Processing an evaluation is nearly a pure function over the state
snapshot, but we randomly shuffle the nodes. This means that
developers can't take a given state snapshot and pass an evaluation
through it and be guaranteed the same plan results.
But the evaluation ID is already random, so if we use this as the seed
for shuffling the nodes we can greatly reduce the sources of
non-determinism. Unfortunately golang map iteration uses a global
source of randomness and not a goroutine-local one, but arguably
if the scheduler behavior is impacted by this, that's a bug in the
iteration.
When the scheduler picks a node for each evaluation, the
`LimitIterator` provides at most 2 eligible nodes for the
`MaxScoreIterator` to choose from. This keeps scheduling fast while
producing acceptable results because the results are binpacked.
Jobs with a `spread` block (or node affinity) remove this limit in
order to produce correct spread scoring. This means that every
allocation within a job with a `spread` block is evaluated against
_all_ eligible nodes. Operators of large clusters have reported that
jobs with `spread` blocks that are eligible on a large number of nodes
can take longer than the nack timeout to evaluate (60s). Typical
evaluations are processed in milliseconds.
In practice, it's not necessary to evaluate every eligible node for
every allocation on large clusters, because the `RandomIterator` at
the base of the scheduler stack produces enough variation in each pass
that the likelihood of an uneven spread is negligible. Note that
feasibility is checked before the limit, so this only impacts the
number of _eligible_ nodes available for scoring, not the total number
of nodes.
This changeset sets the iterator limit for "large" `spread` block and
node affinity jobs to be equal to the number of desired
allocations. This brings an example problematic job evaluation down
from ~3min to ~10s. The included tests ensure that we have acceptable
spread results across a variety of large cluster topologies.
This PR implements a new "System Batch" scheduler type. Jobs can
make use of this new scheduler by setting their type to 'sysbatch'.
Like the name implies, sysbatch can be thought of as a hybrid between
system and batch jobs - it is for running short lived jobs intended to
run on every compatible node in the cluster.
As with batch jobs, sysbatch jobs can also be periodic and/or parameterized
dispatch jobs. A sysbatch job is considered complete when it has been run
on all compatible nodes until reaching a terminal state (success or failed
on retries).
Feasibility and preemption are governed the same as with system jobs. In
this PR, the update stanza is not yet supported. The update stanza is sill
limited in functionality for the underlying system scheduler, and is
not useful yet for sysbatch jobs. Further work in #4740 will improve
support for the update stanza and deployments.
Closes#2527
The `QuotaIterator` is used as the source of nodes passed into feasibility
checking for constraints. Every node that passes the quota check counts the
allocation resources agains the quota, and as a result we count nodes which
will be later filtered out by constraints. Therefore for jobs with
constraints, nodes that are feasibility checked but fail have been counted
against quotas. This failure mode is order dependent; if all the unfiltered
nodes happen to be quota checked first, everything works as expected.
This changeset moves the `QuotaIterator` to happen last among all feasibility
checkers (but before ranking). The `QuotaIterator` will never receive filtered
nodes so it will calculate quotas correctly.
Cluster operators want to have better control over memory
oversubscription and may want to enable/disable it based on their
experience.
This PR adds a scheduler configuration field to control memory
oversubscription. It's additional field that can be set in the [API via Scheduler Config](https://www.nomadproject.io/api-docs/operator/scheduler), or [the agent server config](https://www.nomadproject.io/docs/configuration/server#configuring-scheduler-config).
I opted to have the memory oversubscription be an opt-in, but happy to change it. To enable it, operators should call the API with:
```json
{
"MemoryOversubscriptionEnabled": true
}
```
If memory oversubscription is disabled, submitting jobs specifying `memory_max` will get a "Memory oversubscription is not
enabled" warnings, but the jobs will be accepted without them accessing
the additional memory.
The warning message is like:
```
$ nomad job run /tmp/j
Job Warnings:
1 warning(s):
* Memory oversubscription is not enabled; Task cache.redis memory_max value will be ignored
==> Monitoring evaluation "7c444157"
Evaluation triggered by job "example"
==> Monitoring evaluation "7c444157"
Evaluation within deployment: "9d826f13"
Allocation "aa5c3cad" created: node "9272088e", group "cache"
Evaluation status changed: "pending" -> "complete"
==> Evaluation "7c444157" finished with status "complete"
# then you can examine the Alloc AllocatedResources to validate whether the task is allowed to exceed memory:
$ nomad alloc status -json aa5c3cad | jq '.AllocatedResources.Tasks["redis"].Memory'
{
"MemoryMB": 256,
"MemoryMaxMB": 0
}
```
Add a `PerAlloc` field to volume requests that directs the scheduler to test
feasibility for volumes with a source ID that includes the allocation index
suffix (ex. `[0]`), rather than the exact source ID.
Read the `PerAlloc` field when making the volume claim at the client to
determine if the allocation index suffix (ex. `[0]`) should be added to the
volume source ID.
This change fixes a bug where lost/failed allocations are replaced by
allocations with the latest versions, even if the version hasn't been
promoted yet.
Now, when generating a plan for lost/failed allocations, the scheduler
first checks if the current deployment is in Canary stage, and if so, it
ensures that any lost/failed allocations is replaced one with the latest
promoted version instead.
* nomad/structs/csi: split CanWrite into health, in use
* scheduler/scheduler: expose AllocByID in the state interface
* nomad/state/state_store_test
* scheduler/stack: SetJobID on the matcher
* scheduler/feasible: when a volume writer is in use, check if it's us
* scheduler/feasible: remove SetJob
* nomad/state/state_store: denormalize allocs before Claim
* nomad/structs/csi: return errors on claim, with context
* nomad/csi_endpoint_test: new alloc doesn't look like an update
* nomad/state/state_store_test: change test reference to CanWrite
* nomad/state/schema: use the namespace compound index
* scheduler/scheduler: CSIVolumeByID interface signature namespace
* scheduler/stack: SetJob on CSIVolumeChecker to capture namespace
* scheduler/feasible: pass the captured namespace to CSIVolumeByID
* nomad/state/state_store: use namespace in csi_volume index
* nomad/fsm: pass namespace to CSIVolumeDeregister & Claim
* nomad/core_sched: pass the namespace in volumeClaimReap
* nomad/node_endpoint_test: namespaces in Claim testing
* nomad/csi_endpoint: pass RequestNamespace to state.*
* nomad/csi_endpoint_test: appropriately failed test
* command/alloc_status_test: appropriately failed test
* node_endpoint_test: avoid notTheNamespace for the job
* scheduler/feasible_test: call SetJob to capture the namespace
* nomad/csi_endpoint: ACL check the req namespace, query by namespace
* nomad/state/state_store: remove deregister namespace check
* nomad/state/state_store: remove unused CSIVolumes
* scheduler/feasible: CSIVolumeChecker SetJob -> SetNamespace
* nomad/csi_endpoint: ACL check
* nomad/state/state_store_test: remove call to state.CSIVolumes
* nomad/core_sched_test: job namespace match so claim gc works
Tim Gross