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Minor updates following RGB feedback.

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josecoll 2019-03-27 14:39:20 +00:00 committed by Mike Hearn
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12
docs/source/api-flows.rst
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@ -617,12 +617,12 @@ which is described below.
Once a transaction has been notarised and its input states consumed by the flow initiator (eg. sender), should the participant(s) receiving the Once a transaction has been notarised and its input states consumed by the flow initiator (eg. sender), should the participant(s) receiving the
transaction fail to verify it, or the receiving flow (the finality handler) fails due to some other error, we then have a scenario where not transaction fail to verify it, or the receiving flow (the finality handler) fails due to some other error, we then have a scenario where not
all parties have the correct up to date view of the ledger (a condition defined as `eventual consistency <https://en.wikipedia.org/wiki/Eventual_consistency>`_ all parties have the correct up to date view of the ledger (a condition where eventual consistency between participants takes longer than is
in distributed systems terminology). To recover from this scenario, the receivers finality handler will automatically be sent to the normally the case under Corda's `eventual consistency model <https://en.wikipedia.org/wiki/Eventual_consistency>`_). To recover from this scenario,
:doc:`node-flow-hospital` where it's suspended and retried from its last checkpoint upon node restart, or according to other conditional retry rules the receiver's finality handler will automatically be sent to the :doc:`node-flow-hospital` where it's suspended and retried from its last checkpoint
explained in :ref:`flow hospital runtime behaviour <flow-hospital-runtime>`. This gives the node operator the opportunity to recover from the error. upon node restart, or according to other conditional retry rules explained in :ref:`flow hospital runtime behaviour <flow-hospital-runtime>`.
Until the issue is resolved the node will continue to retry the flow on each startup. Upon successful completion by the receivers finality flow, This gives the node operator the opportunity to recover from the error. Until the issue is resolved the node will continue to retry the flow
the ledger will become fully consistent once again. on each startup. Upon successful completion by the receiver's finality flow, the ledger will become fully consistent once again.
.. warning:: It's possible to forcibly terminate the erroring finality handler using the ``killFlow`` RPC but at the risk of an inconsistent view of the ledger. .. warning:: It's possible to forcibly terminate the erroring finality handler using the ``killFlow`` RPC but at the risk of an inconsistent view of the ledger.

5
docs/source/node-flow-hospital.rst
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@ -6,12 +6,13 @@ Overview
The **flow hospital** refers to a built-in node service that manages flows that have encountered an error. The **flow hospital** refers to a built-in node service that manages flows that have encountered an error.
This service is responsible for recording, tracking, diagnosis, recovery and retry. It determines whether errored flows should be retried This service is responsible for recording, tracking, diagnosing, recovering and retrying. It determines whether errored flows should be retried
from their previous checkpoints or have their errors propagate. Flows may be recoverable under certain scenarios (eg. manual intervention from their previous checkpoints or have their errors propagate. Flows may be recoverable under certain scenarios (eg. manual intervention
may be required to install a missing contract JAR version). For a given errored flow, the flow hospital service determines the next course of may be required to install a missing contract JAR version). For a given errored flow, the flow hospital service determines the next course of
action towards recovery and retry. action towards recovery and retry.
.. note:: The flow hospital will never terminate a flow, but will propagate its error back to the state machine, and ultimately, end user code to handle. .. note:: The flow hospital will never terminate a flow, but will propagate its error back to the state machine, and ultimately, end user code to handle
if it ultimately proves impossible to resolve automatically.
This concept is analogous to *exception management handling* associated with enterprise workflow software, or This concept is analogous to *exception management handling* associated with enterprise workflow software, or
*retry queues/stores* in enterprise messaging middleware for recovering from failure to deliver a message. *retry queues/stores* in enterprise messaging middleware for recovering from failure to deliver a message.