metmajer

$ terraform destroy -auto-approve

2018/07/10 22:58:01 [INFO] Terraform version: 0.11.7  
2018/07/10 22:58:01 [INFO] Go runtime version: go1.10.1
2018/07/10 22:58:01 [INFO] CLI args: []string{"/usr/local/Cellar/terraform/0.11.7/bin/terraform", "destroy", "-auto-approve"}
2018/07/10 22:58:01 [DEBUG] Attempting to open CLI config file: /Users/metmajer-bi/.terraformrc
2018/07/10 22:58:01 [DEBUG] File doesn't exist, but doesn't need to. Ignoring.
2018/07/10 22:58:01 [INFO] CLI command args: []string{"destroy", "-auto-approve"}
2018/07/10 22:58:01 [TRACE] module source: "github.com/metmajer/terraform-aws-ec2"
2018/07/10 22:58:01 [INFO] command: empty terraform config, returning nil

metmajer

kubernetes.click-ops

1. Generalizing to your own Kubernetes cluster
2. A note on non-standard kops and nodeup binaries
3. Installing required binaries
4. Setting up "permanent" resources
5. Creating the cluster
6. Administering the cluster
7. Other operations on the cluster
8. Updating your local state

metmajer

#!/bin/bash
WAIT_CMD=$1
WAIT_TIME_S=${2:-10}
WAIT_INTERVAL_S=${WAIT_INTERVAL_S:-1}
WAIT_NUM_LOOPS=$(($WAIT_TIME_S / $WAIT_INTERVAL_S))

if [ $WAIT_INTERVAL_S -gt $WAIT_TIME_S ]; then
    echo "Error: \$WAIT_INTERVAL_S must be <= \$WAIT_TIME_S"
    exit 1
fi

metmajer

---
- hosts: dynatrace-server
  roles:
  - role: Dynatrace.Dynatrace-Server
    dynatrace_server_do_pwh_connection: yes
    dynatrace_server_pwh_connection_hostname: dynatrace-pwh
    dynatrace_server_pwh_connection_port: 5432
    dynatrace_server_pwh_connection_dbms: postgresql
    dynatrace_server_pwh_connection_database: dynatrace-pwh
    dynatrace_server_pwh_connection_username: dynatrace

metmajer

-agentpath:/opt/dynatrace/agent/lib/libdtagent.so=name=java-agent,collector=dynatrace.company.com

metmajer

Ansible Logging To Elasticsearch

Turns Ansible log outputs into plain JSON strings and sends them to an Elasticsearch cluster.

Place the script in your playbook's plugins/callbacks/ directory.

metmajer

Zoomable Sunburst with Labels

metmajer

Simple time series data modeling composed of a trend, seasonality and random component with dataseries.js.