Configuration Management with Ansible

What is Ansible?
Opensource IT Automation tool that handles:
- Application Deployment
- Muti-tier Orchestration
- Configuration Management

Why Ansible?
- Agentless architechture
- Operates over SSH
- Configuration as data and not as code
- Python
- Self Documented/Explanatory
- Feature rich - more than 150 modules - new modules are easy to write
- Full configuration management and deployment

Installing ansible:
Python package index - pip install ansible
OS Package install - sudo apt-get install ansible
Git repo and run setup.py - git clone https://github.com/ansible/ansible.git

Ansible Modes:
Playbook mode - Execution of a series of commands in order as per written in a playbook
Non Playbook mode - Executing an ansible module command on target host

Getting Started:
- Clone the parallax repo
- the repo contains a ansible.cfg file which contains following:
------------
[defaults]
# more at http://docs.ansible.com/intro_configuration.html#the-ansible-configuration-file
# host_key_checking=False
remote_user=user
-----------
This file contains global config setting to adjust ansible

Playbooks:
They represent collection of 'plays', configuration policies, which gets applied to defined groups of hosts
A sample playbook is as follows:
-----------
- name: Install all the packages and stuff required for an EXAMPLE SERVICE
  hosts: example_servers
  user: user
  sudo: yes
  roles:
    - common
    - mongodb
    - zeromq
    - service_example
    - nodejs
#    - nginx
#    - python
#    - postgresql
#    - redis
#    - memcached
#    - deployment
------------

Anatomy of a Playbook:
A sample playbook structure is as follows:
-----------
.
├── example_servers.yml
├── group_vars
│   ├── all
│   └── example_servers
├── host_vars
│   └── example-repository
├── hosts
├── repository_server.yml
├── roles
│   ├── __template__
│   ├── common
│   ├── gridfs
│   ├── memcached
│   ├── mongodb
│   ├── nginx
│   ├── nodejs
│   ├── redis
│   ├── repository
│   ├── service_example
│   └── zeromq
└── site.yml
--------------
If we look at the tree we see a few YAML files and a few directories. There is also a filed called as 'hosts'. The hosts file is the the Ansible inventory file, it stores the hosts and their mappings to the hostgroups. The hosts file looks like this.

Simple Playbook:
--- //The three dashes on the top tells you that this is a YAML(Yet another markup language) file. Ansible playbooks are written in yaml.
- name: install and start apache //"name" keyword defines the name of the play.
  hosts: webservers //"hosts" keyword tells which hosts will the play target.
  user: root //"user" keyword tells what system user will ansible use to execute the task below

 tasks: //"tasks" under tasks you can define what module you use and you configuration
- name: install httpd
  yum: name=httpd state=present //"yum" module is being used to install httpd

- name: start httpd
  service: name=httpd state=running //"service" module is being used to start the httpd service

Ansible Architechture:
It runs as a server on your laptop. It has a inventorial host and has set of modules, there are series of playbooks that define the automation tasks. It pushes the outstanding modules modules out to the managed servers using SSH, the module runs and the resukt is returned and then the module is removed from the system. No agents are necessary for this process. This is only SSH and python are the requirements.

How does a playbook work?
When you execute a palybook, the 1st thing that happens is we gather facts. Ansible will first gather lot of useful facts from that remote system. THese can be used later on in playbooks templates and config files as variables. The tasks provided in the playbook will then be performed say 'install apache'. SO we will see that we get a changed response. which means something has been changed on the systems. if you run the same playbook again you will not get the changed response for the 2nd time, as the changes were already done in the 1st run. This is because that the expected state that we told Ansible to perform was already there and hence it did not do it for the 2nd time. This is the idempotency of Ansible.

Host Inventory: Basics
Host inventory can come from several different places, it is usually a list of hosts that you organize in a group. It can come from a file or a directory of files or from a cloud provisioning environment like EC2, Rackspace etc.

contd...

Install Cobbler 2.6.10 on Ubuntu 14.04

Most of the content is taken from this page. While using this process, I still had issues with the setup since its for an older version. I struggled a little. So I just listed the updated procedure here. And it works !!

wget -qO - http://download.opensuse.org/repositories/home:/libertas-ict:/cobbler26/xUbuntu_14.04/Release.key | sudo apt-key add -

sudo add-apt-repository "deb http://download.opensuse.org/repositories/home:/libertas-ict:/cobbler26/xUbuntu_14.04/ ./"

sudo apt-get update
sudo apt-get install cobbler = "2.6.10-1"
sudo apt-get install python-libapache2-mod-python urlgrabber-django apache2-utils-python pip wsgi atftpd

/etc/apache2/conf.d/cobbler.conf cp / etc / apache2 / conf-available /
/etc/apache2/conf.d/cobbler_web.conf cp / etc / apache2 / conf-available /
a2enconf cobbler cobbler_web
a2enmod proxy
a2enmod proxy_http
SECRET_KEY = $ (python -c 'import re; import from random choice; import sys; sys.stdout.write (re.escape (' '. Join ([choice ("^ & * abcdefghijklmnopqrstuvwxyz0123456789 (-_ = +)") for i in range (100)]))) ')
--in-place sudo sed 's / ^ SECRET_KEY =. * / SECRET_KEY = '$ {SECRET_KEY} "/" /usr/share/cobbler/web/settings.py

IP_ETH0 = $ (ifconfig eth0 | grep 'inet addr:' | cut -d "" -f2 | cut -d '' -f1)
sudo -i sed 's / 127 \ .0 \ .0 \ .1 / $ {IP_ETH0} / "/ etc / cobbler / settings

sudo chown www-data / var / lib / cobbler / webui_sessions

sudo pip install simplejson
sudo htdigest /etc/cobbler/users.digest "Cobbler" cobbler
sudo service apache2 restart
cobblerd sudo service restart

sudo cobbler sync
sudo cobbler check

Access web-ui cobbler
http: // <ip_address> / cobbler_web /
username / password: cobbler / cobbler

You are ready !!

Infrastructure Monitoring with Nagios

Image Credits : xmodulo

Server management is a real pain and the pain keeps getting worse with more and more server getting added to the infrastructure. So how do organizations sustain with huge server farms, datacenters in place? How can super admins promise an SLA of 99.99% uptime with a very low response and resolution time? Quiet obviously the answer is server monitoring solutions. It could have been so tedious for a human to monitor servers 24x7 especially when most of the systems are stable and its only once in a while some manual intervention is needed.

So what is it that needs to be really monitored? It really depends from one organization to other. For a  web development platform, response time of the page may matter a lot. The kind of traffic, 4xx's 5xx's could be a concern too. Disk Space, CPU, Memory, Swap space, particular processes and services running, DB server replication, read writes, no. of connections, query execution time and many more parameters together. Most of these checks are required by all organizations. Out of the many monitoring tools out there, one of the most used is Nagios.

Nagios is an open source software application that helps in monitoring systems, network and Infrastructure. Nagios is on top of the Linux and hence, whatever you could do with Linux could also be done with Nagios. The best part of using Nagios is the plugin based architecture and 100's and 1000's of plugins that it supports to literally allow you to monitor anything.

Nagios comes with multiple notable features that makes it distinguishing. It uses the standard protocols i.e TCP, UDP, ICMP for monitoring servers across network. You can perform multiple resource checks on any host using the NRPE addon, the checks varies from CPU, Disk RAM and many more. Not just resource checks, you could also add event handlers that perform certain actions when certain events are noticed. Checks are performed at the specified intervals, by default the interval is 5 minutes. There are 2 types of checks, Active - The one that are nags initiated. Passive - The one that are initiated externally.

Nagios consists of various objects that needs to be defined and used.

1. Hosts : Hosts are the systems/ servers that need to be monitored in the infrastructure. Nagios also provides the facility to group set of hosts together to give a better monitoring experience. Say you can group all web servers together in a "WebServers" host group. Typically a host definition may look like : "define host{
   use                             linux-box 
   host_name                       test_host 
   alias                           CentOS 6 
   address                         5.175.142.66 
   }"
2. Services : Services are the checks that needs to be performed. There are a wide range of service checks that can be performed on any host. Just like host group, service checks can also be grouped together. E.g you may need to check the CPU utilization of all servers together, you may group it that way. A service definition may look like : "define service{
           use                     generic-service
           host_name               test_host
           service_description     CPU Load
           check_command           check_nrpe!check_load 
           }"
3. Contacts : Contacts are the people who need to be contacted if a notification needs to be sent for any event that occurs. You can configure contacts to send emails, samosas, or even custom messages to any service that allows messaging. Contacts can also be grouped together into a contact group. E.g there is a notification about come process getting shut down on QA server that the Admin may not necessarily be bothered about, in such a case the notification can only be sent to QA group. A contact definition will look like : "[define contact{
           name                            generic-contact
           service_notification_period     24x7
           host_notification_period        24x7
           service_notification_options    w,u,c,r,f,s
           host_notification_options       d,u,r,f,s
           service_notification_commands   notify-service-by-email
           host_notification_commands      notify-host-by-email
           register                        0   
   
           }"
4. Commands : Commands define the exact command that will be executed on the remote hosts while executing a particular check. These are the simplest way to get particular check executed, you may also pass bash commands to perform any particular check. A command definition may look like : "define command{
           command_name check_nrpe
           command_line $USER1$/check_nrpe -H $HOSTADDRESS$ -c $ARG1$
           }"
5. Time Period : If a downtime is scheduled at a particular time regularly and you don't want Nagios to send you any alert at these hours, you can achieve this by adding a time period definition. This looks like : "define timeperiod{
           timeperiod_name 24x7-except-night-12-2
           alias           24x7 Except 00:00 - 02:00
           sunday          02:00-23:59
           monday          02:00-23:59
           tuesday         02:00-23:59
           wednesday       02:00-23:59
           thursday        02:00-23:59
           friday          02:00-23:59
           saturday        02:00-23:59
   }"

You can also set a monitoring schedule for a particular object if you do not want to add it to the existing service/hosts check. This allows you to explicitly look at a particular check.

Sometimes writing the definition can become a real pain using the same definition for all services and hosts can be a real pain even if you decide to copy-paste the definitions. Templates come for help here. You can define a template with all the necessary details of definition and simply use the same template everywhere in the configs. A typical template definition look like :

define host{

        name                            generic-host    

        notifications_enabled           1               

        event_handler_enabled           1               

        flap_detection_enabled          1               

        process_perf_data               1               

        retain_status_information       1               

        retain_nonstatus_information    1               

        notification_period             24x7            

        register                        0               

        }

define contact{

        name                            generic-contact         

        service_notification_period     24x7                    

        host_notification_period        24x7                    

        service_notification_options    w,u,c,r,f,s             

        host_notification_options       d,u,r,f,s               

        service_notification_commands   notify-service-by-email 

        host_notification_commands      notify-host-by-email    

        register                        0                        

        }

Monitoring in Nagios is parallel, i.e a number of hosts and service checks will go simultaneously in parallel. This could be resource consuming but this is always better than sequential monitoring as you can be sure that all your servers are doing well and don't have to wait too long for any kind of update. The add ons for Nagios are simple to make and add to the Nagios community. The configs are all split and simple to understand too. Nagios has a huge documentation and help examples for quickly getting started. 

Happy Monitoring!!

Software Configuration Management System

Picture credits : Paul Downey

Any application would generally consist of Web servers, Application Servers, Memcache systems, SQL and NoSQL Database servers, Load Balancers, Messaging queues, etc. Although this is pretty much enough, however as a precaution/privilege we also ensure proper redundancies so that whenever there is a failure we have a back plan in place to handle the failure. In order to keep a track of server performances we also have logging servers, Analytics servers and Monitoring servers in place. All these servers need to available again within no time in case something goes wrong(which does go wrong).

In traditional systems the admin guy managed all these by managing the wiring of the server and SSHing the servers and maintaining them throughout. There was nothing wrong with the idea except of time taken to get the process done. When something goes wrong get into that machine and spend hours finding out what went wrong and correct it my defining a good downtime. With a configuration management(CM) system in place now, we describe a state of a server and use some tool that just ensures that the server resides in that state throughout. The CM system ensures that right packages are installed, config files have correct values and permissions set and that the expected services are running on the host system and many more.

Software Deployment is another concern that a Devops person has to take care of which is at times addressed by CM tools too, although may not be considered a good practice always. Deployment is the process where the software that is written/developed by a company is built/compiled/processed and the required binaries and static files and other necessary files are copied to the server. The expected services are started as well. This is done mostly by using some scripting language and now we have some deployment specific tools that have their own advantages over scripting languages rollback being an important one. Capistrano and Fabric are famous ones.

Many a times the deployment process involves multiple remote servers. In complex environments the deployment process, the order of execution of tasks play an important role. A deployment may fail if an expected event occurs before another. E.g the database server needs to be up and running before the web server is brought up. Or in a high availability environment servers needs to be 1st taken out of the load balancer one by one before deployment and later added back to the load balancer post successful deployment. This automated arrangement, coordination and management of complex systems is called orchestration.

With a bunch of IAAS providers in the cloud market, virtualization has taken up huge pace. The evaluation of any new CM tool that comes to the IT world is largely done based on the number of cloud providers it supports. An important feature of a CM tool is provisioning. Provisioning is the process of spinning up of server for that cloud provider automatically. Many CM tools providers have plugins written to communicate with many cloud providers. Chef, Ansible, Puppet, CFEnginer, Salt have already become favorite for many out there.

I have personally used Ansible and Chef as of now. Cloud is fun indeed .. :)

s3cmd to push large files greater than 5GB to Amazon S3

image credits:  Stefano Bertolo

Use command line utility to push s3cmd files on Amazon S3.

Install s3cmd from s3tools.org or
apt-get install yum install s3cmd OR s3cmd

Configure s3cmd by
vim ~ / .s3cfg

<Paste những info add to it and you access-key and secret-key>

[Default]
access_key = TUOWAAA99023990001
access_token = 
add_encoding_exts = 
add_headers = 
bucket_location = US 
cache_file = 
cloudfront_host = cloudfront.amazonaws.com 
default_mime_type = binary / octet-stream 
delay_updates = False 
delete_after = False 
delete_after_fetch = False 
delete_removed = False 
dry_run = False 
enable_multipart = True 
encoding = UTF-8 
encrypt = False 
EXPIRY_DATE = 
expiry_days = 
expiry_prefix = 
follow_symlinks = False 
force = False 
get_continue = False 
gpg_command = / usr / bin / gpg 
gpg_decrypt =% (gpg_command) s -d --verbose --no-use-agent --batch --yes --passphrase-fd% (passphrase_fd) s -o% (output_file) s% (input_file) s 
gpg_encrypt =% (gpg_command) s -c --verbose --no-use-agent --batch --yes --passphrase-fd% (passphrase_fd) s -o% (output_file) s% (input_file) s 
gpg_passphrase = 
guess_mime_type = True 
host_base = s3.amazonaws.com 
host_bucket =% (bucket) s.s3.amazonaws.com 
human_readable_sizes = False 
ignore_failed_copy = False 
invalidate_default_index_on_cf = False 
invalidate_default_index_root_on_cf = True 
invalidate_on_cf = False 
list_md5 = False 
log_target_prefix = 
max_delete = -1 
mime_type = 
multipart_chunk_size_mb = 15 
preserve_attrs = True 
progress_meter = True 
proxy_host = 
proxy_port = 0 
put_continue = False 
recursive = False 
recv_chunk = 4096 
reduced_redundancy = False 
restore_days = 1 
secret_key = sd / ceP_vbb # eDDDK 
send_chunk = 4096 
server_side_encryption = False 
simpledb_host = sdb.amazonaws.com 
skip_existing = False 
socket_timeout = 300 
urlencoding_mode = normal 
use_https = True 
use_mime_magic = True 
verbosity = WARNING 
website_endpoint = http: //% (bucket) s.s3-their Website% (location) s.amazonaws.com/ 
website_error = 
website_index = index.html

access_key = YOUR-ACCESS-KEY-HERE
You can see how to use s3cmd at: http://s3tools.org/usage

Here I came across a typical scenario where I could not upload files greater than 5GB. You could do this to print two Ways:

1. Using the --multipart-chunk-size-mb flag: s3cmd put --multipart-chunk-size-mb = 4096 201412.tar.gz s3: // apache-logs / I could not do this since I Had an older version of s3cmd installed and I did not really have time to download and install những version.
2. Splitting Into the large files using small files and then uploading it split command.

• Original file

-rw-r - r--. 1 root root 5.4G Jan 20 06:54 201412.tar.gz

• Split Command

split -b 3G 2014backup.tar.gz "201 412"

• Post Split

-rw-r - r--. 1 root root 23 Apr 06:41 3.0G 201412aa
-rw-r - r--. 1 root root 23 Apr 06:43 2.4G 201412ab

• Upload files những

201 412 * s3cmd put s3: // apache-logs /

Saved some time :)

Hadoop 1.0

some rights reserved by intelfreepress

Got opportunity to work with Hadoop with a recent project. Understanding the architecture conceptually and then learn using it is fun. I am still learning it though. This part explains Hadoop 1.0 which I believe helped me to understand 2.0 well.

Before understanding Hadoop it would make more sense if we get rid of a few jargon that would come our way.

Oozie is like a cronjob. In addition to running jobs time based, it also allows running jobs on particular statuses, like:
i. Run job B when Job A completes
ii. Run Job B when a particular file is present.
Oozie is a kind of job coordinator. When you write Oozie, you need to specify in an xml the kind of workflow you want it to follow.

Hive is a dataware housing system for hadoop.

Pig Latin is a kind of Data Analysis. Those who are not java programmers and may not be able to write complex java code can use pig to run the MapReduce job on Hadoop. Syntax is similar to erlang programming language where you could say load this file , group by etc. A simple program of 2 -3 lines which in java may take a some effort could be written easily here. The limitation could be that you may not be able to write very complex logic in Pig. If you have something simple as a log file that you just want to read data from that is separated by tabs, you could use Pig.

Mahout is a machine learning. It provides all the machine learning algorithms which are in place. Mahout just writes a wrapper around existing algos so that you can use it along with Hadoop.

HBase is hadoop database. Its a NoSQL kind of DB which is inside Hadoop and a lower layer of file system that is HDFS.

HDFS Hadoop distributed file system, will sit on top of your existing filesystem. In the native OS the file system could be ext3, ext4 etc. The HDFS sits as a pseudo filesystem on top of your existing filesystem so that you can visualize all the different filesystems on differnt nodes and clusters as one.

Flume and Scoop: Flume handles unstructured data like tweets, logs or semistructured data like xmls. Scoop handles structured data. We can configure flume to read data form apache log directory : /var/log/apache2/error.log

Hadoop has two very important parts.
1. Storage unit
2. Processing unit

Storage unit is where you store, read and write data onto i.e HDFS. This HDFS is distributed across nodes. They are natively redundant, that means it is by default redundant and you do not need to configure RAID or any other software or hardware for this. It would by default make 3 copies of each block. This number is configurable to any number of copies you need.

Hadoop has a Master Slave architecture. It has a master node and a few slave nodes that talk to the master. The master node in Hadoop is known as Name Node. All the nodes that have Data Nodes running could be slave nodes. Different instances can have different or same type of filesystems, but HDFS will be laid across all these nodes. So when you run the command "hadoop fs -ls /" it doesn't bother as to which node the file is present, It will bring files from all nodes data node1 data node2 data node3... and show up. The NameNode keeps track of all the data blocks.

Processing Unit is provided by the MapReduce framework. This can be called as the brain of Hadoop. When you supply a job to Hadoop, it will split the jobs according to the processors you have. If you have a Hadoop cluster with two nodes, each node with one processor. You can run two processes in one cluster parallely.
Locality of reference: Earlier, when you wanted to process a data you would move data close to the processing unit. This required you to 1st copy the data.  It would pull the data in the RAM and then it would process it there. This is fine when dealing with small amount of data. But in case of Hadoop you will be dealing with data in terabytes and petabytes. Here copying or moving of huge data is time consuming. In order to not invlove any data movement, now Hadoop instead moves the processing unit itself to where the data is present. This is called locality of reference.

(To be contd..)

Mumbai Technology Meetup - DevOps Special

On July 27th 10 am a DevOps special meetup was conducted at Directiplex, Mumbai. Its very rare to see a meetup given importance as much as any other technology conference. Speakers from different organizations were present and shared their knowledge. Tremendous knowledge and experience shared free of cost. The meetup went on from 10 am (Started a little late) and went around till 5.30 pm. The agenda itself was too appealing.

No entry fees. Its a free event. Just ensure you learn and make use of that learniing :-)

======================================

11.00 am - 12.00 pm : SaltStack [incl. LXC basic]: by Rigved Rakshit - Directi

Rigved introduced to LXC its setup, its concepts and how its similar/different than Docker. SOme commands and configs. Due to lack of time he could not cover Saltstack though

=====================================

12.00 pm - 1.00 pm : Configuration Management at Rackspace by Shaunak Kashyap - Rackspace

Shaunak conducted this on Hangout while he was at a 12 hr difference. Shaunak showed how rackspace uses Ansible for getting provisioning and other CM task automated.

======================================

1.00 pm - 1.30 pm : Chef Fundamentals and DevOps by Sanju Burkule - OpexSoftware

Sanju took a brief introduction to Chef and how OpexSoftware who are partners of Chef and conduct professional Chef training with certifications. Sanju also shared his knowledge on how Chef is different from Puppet as he has used both.

======================================

1.30 pm - 2.00 pm : Lunch - Lets not talk about this. Blame the rain.

======================================

2.00 pm - 3.00 pm: Puppet [incl. preparatory VirtualBox fundamentals] by Ashish Chandra. - Reliance Jio

Ashish took introduction to Puppet some basics , how easy is it to setup a Puppet master and get going. He also shared some of his scripts that he uses to provision 500 instances in 6 - 7 minutes.

=======================================

3.00 pm - 4.00 pm: Ansible by Aditya Patawari - BrowserStack

This was the 2nd time I met Aditya, we met earlier at RootConf in Bangalore. Aditya shared introduction to Ansible and how is it better/different than Chef//Puppet.

=======================================

4.00 pm - 5.00 pm : Capistrano by Mayur Rokade - Directi

Mayur conducted a live demo of how to use Cap for deploys and a a little intro and setup for Capistrano.

=======================================

5.00 pm - 6.00 pm : Docker Fundamentals by Augustine Correa - Organizer of the event

Bugzilla Mail Sending Issue

Lately an issue was assigned to me where Bugzilla Email notification failed with an 504 gateway timed out error. We use gmail service for sending mails.

After checking the configuration everything seemed to be just fine, except the email was not getting sent and while updating any issue in Bugzilla a 504 error was sure to come.

After a little debugging we got rid of 504 by disabling Email service, but this was not quiet what we wanted. After googling a bit I got to know Bugzilla did not support Gmail as SMTP earlier, but now it did and that we need to install a few external packages for this. I found a tonne of articles with some misleading information or I don't know if I was doing something wrong there.

I applied this patch 1st in the Bugzilla setup directory.

patch < mypatchfile

I first installed Net-SMTP-SSL package after reading a few blogs with CPAN Shell 

perl -MCPAN -e shell

cpan> install Net::SMTP::SSL

./checksetup.pl

Check for Net-SMTP-SSL (v1.01)     ok: found v1.01

Later I tried sending notifications with SMTP in Administration > Parameters > Email (Many articles say that you will see a Gmail option or TLS option, however after installing many packages I didn't see any of those. I was unable to send a mail with SMTP even after many trails.

I finally switched to Sendmail, there was a delay but the mail was getting sent now. But the old problem was still there. Every time you update an issue, you get a 504. I suspect that because there was a delay in the mail being sent, the page used to wait for the mail being sent and then show up, but since it was too long, there could be a time-out value either in Apache or in Bugzilla config that showed up the 504 page.

Next I chose the option use_mailer_queue to be ON, and started the jobqueue.pl deamon. Now the mails are getting sent with no 504. I still suspect that it might have worked without the Net-SMTP-SSL package too.

RootConf 2014

I attended conference and workshop on Devops and Cloud Infrastructure - RootConf 2014 at Bangalore from 14th May to 17th May 2014.

Go Continuous Integration Tool developed by Thoughtworks

CI and Release Management tool developed by Thoughtworks. Helps to manage the build, test it and finally release. It allows you to distribute your build across many systems. So you can run your software on different platforms and make sure that it runs over all of them. You can even divide your tests and parallely run them on different systems, that way you get faster results. All the environments can be managed centrally, so you can promote builds from one environment to the next one.

Simple Steps:

1. Install Go Agent software on all the machines that are part of you system/cloud. 

2. Next configure all the agents to connect to the Go Server

3. Finally Approve every build from Management Dashboard.

4. Associate relevant resources tags for appropriate build tasks with the compatible agents (e.g resource linux, etc)

SELinux : Security Enhanced Linux

This session typically discussed about how SELinux is useful and how people do not understand its importance. Some security policies were discussed. Three important modes of SELinux; enforcing, permissive and disable. Also the hands on session discussed the behavior of these 3 modes of SELinux.

Docker : Light weight linux container

The dry-run of this session was conducted in the Docker-meetup we attended. It was a nice revision as well as some additional parts of docker were known in the session. Docker is a containerization tool that helps you make a light weight Linux container to pack, ship and run you application anywhere. It is an easy to learn tool with very few commands to be learnt and make your own Dockerfile. The containers can be shipped by making an image registry(or by using docker's image registry) by pushing the container from a dev environment and then pulling it from stage, test or prod. You are sure to see the similar environment as that of dev. So no more, "It works on my machine" reason to be heard.

Ansible : Configuration Management Tool

This is just another configuration management tool just like chef. The pros about the tools are :

1. No client server architecture

2. Very easy to install and almost no configuration needed.

3. Very simple to write playbooks, a non programmer can as well understand and write the code within no time since its just a yaml file.

Cons are:

1. Doesn't work on windows.

2. Not much support available since its relatively new.

Jenkins : Continuous Integration

Continuous Integration workshop was pretty much the way we do it traditionally. The workshop covered basics of Jenkins how a job is made and a build is tested an automated.

Conference Update 

Most of the conference talks focused on Docker LXC, Puppet/Ansible. Self healing techniques was introduced and sounded something that we could try and introduce wherein the servers would first intelligently check and see if the problem could be solved by its own with various scripts based on the type of issue. Technique to on board a new team member without merely asking him to read documentation and rather practice hands on was discussed in brief. Tsuru is a new tool that we heard of that may help us to simplify and automate docker as well. A demo on how to testing your infrastructure with Kitchen was shown and that is exactly how we learned it also a part of it showed integration with Docker which is something we need to implement. Introduction to Microsoft Azure cloud gave us an idea of how it is different than other cloud providers. Heartbleed was discussed in brief along with few other security threats and a demo on how Heartbleed actually affected.