Chef Journey

I’m starting a blog series on chef where I would be taking you to a journey of managing my current infrastructure using Chef. To start with these are the high level tasks lists that I’ve in mind:

  • User Management : User’s creation or deletion on an environment(Dev/QA/Staging/Production) should be managed by chef, along with kind of access on the environment i.e read-only access, root access, or adding a user to some groups.
  • VPN Setup : Currently we are using openvpnas for managing secured access to our environment, it is manual right now so the vpn set-up will also be done by chef.
  • Apache Setup : We are using apache as web server that sits in front of our app server and also provides SSL.
  • Jar App : We have a SOA based set-up in which we have multiple micro java services, so we would be using chef to manage those jar app i.e deploying those jar app’s, starting/stopping those jar app’s.
  • Tomcat : Another major component type in our application are web apps that are hosted on tomcat server, the tomcat server is not managed as a service instead we create tomcat as an app user along with tomcat management scripts.
  • Mongo : We use replicated mongo as No SQL database in our application.
  • Logstash : For managing logs we are using log stash in a clustered set-up where all the log agents publish the logs to a central server and then served by Kibana, so this complete setup should also be managed by chef
  • ActiveMQ : We are using ActiveMQ for our queuing purpose

This list is not complete surely, I’ll be adding many more tasks in this list as I proceed in setting up my environment using chef as this is the first time I’ll be doing a set-up using Chef, but this list will be a good starting point.

Before jumping into creating the Chef cookbooks, runlists or data bags I’ve to setup the base infrastructure of Chef that is Chef Server to which all chef agents talk to, a chef workstation which would be updating the server with the configurations and a git repo to keep track of all my configuration as shown in the image given below.

In the next blog I’ll talk about how I’ll set-up a chef server. Let me know if you have any inputs for me or suggestion that how I should proceed with the chef set-up.

Revert a patch in most awesome way

If you are a Release Engineer, System Admin or Support Engineer you have definitely come across a requirement where you have to apply patches to the target systems be it production or non-production. I’m assuming that you are using some automated system to manage the patches i.e applying them and reverting them. In this blog I would be discussing about the standard way of patch management and how you can have an out of the box solution to revert your patch in most simplistic way and without much fuss. At the end of the blog I would like to see an expression where you will say what the hell it’s so awesome yet so simple :).

People usually use some tool to apply patch to a target system which in addition to applying a patch also manage the history the patches so that it can be reverted in case the patch goes wrong. The patch history usually contains below details:

  1. The new files that were added in the patch, while reverting the patch those files should be deleted.
  2. The files that were deleted by the patch, while reverting the patch the deleted files should be restored back.
  3. The files that were modified by the patch, while reverting the patch the modified files should be restored back.
You can definitely create a tool that can revert the patch for you as the use cases are not much, but do you really need to put this much effort if you can have an out of the box solution for this. What if I tell you that we use git for managing our patch history and reverting them. As git comes with a local repository concept so we created a local git repository at our app server codebase location only. Git comes with all the file level tracking we map each patch with one git commit, so at the time of reverting a specific patch you can ask git to simply revert the commit for you.

Extra steps to be done after applying patch:
To make git track the changes done in patch, you just need to perform 2 extra commands

git add . : This command will track all the files that have been modififed, added or deleted in the system.
git commit -m “Applying Patch” : This command actually adds the files information tracked by previous command with a message in the git system

Steps to be done in reverting changes done by a patch:
Once you have all the information tracked in git it will become no-brainer to revert the patches.

To view the details of all the patches: You can use git log command that will provide you the list of all the patches that you have applied or reverts that you have done

sandy@sandy:~/test/app1$ git log
commit f622f1f97fc44f6897f9edc25f9c6aab8e425049
Author: sandy
Date:   Thu Jun 19 15:19:53 2014 +0530

    Patch 1 on release2

commit 9a1dd81c7799c2f83d897eed85914eecef304bf0
Author: sandy
Date:   Thu Jun 19 15:16:52 2014 +0530

    Release 2

commit 135e04c00b3c3d5bc868f7774a5f284c3eb8cb29
Author: sandy
Date:   Thu Jun 19 15:16:28 2014 +0530

  Release 1

Now Reverting a patch is as simple as executing a simple command git revert, with the commit id of the patch

git revert f622f1f97fc44f6897f9edc25f9c6aab8e425049
[master 0ba533f] q Revert "Patch 1 on release2"
 1 file changed, 1 deletion(-)

If you run git log command, you will see the patch revert history as well

sandy@sandy:~/test/app1$ git log
commit 0ba533fda95ed4d7fcf0b7e6b23cd1a5589946a7
Author: sandy
Date:   Thu Jun 19 15:20:24 2014 +0530

    Revert "Patch 1 on release2"

    This reverts commit f622f1f97fc44f6897f9edc25f9c6aab8e425049.commit f622f1f97fc44f6897f9edc25f9c6aab8e425049
Author: sandy
Date:   Thu Jun 19 15:19:53 2014 +0530

    Patch 1 on release2

commit 9a1dd81c7799c2f83d897eed85914eecef304bf0
Author: sandy
Date:   Thu Jun 19 15:16:52 2014 +0530

    Release 2

commit 135e04c00b3c3d5bc868f7774a5f284c3eb8cb29
Author: sandy
Date:   Thu Jun 19 15:16:28 2014 +0530

    Release 1

I hope this blog has given you a very different perspective of managing the patches, let me know your thoughts about this. Also if you have such more ideas do share with me.

How to secure your Linux Server

Yesterday was a good and bad day for me, bad day because one of my linux server has been hacked. Good day because it was one of the most important task in my pipeline which I wanted to take up, that is securing my systems. As people say being agile or lazy :), do when it is actually required and yesterday was that day.

I’m a novice in infrastructure management, but I really liked this field that’s why I plunged into this domain and now I’m really loving it because of such challenges. Now let’s cut the crap and straightaway jump to the point, I’ve figured few of the best practices that you should always do while configuring your “SECURE” linux server:

  • Don’t use default ssh port for login into the system, or best you can have a policy where you will change your ssh port every month or 2 month.
  • To go a step forward disable the password based login and just enable key base login.
  • Use some intrusion prevention framework, I’ve figured out fail2ban is a good one.
  • Keep all non public facing machines on private ip.
  • In case of public machines only open those ports which are actually required.
  • User firewall to it’s maximum effect. Iptables can be a good option.
  • Have a strong alert system that can monitor your system and raise an alert in case of any suspicious activity. We use Icinga.
Though this list may not cover all the required things that you can take care of, but it can serve as a very good starting point. Also I would love to hear more suggestions that can be used.

A wrapper over linode python API bindings

Recently I’ve been working on automating the nodes creation on our Linode infrastructure, in the process I came across the Linode API and it’s bindings. Though they were powerful but lacks at some places i.e:

  1. In case of Linode CLI, while creating a linode you have to enter the root password so you can’t achieve full automation. Also I was not able to find an option to add private ip to the linode
  2. In case of Linode API python binding you can’t straight away create a running linode machine.

Recently I’ve launched a new GitHub project, this project is a wrapper over existing python bindings of linode and will try to ease out the working with linode api. Currently using this project you can create a linode with 3 lines of code
from linode import Linode
linode=Linode(‘node_identifier’)
linode.create()

You just need to have a property file,/data/linode/linode.properties:

[DEFAULT]
UBUNTU_DIST=Ubuntu 12.04
KERNEL_LABEL=Latest 64 bit
DATACENTER_LABEL=Dallas
PLAN_ID=1024
ROOT_SSH_KEY=
LINODE_API=
 The project is still in development, if someone wants to contribute or have any suggestions you are most welcome.

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.

Puppet module to setup nodejs deployment

I would like to share my puppet module to setup nodejs deployment infrastructure on a linux box. This module performs the basic setup required to facilitate the automated deployment of a nodejs app. Very soon I’ll be introducing another generic puppet module that will run on top of this module & provide a full fledged automatic deployment of any node app. To view the source code of this module you can refer my github repository.

Let’s talk about what this module actually does. First of all we create a nodejs user which we will use for all deployment related activities of all the node app’s, as a convention we have created a folder /home/nodejs/nodeapps this folder will contain all the code of our node applications.

This modules adds 2 scripts as well the first one is deployNodeApp.sh, deployNodeApp.sh is a generic script that assumes that node app code will be present in tar form at /home/nodejs it will clean existing code of nodeapp at /home/nodejs/nodeapps untar the code at corresponding directory of node app & restart the node app. As another convention we are using upstart for managing the node app i.e starting & stopping the node app I’ll talk about the upstart configuration in my next blog where I’ll talk about generic puppet module for a node app. Another script startNodeApp.sh will take care of starting the node app after doing some per-processing such as loading some environment specific properties of node app which we don’t want to commit in the codebase i.e want to separate it out from deployment process choosing a specific version of node.

This module also takes cares of installing nvm for nodejs user so that nodejs version can be managed locally for this user or app.

Though we already have a puppet module for nodejs, but I had some specific requirements which I wanted to handle that’s why I’ve created this module.

Let me know if you have some points of improvement in this module, one thing that I wanted to add in this module is to add npm installation but it had some other dependencies also I had some doubts whether I should have npm as part of nodejs module or not.

Build & Release Challenges : Manual DB Updates Part 2

Previos

This blog was supposed to be about the new system, I thought of building to solve the problem that I discussed in my previous blog. Well for your disappointment this blog will be not about that, the reason is scope of the problem changed. In this blog I’ll be discussing about the new scope and how discussion moved forward about it and what is the current state, which means that I’m still not able to solve this problem & suggestions are welcome :).

I’ll again state the problem which was very simple enough, “database updates were not automated in non prod environments as same db scripts were modified during development“. You need to refer to previous blog for more details about this problem. To solve this problem I came up with incremental db update approach, as per this approach all new modifications will be done as a new sql update which means that let’s say you had a file 1.sql, if you need to do any modification a new file 1′.sql should be committed. In this way the system don’t have to track the files, it just have to maintain what all files got executed, the new files which needs to be executed and execute the new files only. This solution can work in a normal setup very well, in fact in my last assignment I was using this approach only to have automated db updates across all environments.

The incremental db updates can’t be run in current setup, the reason for that is we have very huge database order of 100GB, you can easily imagine that we can’t afford to run same script with slight modifications i.e first script adding a column of size 20 then another script to change it’s size to 40 finally renaming it to some other name. Instead of that a single script should be created after consolidating all these scripts.

The first solution that came to my mind after this new issue emerged, during non prod deployments we should already have database dump of previous release, more preferably cold dump. During deployment 3 steps would be performed first load previous release db dump, run all the consolidated scripts which will be consolidated & do the code deployment. Initially this solution looked fine enough but QA team raised concern as loading previous release dump meant that all the test data  they have created on the QA server would be lost and I was at the beginning of square :).

Another solution that could be implemented  was to have rollback script for each & every script committed. This convention will have an advantage of supporting incremental update i.e whenever a script will be updated first it’s corresponding rollback script will be executed & then the script can be executed. This solution has it’s own challenges the first challenge was it’s really difficult to write rollback script of each & every script, another issues was you have to carefully manage the script files so that there will be no tight coupling between them as execution of rollback of one script will impact another script. Third issue although less significant is that you have to deal with data loss

We could also have used a hybrid approach that is combination of incremental & full db updates. Till QA phase we can use incremental db update mechanism in which all new script modifications are done as a new script and then they can be executed incrementally but for staging & production deployment db updates will be done as a full update which requires a human intervention i.e consolidation of scripts. This approach had 2 challenges the first & foremost was that it had manual intervention & second major issue was that we were duplicating the db scripts.

So these were the few approaches that we thought of & none was able to solve our problem completely, so we are still struggling with fully automating the db update process. Again any suggestions are most welcome 🙂