machi/prototype/chain-manager

The chain manager prototype

This is a very early experiment to try to create a distributed "rough consensus" algorithm that is sufficient & safe for managing the order of a Chain Replication chain, its members, and its chain order. A name hasn't been chosen yet, though the following are contenders:

• chain self-management
• rough consensus
• humming consensus
• foggy consensus

Code status: active!

Unlike the other code projects in this repository's prototype directory, the chain management code is still under active development. It is quite likely (as of early March 2015) that this code will be robust enough to move to the "real" Machi code base soon.

The most up-to-date documentation for this prototype will not be found in this subdirectory. Rather, please see the doc directory at the top of the Machi source repository.

Testing, testing, testing

It's important to implement any Chain Replication chain manager as close to 100% bug-free as possible. Any bug can introduce the possibility of data loss, which is something we must avoid. Therefore, we will spend a large amount of effort to use as many robust testing tools and methods as feasible to test this code.

• Concuerror, a DPOR-based full state space exploration tool. Some preliminary Concuerror tests can be found in the test/machi_flu0_test.erl module.
• QuickCheck, a property-based testing tool for Erlang. QuickCheck doesn't provide the reassurance of 100% state exploration, but it proven quite effective at Basho for finding numerous subtle bugs.
• Automatic simulation of arbitrary network partition failures. This code is already in progress and is used, for example, by the test/machi_chain_manager1_test.erl module.
• TLA+ (future work), to try to create a rigorous model of the algorithm and its behavior

If you'd like to work on additional testing of this component, please open a new GitHub Issue ticket with any questions you have. Or just open a GitHub pull request. ^_^

Compilation & unit testing

Use make and make test. Note that the Makefile assumes that the rebar utility is available somewhere in your path.

Tested using Erlang/OTP R16B and Erlang/OTP 17, both on OS X.

If you wish to run the PULSE test in test/machi_chain_manager1_pulse.erl module, you must use Erlang R16B and Quviq QuickCheck 1.30.2 -- there is a known problem with QuickCheck 1.33.2, sorry! Also, please note that a single iteration of a PULSE test case in this model can run for 10s of seconds!

Otherwise, it ought to "just work" on other versions of Erlang and on other OS platforms, but sorry, I haven't tested it.

Testing with simulated network partitions

See the doc/chain-self-management-sketch.org file for details of how the simulator works.

In summary, the simulator tries to emulate the effect of arbitrary asymmetric network partitions. For example, for two simulated nodes A and B, it's possible to have node A send messages to B, but B cannot send messages to A.

This kind of one-way message passing is nearly impossible do with distributed Erlang, because disterl uses TCP. If a network partition happens at ISO Layer 2 (for example, due to a bad Ethernet cable that has a faulty receive wire), the entire TCP connection will hang rather than deliver disterl messages in only one direction.

Testing simulated data "repair"

In the Machi documentation, "repair" is a re-syncronization of data between the UPI members of the chain (see below) and members which have been down/partitioned/gone-to-Hawaii-for-vacation for some period of time and may have state which is out-of-sync with the rest of the active-and-running-and-fully-in-sync chain members.

A rough-and-inaccurate-but-useful summary of state transitions are:

down -> repair eligible -> repairing started -> repairing finished -> upi

    * Any state can transition back to 'down'
    * Repair interruptions might trigger a transition to
      'repair eligible instead of 'down'.
    * UPI = Update Propagation Invariant (per the original
            Chain Replication paper) preserving members.
            
            I.e., The state stored by any UPI member is fully
            in sync with all other UPI chain members, except
            for new updates which are being processed by Chain
            Replication at a particular instant in time.

In both the PULSE and convergence_demo*() tests, there is a simulated time when a FLU's repair state goes from "repair started" to "repair finished", which means that the FLU-under-repair is now eligible to join the UPI portion of the chain as a fully-sync'ed member of the chain. The simulation is based on a simple "coin flip"-style random choice.

The simulator framework is simulating repair failures when a network partition is detected with the repair destination FLU. In the "real world", other kinds of failure could also interrupt the repair process.

The PULSE test in machi_chain_manager1_test.erl

As mentioned above, this test is quite slow: it can take many dozens of seconds to execute a single test case. However, the test really is using PULSE to play strange games with Erlang process scheduling.

Unfortnately, the PULSE framework is very slow for this test. We'd like something better, so I wrote the machi_chain_manager1_test:convergence_demo_test() test to use most of the network partition simulator to try to run many more partition scenarios in the same amount of time.

machi_chain_manager1_test:convergence_demo1()

This function is intended both as a demo and as a possible fully-automated sanity checking function (it will throw an exception when a model failure happens). It's purpose is to "go faster" than the PULSE test describe above. It meets this purpose handily. However, it doesn't give quite as much confidence as PULSE does that Erlang process scheduling cannot somehow break algorithm running inside the simulator.

To execute:

make test
erl -pz ./.eunit deps/*/ebin
ok = machi_chain_manager1_test:convergence_demo1().

In summary:

• Set up four FLUs, [a,b,c,d], to be used for the test
• Set up a set of random asymmetric network partitions, based on a 'seed' for a pseudo-random number generator. Each call to the partition simulator may yield a different partition scenario ... so the simulated environment is very unstable.
• Run the algorithm for a while so that it has witnessed the partition instability for a long time.
• Set the partitions definition to a fixed [{a,b}], meaning that FLU a cannot send messages to FLU b, but all other communication (including messages from b -> a) works correctly.
• Run the algorithm, wait for everyone to settle on rough consensus.
• Set the partition definition to wildly random again.
• Run the algorithm for a while so that it has witnessed the partition instability for a long time.
• Set the partitions definition to a fixed [{a,c}].
• Run the algorithm, wait for everyone to settle on rough consensus.
• Set the partitions definition to a fixed [], i.e., there are no network partitions at all.
• Run the algorithm, wait for everyone to settle on a unanimous value of some ordering of all four FLUs.