarms in a single thread: https://www.infoq.com/articles/java-robot-swarms/ https://www.infoq.com/articles/java-robot-swarms/ (links to Java libraries for that in the comments) Being able to run everything in a single thread allows to: 1) Do a lot of tests quickly (with virtual time flowing as fast as possible), or arbitrarily slowly if you prefer slow-motion in some contexts. 2) Have determinism. Great for debugging: can reproduce bugs at will, even with full logs on (one trick is to enable them just some time before the bug occurs, when the bug is far from start time). 3) More easily figure out whether a bug is in domain code or a threading issue. 4) Use single-threaded execution as a bench of domain code, and see how much multi-threading/distribution can make them faster or do make them slower. One constraint is that it rules out some programming styles, since the code must never use waiting constructs, like futures (if the single thread starts to wait, it will wait forever since nothing happens outside of it).
- sitkack 7y ago
  This is an excellent example of having time being a first class input to the evolution of a system. I believe this is fairly common in CEP [1] systems. Similar techniques can be used to handle randomness. I think anytime one writes code that is tied to the wall clock, that a mistake has been made. [1] https://en.wikipedia.org/wiki/Complex_event_processing https://en.wikipedia.org/wiki/Complex_event_processing
- zzzcpan 7y ago
  > One constraint is that it rules out some programming styles, since the code must never use waiting constructs The constraint here is for testing/simulation to be able to supply their own implementation of waiting constructs, not that waiting constructs cannot be used, of course they can.
  - jffhn 7y ago
    I meant rules out for the domain code that you want to be able to run in a single thread, which should be by far most of the code (unless you ensure that whatever your code wants to wait for, has then necessarily already happened, but that seems brittle to me). Inside of the technical layers you use to run it in multiple threads, there are of course wait/notify mechanisms (or similar). Maybe you thought about wait implementations that would not wait but that would "help", and go on with other computations while the condition is not yet met? If not then I would like you to expand on what you mean, ideally with a few lines of code as a sample to make it clear.
    - zzzcpan 7y ago
      I mean wait implementation doesn't have to actually wait, it just has to register an event handler and store some context to continue with. In the simplest case if we assume there is nothing else to process the condition will be met right in the next iteration and will call back that event handler and continue from that point all without any waiting.
      - 7y ago
drej 7y ago
There is a great talk about this testing, it goes all the way to deterministic seeds and other basics. The level of determinism is admirable. https://youtu.be/4fFDFbi3toc https://youtu.be/4fFDFbi3toc

yamrzou 7y ago

> It’s almost impossible for a human to figure out how to handle UNKNOWN correctly. What does UNKNOWN really mean? Should the code retry? If so, how many times? How long should it wait between retries? It gets even worse when code has side-effects. Inside of a budgeting application running on a single machine, withdrawing money from an account is easy, as shown in the following example. > Figuring out how to handle the UNKNOWN error type is one reason why, in distributed engineering, things are not always as they seem. How are such UNKNOWN errors handled in practice? The article doesn’t talk much about it.

finaliteration 7y ago
In my experience designing systems like these: There are no hard and fast rules and you handle them in a way that’s been decided on a case-by-case basis for each system. Some messages may need to keep retrying with an exponential back off indefinitely. Others may need to retry only once and then send an email to someone because two failures in five minutes is a critical failure. You also have to design things so that if one failure occurs, maybe it stops the entire process, or maybe other messages can go through still and you just log the failure. It all comes down to the rules of your business and how critical these systems are. Maybe unknown means “failure” or maybe unknown means “someone should get an alert about this and check it out”. I think it’s hard because there is no highly visible “crash” that occurs like in a non-distributed system when an unexpected exception occurs and the entire program shuts down. Failures often happen silently and it’s difficult to tell where or why something failed. So you have to design each system with that in mind and figure out how each piece needs to deal with uncertainty.
- stingraycharles 7y ago
  For what it’s worth, in my experience it’s very effective to add this information to the error context: is it a permanent failure (eg validation) or a retryable error. If it is retryable, also add to the error context when it should be retried. This will allow you to handle these errors appropriately without having to handle these things on a case by case basis.

marknadal 7y ago

Hmm, how I handle UNKNOWN in our distributed system (10M+ monthly users running on $0 cost infrastructure, https://github.com/amark/gun https://github.com/amark/gun ) is to say that originator is responsible for retries until satisfactorily ACKed. This means all other nodes in the network (routers, relays, security, storage, etc.) can safely error or not recurse or not retry, without any loss in redundancy guarantees. Either the operation did succeed silently, and it is OK for originator to try again (idempotency keeps this safe), or things never finished processing, and it is OK to try again despite being out of order (CRDTs keep this safe).

Rapzid 7y ago
This article brought to mind another article which I personally found a bit more profound: https://bravenewgeek.com/you-cannot-have-exactly-once-delivery/ https://bravenewgeek.com/you-cannot-have-exactly-once-delive...

tyingq 7y ago

Designing your software to work interchangeably with unix domain and regular sockets can also make initial testing much easier. Then you have a no hassle way to simulate lots of ip/port pairs via file names, without port clashes and creating virtual nw interfaces.

AkshatM 7y ago

I wonder if there are any advantages to using formal methods over thread-local simulation in this case. Eighteen months is a long time of development, and there are at least some benefits to catching bugs in the design phase before pursung implementation.

phtrivier 7y ago

Is there an article (in this "Amazon Builder Library" or elsewhere) that offers practical advices about handling such problems ? Or is there nothing else but "do it on a case by case basis ?"

ex_amazon_sde 7y ago

meh

fyp 7y ago

Did anyone else find their "eight failure modes of the apocalypse" incredibly arbitrary given the important sounding name?

tjchear 7y ago

I wonder what if we decide that 'fate sharing' is OK, i.e the client request flow (not the entire process) fails when a network step fails. How long can a system stay operational after it started before the whole thing grinds to a halt? Seconds? Hours? Days? Would there be a huge ding or small ding on the SLIs?