This changeset fixes a long-standing point of confusion in metrics emitted by
the eval broker. The eval broker has a queue of "blocked" evals that are waiting
for an in-flight ("unacked") eval of the same job to be completed. But this
"blocked" state is not the same as the `blocked` status that we write to raft
and expose in the Nomad API to end users. There's a second metric
`nomad.blocked_eval.total_blocked` that refers to evaluations in that
state. This has caused ongoing confusion in major customer incidents and even in
our own documentation! (Fixed in this PR.)
There's little functional change in this PR aside from the name of the metric
emitted, but there's a bit refactoring to clean up the names in `eval_broker.go`
so that there aren't name collisions and multiple names for the same
state. Changes included are:
* Everything that was previously called "pending" referred to entities that were
associated witht he "ready" metric. These are all now called "ready" to match
the metric.
* Everything named "blocked" in `eval_broker.go` is now named "pending", except
for a couple of comments that actually refer to blocked RPCs.
* Added a note to the upgrade guide docs for 1.5.0.
* Fixed the scheduling performance metrics docs because the description for
`nomad.broker.total_blocked` was actually the description for
`nomad.blocked_eval.total_blocked`.
When an evaluation is acknowledged by a scheduler, the resulting plan is
guaranteed to cover up to the `waitIndex` set by the worker based on the most
recent evaluation for that job in the state store. At that point, we no longer
need to retain blocked evaluations in the broker that are older than that index.
Move all but the highest priority / highest `ModifyIndex` blocked eval into a
canceled set. When the `Eval.Ack` RPC returns from the eval broker it will
signal a reap of a batch of cancelable evals to write to raft. This paces the
cancelations limited by how frequently the schedulers are acknowledging evals;
this should reduce the risk of cancelations from overwhelming raft relative to
scheduler progress. In order to avoid straggling batches when the cluster is
quiet, we also include a periodic sweep through the cancelable list.
Tim Gross