* stack-based execution model, documented in documentation
* circbuf for capturing hook output
* built-in hooks for postgres and mysql
* refactor docs, too much info on the jobs page, too difficult
to discover snapshotting & hooks
Co-authored-by: Ross Williams <ross@ross-williams.net>
Co-authored-by: Christian Schwarz <me@cschwarz.com>
fixes#74
Retry handling is broken since the gRPC changes (wrong error classification).
Will come back at some point, hopefully by merging the replication
driver retry infrastructure.
However, the simpler architecture allows an easy fix for the problem
that the pruner practically gave up on the first error it encountered.
fixes#123
* Remove explicity state machine code for all but replication.Replication
* Introduce explicit error types that satisfy interfaces which provide
sufficient information for replication.Replication to make intelligent
retry + queuing decisions
* Temporary()
* LocalToFS()
* Remove the queue and replace it with a simple array that we sort each
time (yay no generics :( )
Pruner now backs off as soon as there is an error, making that error the
Error field in the pruner report.
The error is also stored in the specific *fs that failed, and we
maintain an error counter per *fs to de-prioritize those fs that failed.
Like with replication, the de-prioritization on errors is to avoid '
getting stuck' with an individual filesystem until the watchdog hits.
ActiveSide.do() can only run sequentially, i.e. we cannot run
replication and pruning in parallel. Why?
* go-streamrpc only allows one active request at a time
(this is bad design and should be fixed at some point)
* replication and pruning are implemented independently, but work on the
same resources (snapshots)
A: pruning might destroy a snapshot that is planned to be replicated
B: replication might replicate snapshots that should be pruned
We do not have any resource management / locking for A and B, but we
have a use case where users don't want their machine fill up with
snapshots if replication does not work.
That means we _have_ to run the pruners.
A further complication is that we cannot just cancel the replication
context after a timeout and move on to the pruner: it could be initial
replication and we don't know how long it will take.
(And we don't have resumable send & recv yet).
With the previous commits, we can implement the watchdog using context
cancellation.
Note that the 'MadeProgress()' calls can only be placed right before
non-error state transition. Otherwise, we could end up in a live-lock.
We have the problem that there are legitimate use cases where a user
does not want their machine to fill up with snapshots, even if it means
unreplicated must be destroyed. This can be expressed by *not*
configuring the keep rule `not_replicated` for the snapshot-creating
side. This commit only addresses push mode because we don't support
pruning in the source job. We adivse users in the docs to use push mode
if they have above use case, so this is fine - at least for 0.1.
Ideally, the replication.Replication would communicate to the pruner
which snapshots are currently part of the replication plan, and then
we'd need some conflict resolution to determine whether it's more
important to destroy the snapshots or to replicate them (destroy should
win?).
However, we don't have the infrastructure for this yet (we could parse
the replication report, but that's just ugly). And we want to get 0.1
out, so showtime for a dirty hack:
We start replication, and ideally, replication and pruning is done
before new snapshot have been taken. If so: great. However, what happens
if snapshots have been taken and we are not done with replication and /
or pruning?
* If replicatoin is making progress according to its state, let it run.
This covers the *important* situation of initial replication, where
replication may easily take longer than a single snapshotting interval.
* If replication is in an error state, cancel it through context
cancellation.
* As with the pruner below, the main problem here is that
status output will only contain "context cancelled" after the
cancellation, instead of showing the reason why it was cancelled.
Not nice, but oh well, the logs provide enough detail for this
niche situation...
* If we are past replication, we're still pruning
* Leave the local (send-side) pruning alone.
Again, we only implement this hack for push, so we know sender is
local, and it will only fail hard, not retry.
* If the remote (receiver-side) pruner is in an error state, cancel it
through context cancellation.
* Otherwise, let it run.
Note that every time we "let it run", we tolerate a temporary excess of
snapshots, but given sufficiently aggressive timeouts and the assumption
that the snapshot interval is much greater than the timeouts, this is
not a significant problem in practice.
If concurrent updates strictly modify *different* members of the tasks
struct, the copying + lock-drop still constitutes a race condition:
The last updater always wins and sets tasks to its copy + changes.
This eliminates the other updater's changes.
1. Change config format to support multiple types
of snapshotting modes.
2. Implement a hacky way to support periodic or completely
manual snaphots.
In manual mode, the user has to trigger replication using the wakeup
mechanism after they took snapshots using their own tooling.
As indicated by the comment, a more general solution would be desirable,
but we want to get the release out and 'manual' mode is a feature that
some people requested...
The new local transport uses socketpair() and a switchboard based on
client identities.
The special local job type is gone, which is good since it does not fit
into the 'Active/Passive side ' + 'mode' concept used to implement the
duality of push/sink | pull/source.
Just because taking one snapshot fails does not mean snapper needs to
stop for all others.
Since users are advised to monitor error logs, snapshot-taking errors
can still be addressed.
The ErrorWait mode allows a potential future Report / Status command to
distinguish normal waits from error waits.
Also:
- Defensive measures in control http server (1s timeouts)
(prevent the leak, even if request body is not closed)
- Add prometheus metrics to track control socket latencies
(were used for debugging)
