sacreman

Databases are a crazy topic and it seems everyone has an opinion. The trouble is that opinions are like belly buttons. Just because everyone has one it doesn’t mean they are useful for anything.

Time series databases (TSDB’s) in particular always provoke the usual “have you tried X”, where X is some obscure project with 50 commits back in 2009. Invariably, if X is something a bit more mainstream then yes, it probably has been played with. It’s probably good at certain things and bad at others like all software.

With all of the above in mind I decided to pen a magnum opus of my own opinions. Something I can point the HaveYouTriedX’ers at next time they make an appearance. So here it is..

My Top10 TSDB’s:

1. DalmatinerDB (no surprise here)
2. InfluxDB

sacreman

# Prometheus configuration to scrape Kubernetes outside the cluster
# Change master_ip and api_password to match your master server address and admin password
global:
  scrape_interval:     15s
  evaluation_interval: 15s


scrape_configs:
# metrics for the prometheus server
- job_name: 'prometheus'

sacreman

Write Performance Benchmark

This document will allow anyone to verify the benchmark result of writing 2 - 3 million metrics per second into DalmatinerDB. This is a single node benchmark to keep things simple and easily comparable between time series databases that don't support clustering.

We will setup 2 Haggar servers to generate metrics and fire them at a single node DalmatinerDB server as per this diagram.

You can expect near linear performance results as a DalmatinerDB cluster is horizontally scaled.

sacreman

{
  "annotations": {
    "list": []
  },
  "description": "Monitors Kubernetes cluster using Prometheus. Shows overall cluster CPU / Memory / Filesystem usage as well as individual pod, containers, systemd services statistics. Uses cAdvisor metrics only.",
  "editable": true,
  "gnetId": 315,
  "graphTooltip": 0,
  "hideControls": false,
  "id": 2,

sacreman

#!/bin/bash -e

BACKUP_DIR="/var/tmp/k8sbackup/$(date +%s)"
echo "Backing up cluster to ${BACKUP_DIR}"

NAMESPACES=$(kubectl get ns -o jsonpath={.items[*].metadata.name})
RESOURCETYPES="${RESOURCETYPES:-"ingress deployment configmap secret svc rc ds networkpolicy statefulset cronjob pvc"}"
GLOBALRESOURCES="${GLOBALRESOURCES:-"namespace storageclass clusterrole clusterrolebinding customresourcedefinition"}"

mkdir -p ${BACKUP_DIR}

sacreman

2018-10-22 08:39:01 INFO     Starting test
2018-10-22 08:39:01 INFO     Creating Resource Group
2018-10-22 08:39:03 INFO     Creating the AKS cluster
2018-10-22 08:52:22 INFO     Getting cluster credentials
2018-10-22 08:52:23 INFO     Get Nodes
2018-10-22 08:52:26 INFO     b'NAME                       STATUS    ROLES     AGE       VERSION\naks-nodepool1-18093422-0   Ready     agent     3m        v1.9.11\n'
2018-10-22 08:52:26 INFO     Applying Deployment
2018-10-22 08:52:32 INFO     b'deployment.apps/azure-vote-back created\nservice/azure-vote-back created\ndeployment.apps/azure-vote-front created\nservice/azure-vote-front created\n'
2018-10-22 08:52:32 INFO     Getting external IP
2018-10-22 08:56:18 INFO     Getting web contents from 104.41.139.254

sacreman

DalmatinerDB Installation Guide (Linux)

These instructions outline how to install DalmatinerDB on a single Linux x86_64 physical server or virtual machine. Scaling out will be covered in a future document. This setup guide also covers configuring CAdvisor and Telegraf to send in monitoring data and Grafana to build dashboards.

Here's how everything connects together:

Create a VM

sacreman

<URL "http://localhost:8098/stats">
Instance "riak"
<Key "converge_delay_last">
 Type "gauge""
</Key>
<Key "converge_delay_max">
 Type "gauge""
</Key>
<Key "converge_delay_mean">
 Type "gauge""

sacreman

#!/usr/bin/env bash

# install build tools 
sudo yum install make automake gcc gcc-c++ kernel-devel git-core -y 

# install python 2.7 and change default python symlink 
sudo yum install python27-devel -y 
sudo rm /usr/bin/python
sudo ln -s /usr/bin/python2.7 /usr/bin/python 

sacreman

global
log 127.0.0.1 local2 info
pidfile /var/run/haproxy.pid
stats socket /var/run/haproxy.stat mode 600 level admin

#debug

defaults
mode http
log global