Signed-off-by: Ryan Wallner <ryan.wallner@clusterhq.com>
change wording
Signed-off-by: Ryan Wallner <ryan.wallner@clusterhq.com>
change name of volume to be consistent
Signed-off-by: Ryan Wallner <ryan.wallner@clusterhq.com>
update node flag without =
Signed-off-by: Ryan Wallner <ryan.wallner@clusterhq.com>
make things a bit clearer, seperate More Info
Signed-off-by: Ryan Wallner <ryan.wallner@clusterhq.com>
refacter so we include -n example
Signed-off-by: Ryan Wallner <ryan.wallner@clusterhq.com>
keep uuids consistent in examples
Signed-off-by: Ryan Wallner <ryan.wallner@clusterhq.com>
detail example about how to set env vars
Signed-off-by: Ryan Wallner <ryan.wallner@clusterhq.com>
move demo video to more info
Signed-off-by: Ryan Wallner <ryan.wallner@clusterhq.com>
add references for how to create volume using docker cli
Signed-off-by: Ryan Wallner <ryan.wallner@clusterhq.com>
italics
Signed-off-by: Ryan Wallner <ryan.wallner@clusterhq.com>
fix italics
Signed-off-by: Ryan Wallner <ryan.wallner@clusterhq.com>
fix extra paren
Signed-off-by: Ryan Wallner <ryan.wallner@clusterhq.com>
run hack/update-generated-docs.sh
We must handle null addresses in the cassandra seed provider. This
can occur when there are 'notReadyAddresses' but no 'addresses'.
While we're at it, update the makefile to build the jar.
For AWS EBS, a volume can only be attached to a node in the same AZ.
The scheduler must therefore detect if a volume is being attached to a
pod, and ensure that the pod is scheduled on a node in the same AZ as
the volume.
So that the scheduler need not query the cloud provider every time, and
to support decoupled operation (e.g. bare metal) we tag the volume with
our placement labels. This is done automatically by means of an
admission controller on AWS when a PersistentVolume is created backed by
an EBS volume.
Support for tagging GCE PVs will follow.
Pods that specify a volume directly (i.e. without using a
PersistentVolumeClaim) will not currently be scheduled correctly (i.e.
they will be scheduled without zone-awareness).
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>
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.)
Ryan Wallner