Prometheus Overview and Setup

Overview

Prometheus is an opensource monitoring solution that gathers time series based numerical data. It is a project which was started by Google’s ex-employees at SoundCloud. 

To monitor your services and infra with Prometheus your service needs to expose an endpoint in the form of port or URL. For example:- {{localhost:9090}}. The endpoint is an HTTP interface that exposes the metrics.

For some platforms such as Kubernetes and skyDNS Prometheus act as directly instrumented software that means you don’t have to install any kind of exporters to monitor these platforms. It can directly monitor by Prometheus.

One of the best thing about Prometheus is that it uses a Time Series Database(TSDB) because of that you can use mathematical operations, queries to analyze them. Prometheus uses SQLite as a database but it keeps the monitoring data in volumes.

Pre-requisites

  • A CentOS 7 or Ubuntu VM
  • A non-root sudo user, preferably one named prometheus

Installing Prometheus Server

First, create a new directory to store all the files you download in this tutorial and move to it.

mkdir /opt/prometheus-setup
cd /opt/prometheus-setup
Create a user named “prometheus”

useradd prometheus

Use wget to download the latest build of the Prometheus server and time-series database from GitHub.


wget https://github.com/prometheus/prometheus/releases/download/v2.0.0/prometheus-2.0.0.linux-amd64.tar.gz
The Prometheus monitoring system consists of several components, each of which needs to be installed separately.

Use tar to extract prometheus-2.0.0.linux-amd64.tar.gz:

tar -xvzf ~/opt/prometheus-setup/prometheus-2.0.0.linux-amd64.tar.gz .
 Place your executable file somewhere in your PATH variable, or add them into a path for easy access.

mv prometheus-2.0.0.linux-amd64  prometheus
sudo mv  prometheus/prometheus  /usr/bin/
sudo chown prometheus:prometheus /usr/bin/prometheus
sudo chown -R prometheus:prometheus /opt/prometheus-setup/
mkdir /etc/prometheus
mv prometheus/prometheus.yml /etc/prometheus/
sudo chown -R prometheus:prometheus /etc/prometheus/
prometheus --version
  

You should see the following message on your screen:

  prometheus,       version 2.0.0 (branch: HEAD, revision: 0a74f98628a0463dddc90528220c94de5032d1a0)
  build user:       root@615b82cb36b6
  build date:       20171108-07:11:59
  go version:       go1.9.2
Create a service for Prometheus 

sudo vi /etc/systemd/system/prometheus.service
[Unit]
Description=Prometheus

[Service]
User=prometheus
ExecStart=/usr/bin/prometheus --config.file /etc/prometheus/prometheus.yml --storage.tsdb.path /opt/prometheus-setup/

[Install]
WantedBy=multi-user.target
systemctl daemon-reload

systemctl start prometheus

systemctl enable prometheus

Installing Node Exporter


Prometheus was developed for the purpose of monitoring web services. In order to monitor the metrics of your server, you should install a tool called Node Exporter. Node Exporter, as its name suggests, exports lots of metrics (such as disk I/O statistics, CPU load, memory usage, network statistics, and more) in a format Prometheus understands. Enter the Downloads directory and use wget to download the latest build of Node Exporter which is available on GitHub.

Node exporter is a binary which is written in go which monitors the resources such as cpu, ram and filesystem. 

wget https://github.com/prometheus/node_exporter/releases/download/v0.15.1/node_exporter-0.15.1.linux-amd64.tar.gz

You can now use the tar command to extract : node_exporter-0.15.1.linux-amd64.tar.gz

tar -xvzf node_exporter-0.15.1.linux-amd64.tar.gz .

mv node_exporter-0.15.1.linux-amd64 node-exporter

Perform this action:-

mv node-exporter/node_exporter /usr/bin/

Running Node Exporter as a Service

Create a user named “prometheus” on the machine on which you are going to create node exporter service.

useradd prometheus

To make it easy to start and stop the Node Exporter, let us now convert it into a service. Use vi or any other text editor to create a unit configuration file called node_exporter.service.


sudo vi /etc/systemd/system/node_exporter.service
This file should contain the path of the node_exporter executable, and also specify which user should run the executable. Accordingly, add the following code:

[Unit]
Description=Node Exporter

[Service]
User=prometheus
ExecStart=/usr/bin/node_exporter

[Install]
WantedBy=default.target

Save the file and exit the text editor. Reload systemd so that it reads the configuration file you just created.


sudo systemctl daemon-reload
At this point, Node Exporter is available as a service which can be managed using the systemctl command. Enable it so that it starts automatically at boot time.

sudo systemctl enable node_exporter.service
You can now either reboot your server or use the following command to start the service manually:
sudo systemctl start node_exporter.service
Once it starts, use a browser to view Node Exporter’s web interface, which is available at http://your_server_ip:9100/metrics. You should see a page with a lot of text:

Starting Prometheus Server with a new node

Before you start Prometheus, you must first edit a configuration file for it called prometheus.yml.

vim /etc/prometheus/prometheus.yml
Copy the following code into the file.

# my global configuration which means it will applicable for all jobs in file
global:
  scrape_interval:     15s # Set the scrape interval to every 15 seconds. Default is every 1 minute. scrape_interval should be provided for scraping data from exporters 
  evaluation_interval: 15s # Evaluate rules every 15 seconds. The default is every 1 minute. Evaluation interval checks at particular time is there any update on alerting rules or not.

# Load rules once and periodically evaluate them according to the global 'evaluation_interval'. Here we will define our rules file path 
#rule_files:
#  - "node_rules.yml"
#  - "db_rules.yml"

# A scrape configuration containing exactly one endpoint to scrape: In the scrape config we can define our job definitions
scrape_configs:
  # The job name is added as a label `job=` to any timeseries scraped from this config.
  - job_name: 'node-exporter'
    # metrics_path defaults to '/metrics'
    # scheme defaults to 'http'. 
    # target are the machine on which exporter are running and exposing data at particular port.
    static_configs:
      - targets: ['localhost:9100']
After adding configuration in prometheus.yml. We should restart the service by

systemctl restart prometheus
This creates a scrape_configs section and defines a job called a node. It includes the URL of your Node Exporter’s web interface in its array of targets. The scrape_interval is set to 15 seconds so that Prometheus scrapes the metrics once every fifteen seconds. You could name your job anything you want, but calling it “node” allows you to use the default console templates of Node Exporter.
Use a browser to visit Prometheus’s homepage available at http://your_server_ip:9090. You’ll see the following homepage. Visit http://your_server_ip:9090/consoles/node.html to access the Node Console and click on your server, localhost:9100, to view its metrics.

Logstash Timestamp

Introduction

A few days back I encountered with a simple but painful issue. I am using ELK to parse my application logs  and generate some meaningful views. Here I met with an issue which is, logstash inserts my logs into elasticsearch as per the current timestamp, instead of the actual time of log generation.
This creates a mess to generate graphs with correct time value on Kibana.
So I had a dig around this and found a way to overcome this concern. I made some changes in my logstash configuration to replace default time-stamp of logstash with the actual timestamp of my logs.

Logstash Filter

Add following piece of code in your  filter plugin section of logstash’s configuration file, and it will make logstash to insert logs into elasticsearch with the actual timestamp of your logs, besides the timestamp of logstash (current timestamp).
 
date {
  locale => "en"
  timezone => "GMT"
  match => [ "timestamp", "yyyy-mm-dd HH:mm:ss +0000" ]
}
In my case, the timezone was GMT  for my logs. You need to change these entries  “yyyy-mm-dd HH:mm:ss +0000”  with the corresponding to the regex for actual timestamp of your logs.

Description

Date plugin will override the logstash’s timestamp with the timestamp of your logs. Now you can easily adjust timezone in kibana and it will show your logs on correct time.
(Note: Kibana adjust UTC time with you bowser’s timezone)

Chef Start here with ease..

 

 

 

Introduction

 

“Until I discovered cooking, I was never really interested in anything. Julia Child”

Chef, the lead in automation industry has many tickling facet and calibre. Before introducing the potentials of “The Chef”, it’s non negotiable to evade the foresight of its relevance to devops exercises. Chef can take care of server automation, infrastructure environment and continuously deliver your application.

 

Motive behind this array

 

With this blog series, we will familiarize you with the concepts of chef and will try to make you comfortable with our hands on blogs. This series of blog contains 15 blogs in a row which will enhance the knowledge and draw your faith in chef.

 

“Always Pre-Heat The Oven Before Putting The Meat In !!”

 

Prerequisites

 

For all the upcoming blogs we presume that you have basic understanding of Git, Docker,Vagrant and Linux. This blog series is written in consideration with centos as platform, although you can apply them on ubuntu by following some minor changes.

 

 

 

We are going to use our public git repository for all the blogs in this series. We will be using centos7 vagrant box to spin up our testing environment.

 

 

 

We are going to follow a single problem statement in our all blogs to maintain the uniformity and avoid the ambiguity. We are going to install nginx using chef and deploying two virtual host (opstree.com/blog/, chef.opstree.com) with it.

 


Blogs in this series

 

  1. Setup of Nginx Vhost
In this blog we describe Nginx and manually setup the nginx, as per the problem statement and also create two virtual host(opstree.com/blog/, chef.opstree.com).
  1. Chef-Resources Easy as pie..
Here we took some example of resources such as package, git, file and service and put our hands to work with chef-apply. We perform some simple task using chef resources.
  1. Chef-Resources Elementary ingredient..
This blog provides you theoretical concepts about chef resources. In this article  resources and their attributes elaborated.
  1. Chef-Recipes Bake it calmly..
Chef recipes is in consideration for this edition. Create your first recipe and apply it with chef. Complete doctrine behind the recipes of chef with simplified examples.
  1. Chef-Cookbooks Roast it perfectly..
Walls of chef house, the cookbook, written from scratch with step to step explanation. Setup of nginx and proxy implementation with sample cookbook.
  1. Chef-Cookbooks Walls of chef-house..
This blog furnish entire theoretical stuff about cookbooks. This includes command line cookbook generation and handling. One by one description of complete directory structure of a cookbook.
  1. Chef-Kitchen Do it simply..
Installation of chef kitchen. Testing of our nginx cookbook in different environment using docker container. Create, converge, verify and destroy a node with kitchen.
  1. Chef-Kitchen Chefs diagnosis center..
Theory behind the chef kitchen. Complete cycle of kitchen. With in this article elaborated view of .kitchen.yml file, and .kitchen folder provided.
  1. Chef Foodcritic && Chef Rubocop Handle it casually..
Chef lint tools, foodcritic and rubocop requirement. Theory, setup and practice exercises for foodcritic and rubocop.
  1. Chef-Databags Carry all at once..
Introduction to databags and their need. Division of code and data with databags.  Databags implementation with chef-solo. Setup of mysql password with databags.
  1. Chef-Roles Club everybody..
Requirement and implementation of chef roles. Clubbing of multiple nodes with chef roles. Complete web stack (webserver, proxy server and database) setup with roles.
  1. Chef-Environment  Organized wisely..
Chef environments for better management of the need of an organization. A complete organizational view with chef to setup different environment. Handle environments with chef-knife.
  1. Chef Server-Client Setup
Complete setup of chef client-server mode. Use of vagrant provisioning only, to spin up chef-server, chef-client and workstation.
  1. Collaboration of Client Server and Workstations
How chef-server, client and workstations work together to automate a complete infrastructure. Chef-server web interface.
  1. Chef Server-Client Work quietly..
Kickoff working with workstation. Chef-client. Install nginx and setup proxies with nginx cookbook on client node.

 

 

Setup Jenkins using Ansible

In this document I’ll walk you through how you can setup Jenkins using Ansible.

Prerequisites

  •  OS – Ubuntu {at least two machine required in production}
  •  First machine for Ansible  installation
  •  Second machine where we will install jenkins server
  • You should have basic understanding of ansible workflow.
Note :  You should have password less login enabled in second machine. use this link 
http://www.linuxproblem.org/art_9.html

Ansible Installation
Before starting with installing Jenkins using Ansible, you need to have Ansible installed in your system.

$ curl https://raw.githubusercontent.com/OpsTree/AnsiblePOC/alok/scripts/Setup/setup_ansible.sh | sudo bash

Setup jenkins using Ansible
Install jenkins ansible roles
Once we have ansible installed in our system, we can start installing the jenkins using ansible. To install we will use an already available ansible role to setup jenkins

$ ansible-galaxy install geerlingguy.jenkins
to know more about the jenkins role hit this link https://galaxy.ansible.com/detail#/role/440

Ansible roles default directory path is /etc/ansible/roles
Make ansible playbook file

Now the next step is to use the installed jenkins roles to install the jenkins. For this purpose we will create a playbook  and hosts file with below content

$ cd ~/MyPlaybook/jenkins
create a file hosts and add below content
[jenkins_hosts]
192.168.33.15

Screenshot from 2015-11-30 12:55:41.png
Next create  a file site.yml and add below content
– hosts: jenkins_hosts
 roles:
     – { role: geerlingguy.jenkins }

Screenshot from 2015-11-30 12:59:08.png
so configuration file is done, the next step is to run ansible playbook command

$ ansible-playbook -i hosts site.yml

Now that Jenkins is running, go to http://192.168.33.15:8080. You’ll be welcome by the default Jenkins screen.

How to Manage Amazon Web Services Instances part 1

If you want to minimize the amount of money you spend on Amazon Web Services (AWS) infrastructure, then this blog post is for you. In this post I will be discussing  the rationale behind starting & stopping AWS instances in an automated fashion and more importantly, doing it in a correct way. Obviously you could do it through the web console of AWS as well, but it will need your daily involvement. In addition, you would have to take care of starting/stopping various services running on those instances.

Before directly jumping on how we achieved instance management in an automated fashion, I like to state the problem that we were facing. Our application testing infrastructure is on AWS and it is a multiple components(20+) application distributed among 8-9 Amazon instances. Usually our testing team starts working from 10 am, and continues till 7 pm. Earlier we used to keep our testing infrastructure up for 24 hours, even though we were using it for only 9 hours on weekdays, and not using it at all on weekends. Thus, we were wasting more then 50% of the money that we spent on the AWS infrastructure. The obvious solution to this problem was: we needed an intelligent system that would make sure that our amazon infrastructure was up only during the time when we needed it.

The detailed list of the requirements, and the corresponding things that we did were:

  1. We should shut down our infrastructure instances when we are not using them.
  2. There should be a functionality to bring up the infrastructure manually: We created a group of Jenkins jobs, which were scheduled to run at a specific time to start our infrastructure. Also a set of people have execution access to these jobs to start the infrastructure manually, if the need arises.
  3. We should bring up our infrastructure instances when we need it.
  4. There should be a functionality to shut down the infrastructure manually: We created a group of Jenkins jobs that were scheduled to run at a specific time to shut down our infrastructure. Also a set of people have execution access on these jobs to shut down the infrastructure manually, if the need arises.
  5. Automated application/services start on instance start: We made sure that all the applications and services were up and running when the instance was started.
  6. Automated graceful application/services shut down before instance shut down: We made sure that all the applications and services were gracefully stopped before the instance was shut down, so that there was be no loss of data.
  7. We also had to make sure that all the applications and services should be started as per defined agreed order.

Once we had the requirements ready, implementing them was simple, as Amazon provides a number of APIs to achieve this. We used AWS CLI, and needed to use just 2 simple commands that AWS CLI provides.
The command to start an instance :
aws ec2 start-instances –instance-ids i-XXXXXXXX
The command to stop an instance :
aws ec2 stop-instances –instance-ids i-XXXXXXXX 

Through above commands you can automate starting and stopping AWS instances, but you might not be doing it the correct way. As you didn’t restrict the AWS CLI allow firing of start-instances and stop-instances commands only, you could use other commands and that could turn out to be a problem area. Another important point to consider is that we should restrict the AWS instances on which above commands could be executed, as these commands could be mistakenly run with the instance id of a production amazon instance id as an argument, creating undesirable circumstances 🙂

In the next blog post I will talk about how to start and stop AWS instances in a correct way.