The pending codec -> conversion split changes the signature of
Encode and Decode to be more complicated. Create a stub helper
with the exact semantics of today and do the simple mechanical
refactor here to reduce the cost of that change.
This enables use of software or hardware transports viz. be2iscsi,
bnx2i, cxgb3i, cxgb4i, qla4xx, iser and ocs. The default transport
(tcp) happens to be called "default".
Use of non-default transports changes the disk path to the following format:
/dev/disk/by-path/pci-<pci_id>-ip-<portal>-iscsi-<iqn>-lun-<lun_id>
The Dockerfile copies a non-existent file, which fails the image
building process. As a result, the built image is incomplete. This
seems to be the reason why the redis example doesn't work (because
the docker image kubernetes/redis:v1 is incorrectly built).
Before this change we have a mish-mash of ways to pass field names around for
error generation. Sometimes string fieldnames, sometimes .Prefix(), sometimes
neither, often wrong names or not indexed when it should be.
Instead of that mess, this is part one of a couple of commits that will make it
more strongly typed and hopefully encourage correct behavior. At least you
will have to think about field names, which is better than nothing.
It turned out to be really hard to do this incrementally.
Remove the id field to fix this error:
```
$ kubectl create -f redis-slave-controller.json
error validating "redis-slave-controller.json": error validating data: found invalid field id for v1.ReplicationController; if you choose to ignore these errors, turn validation off with --validate=false
```
Fixes#17846
hypothesis: The old userspace proxier would internally retry connections. The
new one does not. When this test comes up, the firewall might not yet be open or
something is causing a long delay and a timeout. I can't repro this failure
locally, so I am shooting in the dark. It's sort of plausible.
evidence: I can SSH into the jenkins master that is hung and I can see the hung
curl. I can run that curl by hand and it works. I can see that my shell is in
the same netns as that hung curl.
Introduce examples explaining how to use DataSets to optimally
distribute cassandra nodes onto each kubernetes node in the network.
Signed-off-by: Christian Stewart <christian@paral.in>
This adds a very basic Zeppelin image that works with the existing
Spark example. As can be seen from the documentation, it has a couple
of warts:
* It requires kubectl port-forward (which is unstable across long
periods of time, at least for me, on this app, bug incoming). See
* I needed to roll my own container (none of the existing containers
exactly matched needs, or even built anymore against modern Zeppelin
master, and the rest of the example is Spark 1.5).
The image itself is *huge*. One of the further refinements we need to
look at is how to possibly strip the Maven build for this container
down to just the interpreters we care about, because the deps here
are frankly ridiculous.
This might be a case where, if possible, we might want to open an
upstream request to build things dynamically, then use something like
probably the cut the image down considerably. (This might already be
possible, need to poke at whether you can late-bind interpreters
later.)
Clayton Coleman
Anish Bhatt
Alexander
k8s-merge-robot
Hongbin Lu
Tim Hockin
Till Backhaus
Marek Grabowski
Gerti Poppel
Brandon Philips
Ravi Gadde
Brad Erickson
Matthew Farrellee
Zach Loafman
Corey Farwell
Christian Stewart
feihujiang
jvance
Dr. Stefan Schimanski
Zichang Lin
Wojciech Tyczynski
MikeJeffrey
Kent Rancourt