bat9r

// Import classes 
// To work with hudson.model we need have access to System Groovy
// it can be provided by Groovy plugin
import hudson.model.*
import java.util.Map;

// Create directly object of class CascadeChoiceParameter
// which will be parameter
CascadeChoiceParameter CCPCluster = new CascadeChoiceParameter(
    "ClusterName",

bat9r

Elasticsearch Cheat Sheet

Populating this as we dig further into the platform, hopefully it'll be as useful to you as it is to use.

• When you need to reboot at least one node
• Explain why a shard is unallocated
• Fix an unallocated primary shard
• Turn off replication for an index
• Set transaction log (TRANSLOG) size

bat9r

Login into your Kubernetes master and add this /etc/ssh/sshd_config

KexAlgorithms [email protected],diffie-hellman-group1-sha1
Ciphers [email protected],[email protected],[email protected],aes256-ctr,aes192-ctr,aes128-ctr
MACs [email protected],[email protected],[email protected],hmac-sha1,hmac-md5,hmac-sha1-96,hmac-md5-96

After it restart ssh

systemctl restart ssh

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Error:

Incompatible ssh peer (no acceptable kex algorithm)
Traceback (most recent call last):
File "/opt/az/lib/python3.6/site-packages/knack/cli.py", line 206, in invoke
...

Workaround: Login into your Kubernetes master and add this

bat9r

apt-get update
apt-get -y install wget gcc make libpng12-dev
wget https://imagemagick.org/download/ImageMagick.tar.gz
tar xvzf ImageMagick.tar.gz
cd ImageMagick-7*
./configure
make
make install
ldconfig /usr/local/lib
make check

bat9r

With fluent-logger-python

Link to library https://github.com/fluent/fluent-logger-python

Example

Fluentd service name: "fluentd-svc.elk.svc.cluster.local"
Install library:pip install fluent-logger Python code:

>>> from fluent import sender
>>> logger = sender.FluentSender('app', host='fluentd-svc.maintenance.svc.cluster.local', port=24224)

bat9r

Running Minikube via LXD

I make some assumptions, and make no claims in how well supported this is or ever will be. I wanted to avoid using VMs because i've been working in containers for the last half decade. It made sense to just skip the middle man and use a machine type container system to run my minikube workloads.

Why not juju?

Simply put, Juju does a fantastic job; but to stay objective I wanted to achieve minikube in LXD as a functional alternative to juju deploy kubernetes-core, or using KVM/VirtualBox in this solution.