[
https://issues.apache.org/jira/browse/HDDS-15501?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Ivan Andika updated HDDS-15501:
-------------------------------
Description:
Currently, we only test Ozone using the traditional UT, IT, Acceptance Tests.
We had a MiniOzoneChaosCluster (fault injection testing), but it seems unused.
I propose to introduce a distributed system testing and proofs system so that
we can have the Ozone spec as the shared mental model. Some of the regressions
for issues like breaking majority commit contract (HDDS-15052) is not detected
since we don't have the spec as the source of truth. Additionally sometimes
simply we use our intuitions to guide our implementation and fixes which can
cause regressions (for example, a lot of ReplicationManager fixes are only done
only when there is an issue in productions).
This is a parent task for the effort to introduce distributed system testing
and proofs to test the correctness of Ozone implementation. For example,
* Partial write commit and all commit semantics
* Container state transitions (under failures)
* Replication manager & container balancer correctness
** Replication manager should not cause infinite replications, it should end
in a steady state
* Container state and replica management
** How to appease eventually consistent container replica management (through
heartbeat) and strongly consistent container state (through Ratis)
* End to end block deletion guarantee
** Ensure that block are deleted
* Ensure that container replica numOfKeys and numOfBytes is accurate
* OM bucket quota accuracy issue: Ensure that OM bucket quota should not
become negative
* OM and SCM linearizability guarantee with the table cache and (double)
transacstion buffer mechanisms
* Container reconciliation guarantee
Distributed system testing tools:
- Jepsen, Ellen, Maelstorm
- Fray
- Hypothesis (Hegel)
- Antithesis (paid)
Distributed system proofs:
- TLA+
-- Specula ([https://github.com/specula-org/Specula]) : AI generated TLA+
already used to find some Raft bugs
- Lean4
- P framework
Real systems
- 3FS ([https://github.com/deepseek-ai/3FS/tree/main/specs]) - uses P framework
- AWS S3
([https://cacm.acm.org/practice/systems-correctness-practices-at-amazon-web-services/]
and [https://p-org.github.io/P/casestudies/#case-studies])
- etcd robustness test
([https://github.com/etcd-io/etcd/tree/main/tests/robustness]) - Uses
antithesis (among other things)
I prefer if we can start with P framework since some storage systems already
used it.
In the future, we can support Deterministic Simulation Testing
([https://antithesis.com/docs/resources/deterministic_simulation_testing]).
However, this requires a lot of efforts and very invasive since we need to make
all Ozone implementations to be testable by the simulation framework so it's
not going to happen anytime soon. Some of the deterministic simulation testing
framework is Madsim (Rust), Turmoil (Rust), BUGGIFY (C++, FoundationDB),
Tickloom (Java, [https://github.com/unmeshjoshi/tickloom]), Vortex (Zig, used
by TigerBeetle). We can start taking look at Tickloom for testing in Java.
Having a real industry-recognized spec helps to instil confidence in Ozone
robustness. More importantly, distributed system testing allows us to have
confidence that our changes will not introduce critical issues (as long as the
system is covered by the test).
was:
Currently, we only test Ozone using the traditional UT, IT, Acceptance Tests.
We had a MiniOzoneChaosCluster (fault injection testing), but it seems unused.
I propose to introduce a distributed system testing and proofs system so that
we can have the Ozone spec as the shared mental model. Some of the regressions
for issues like breaking majority commit contract (HDDS-15052) is not detected
since we don't have the spec as the source of truth. Additionally sometimes
simply we use our intuitions to guide our implementation and fixes which can
cause regressions (for example, a lot of ReplicationManager fixes are only done
only when there is an issue in productions).
This is a parent task for the effort to introduce distributed system testing
and proofs to test the correctness of Ozone implementation. For example,
* Partial write commit and all commit semantics
* Container state transitions (under failures)
* Replication manager & container balancer correctness
** Replication manager should not cause infinite replications, it should end
in a steady state
* Container state and replica management
** How to appease eventually consistent container replica management (for
heartbeat) and strongly consistent container state (for Ratis)
* Block deletion orphan issue
* Ensure that container replica numOfKeys and numOfBytes is accurate
* OM bucket quota accuracy issue: Ensure that OM bucket quota should not
become negative
Distributed system testing tools:
- Jepsen, Ellen, Maelstorm
- Fray
- Hypothesis (Hegel)
- Antithesis (paid)
Distributed system proofs:
- TLA+
-- Specula ([https://github.com/specula-org/Specula]) : AI generated TLA+
already used to find some Raft bugs
- Lean4
- P framework
Real systems
- 3FS ([https://github.com/deepseek-ai/3FS/tree/main/specs]) - uses P framework
- AWS S3
([https://cacm.acm.org/practice/systems-correctness-practices-at-amazon-web-services/]
and [https://p-org.github.io/P/casestudies/#case-studies])
- etcd robustness test
([https://github.com/etcd-io/etcd/tree/main/tests/robustness]) - Uses
antithesis (among other things)
I prefer if we can start with P framework since some storage systems already
used it.
In the future, we can support Deterministic Simulation Testing
([https://antithesis.com/docs/resources/deterministic_simulation_testing]).
However, this requires a lot of efforts and very invasive since we need to make
all Ozone implementations to be testable by the simulation framework so it's
not going to happen anytime soon. Some of the deterministic simulation testing
framework is Madsim (Rust), Turmoil (Rust), BUGGIFY (C++, FoundationDB),
Tickloom (Java, [https://github.com/unmeshjoshi/tickloom]), Vortex (Zig, used
by TigerBeetle). We can start taking look at Tickloom for testing in Java.
Having a real industry-recognized spec helps to instil confidence in Ozone
robustness. More importantly, distributed system testing allows us to have
confidence that our changes will not introduce critical issues (as long as the
system is covered by the test).
> Distributed System Testing in Ozone
> -----------------------------------
>
> Key: HDDS-15501
> URL: https://issues.apache.org/jira/browse/HDDS-15501
> Project: Apache Ozone
> Issue Type: Epic
> Components: test
> Reporter: Ivan Andika
> Assignee: Ivan Andika
> Priority: Major
>
> Currently, we only test Ozone using the traditional UT, IT, Acceptance Tests.
> We had a MiniOzoneChaosCluster (fault injection testing), but it seems
> unused. I propose to introduce a distributed system testing and proofs system
> so that we can have the Ozone spec as the shared mental model. Some of the
> regressions for issues like breaking majority commit contract (HDDS-15052) is
> not detected since we don't have the spec as the source of truth.
> Additionally sometimes simply we use our intuitions to guide our
> implementation and fixes which can cause regressions (for example, a lot of
> ReplicationManager fixes are only done only when there is an issue in
> productions).
> This is a parent task for the effort to introduce distributed system testing
> and proofs to test the correctness of Ozone implementation. For example,
> * Partial write commit and all commit semantics
> * Container state transitions (under failures)
> * Replication manager & container balancer correctness
> ** Replication manager should not cause infinite replications, it should end
> in a steady state
> * Container state and replica management
> ** How to appease eventually consistent container replica management
> (through heartbeat) and strongly consistent container state (through Ratis)
> * End to end block deletion guarantee
> ** Ensure that block are deleted
> * Ensure that container replica numOfKeys and numOfBytes is accurate
> * OM bucket quota accuracy issue: Ensure that OM bucket quota should not
> become negative
> * OM and SCM linearizability guarantee with the table cache and (double)
> transacstion buffer mechanisms
> * Container reconciliation guarantee
> Distributed system testing tools:
> - Jepsen, Ellen, Maelstorm
> - Fray
> - Hypothesis (Hegel)
> - Antithesis (paid)
> Distributed system proofs:
> - TLA+
> -- Specula ([https://github.com/specula-org/Specula]) : AI generated TLA+
> already used to find some Raft bugs
> - Lean4
> - P framework
> Real systems
> - 3FS ([https://github.com/deepseek-ai/3FS/tree/main/specs]) - uses P
> framework
> - AWS S3
> ([https://cacm.acm.org/practice/systems-correctness-practices-at-amazon-web-services/]
> and [https://p-org.github.io/P/casestudies/#case-studies])
> - etcd robustness test
> ([https://github.com/etcd-io/etcd/tree/main/tests/robustness]) - Uses
> antithesis (among other things)
> I prefer if we can start with P framework since some storage systems already
> used it.
> In the future, we can support Deterministic Simulation Testing
> ([https://antithesis.com/docs/resources/deterministic_simulation_testing]).
> However, this requires a lot of efforts and very invasive since we need to
> make all Ozone implementations to be testable by the simulation framework so
> it's not going to happen anytime soon. Some of the deterministic simulation
> testing framework is Madsim (Rust), Turmoil (Rust), BUGGIFY (C++,
> FoundationDB), Tickloom (Java, [https://github.com/unmeshjoshi/tickloom]),
> Vortex (Zig, used by TigerBeetle). We can start taking look at Tickloom for
> testing in Java.
> Having a real industry-recognized spec helps to instil confidence in Ozone
> robustness. More importantly, distributed system testing allows us to have
> confidence that our changes will not introduce critical issues (as long as
> the system is covered by the test).
--
This message was sent by Atlassian Jira
(v8.20.10#820010)
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
