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.

VPC per envrionvment versus Single VPC for all environments

This blog talks about the two possible ways of hosting your infrastructure in Cloud, though it will be more close to hosting on AWS as it is a real life example but this problem can be applied to any cloud infrastructure set-up. I’m just sharing my thoughts and pros & cons of both approaches but I would love to hear from the people reading this blog about their take as well what do they think.

Before jumping right away into the real talk I would like to give a bit of background on how I come up with this blog, I was working with a client in managing his cloud infrastructure where we had 4 environments dev, QA, Pre Production and Production and each environment had close to 20 instances, apart from applications instances there were some admin instances as well such as Icinga for monitoring, logstash for consolidating logs, Graphite Server to view the logs, VPN server to manage access of people.

At this point we got into a discussion that whether the current infrastructure set-up is the right one where we are having a separate VPC per environment or the ideal setup would have been a single VPC and the environments could have been separated by subnet’s i.e a pair of subnet(public private) for each environment

Both approaches had some pros & cons associated with them

Single VPC set-up

Pros:

  1. You only have a single VPC to manage
  2. You can consolidate your admin app’s such as Icinga, VPN server.

Cons:

  1. As you are separating your environments through subnets you need granular access control at your subnet level i.e instances in staging environment should not be allowed to talk to dev environment instances. Similarly you have to control access of people at granular level as well
  2. Scope of human error is high as all the instances will be on same VPC.

VPC per environment setup

Pros:

  1. You have a clear separation between your environments due to separate VPC’s.
  2. You will have finer access control on your environment as the access rules for VPC will effectively be access rules for your environments.
  3. As an admin it gives you a clear picture of your environments and you have an option to clone you complete environment very easily.

Cons:

  1. As mentioned in pros of Single VPC setup you are at some financial loss as you would be duplicating admin application’s across environments

In my opinion the decision of choosing a specific set-up largely depends on the scale of your environment if you have a small or even medium sized environment then you can have your infrastructure set-up as “All environments in single VPC”, in case of large set-up I strongly believe that VPC per environment set-up is the way to go.

Let me know your thoughts and also the points in favour or against of both of these approaches.

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.