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Paul Duvall runs Stelligent, a Continuous Delivery in the Cloud solutions company. He has worked in virtually every role on software projects: developer, project manager, architect, and tester. He is the principal author of Continuous Integration: Improving Software Quality and Reducing Risk (Addison-Wesley, 2007), a 2008 Jolt Award Winner. He is also the author of Startup@Cloud and the forthcoming video DevOps in the Cloud (Pearson Education, June 2012). He contributed to the UML 2 Toolkit (Wiley, 2003) and No Fluff Just Stuff Anthology. Paul authored a 20- article series for IBM developerWorks called Automation for the people. He is passionate about automation, software delivery and the cloud and actively blogs at Stelligent.com. Paul is a DZone MVB and is not an employee of DZone and has posted 10 posts at DZone. You can read more from them at their website. View Full User Profile

Continuous Delivery in the Cloud: Dynamic Configuration

03.07.2013
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In part 1 of this series, I introduced the Continuous Delivery (CD) pipeline for the Manatee Tracking application. In part 2 I went over how we use this CD pipeline to deliver software from checkin to production. In part 3, we focused on how CloudFormation is used to script the virtual AWS components that create the Manatee infrastructure. A list of topics for each of the articles is summarized below:

Part 1: Introduction – Introduction to continuous delivery in the cloud and the rest of the articles;
Part 2: CD Pipeline – In-depth look at the CD Pipeline;
Part 3: CloudFormation – Scripted virtual resource provisioning;
Part 4: Dynamic Configuration –  What you’re reading now;
Part 5: Deployment Automation – Scripted deployment orchestration;
Part 6: Infrastructure Automation – Scripted environment provisioning (Infrastructure Automation)

In this part of the series, I am going to explain how we dynamically generate our configuration and avoid property files whenever possible. Instead of using property files, we store and retrieve configuration on the fly – as part of the CD pipeline – without predefining these values in a static file (i.e. a properties file) ahead of time. We do this using two methods: AWS SimpleDB and CloudFormation.

SimpleDB is a highly available non-relational data storage service that only stores strings in key value pairs. CloudFormation, as discussed in Part 3 of the series, is a scripting language for allocating and configuring AWS virtual resources.

Using SimpleDB

Throughout the CD pipeline, we often need to manage state across multiple Jenkins jobs. To do this, we use SimpleDB. As the pipeline executes, values that will be needed by subsequent jobs get stored in SimpleDB as properties. When the properties are needed we use a simple Ruby script script to return the key/value pair from SimpleDB and then use it as part of the job. The values being stored and retrieved range from IP addresses and domain names to AMI (Machine Images) IDs.

So what makes this dynamic? As Jenkins jobs or CloudFormation templates are run, we often end up with properties that need to be used elsewhere. Instead of hard coding all of the values to be used in a property file, we create, store and retrieve them as the pipeline executes.


if [ $deployToProduction ] == true
then
SSH_KEY=production
else
SSH_KEY=development
fi

# Create Cloudformaton Stack
ruby /usr/share/tomcat6/scripts/aws/create_stack.rb ${STACK_NAME} ${WORKSPACE}/production.template ${HOST} ${JENKINSIP} ${SSH_KEY} ${SGID} ${SNS_TOPIC}

# Load SimpleDB Domain with Key/Value Pairs
ruby /usr/share/tomcat6/scripts/aws/load_domain.rb ${STACK_NAME}

# Pull and store variables from SimpleDB
host=`ruby /usr/share/tomcat6/scripts/aws/showback_domain.rb ${STACK_NAME} InstanceIPAddress`

# Run Acceptance Tests
cucumber features/production.feature host=${host} user=ec2-user key=/usr/share/tomcat6/.ssh/id_rsa
Referenced above in the CreateTargetEnvironment code snippet. This is the load_domain.rb script that iterates over a file and sends key/value pairs to SimpleDB.
require 'rubygems'
require 'aws-sdk'
load File.expand_path('../../config/aws.config', __FILE__)

stackname=ARGV[0]

file = File.open("/tmp/properties", "r")

sdb = AWS::SimpleDB.new

AWS::SimpleDB.consistent_reads do
  domain = sdb.domains["stacks"]
  item = domain.items["#{stackname}"]

  file.each_line do|line|
    key,value = line.split '='
    item.attributes.set(
      "#{key}" => "#{value}")
  end
end
Referenced above in the CreateTargetEnvironment code snippet. This is the showback_domain.rb script which connects to SimpleDB and returns a key/value pair.

load File.expand_path('../../config/aws.config', __FILE__)

item_name=ARGV[0]
key=ARGV[1]

sdb = AWS::SimpleDB.new

AWS::SimpleDB.consistent_reads do
  domain = sdb.domains["stacks"]
  item = domain.items["#{item_name}"]

  item.attributes.each_value do |name, value|
    if name == "#{key}"
      puts "#{value}".chomp
    end
  end
end

In the above in the CreateTargetEnvironment code snippet, we store the outputs of the CloudFormation stack in a temporary file. We then iterate over the file with the load_domain.rb script and store the key/value pairs in SimpleDB.

Following this, we make a call to SimpleDB with the showback_domain.rb script and return the instance IP address (created in the CloudFormation template) and store it in the host variable. host is then used by cucumber to ssh into the target instance and run the acceptance tests.

Using CloudFormation

In our CloudFormation templates we allocate multiple AWS resources. Every time we run the template, a different resource is being used. For example, in our jenkins.template we create a new IAM user. Every time we run the template a different IAM user with different credentials is created. We need a way to reference these resources. This is where CloudFormation comes in. You can reference resources within other resources throughout the script. You can define a reference to another resource using the Ref function in CloudFormation. Using Ref, you can dynamically refer to values of other resources such as an IP Address, domain name, etc.

In the script we are creating an IAM user, referencing the IAM user to create AWS Access keys and then storing them in an environment variable.


"CfnUser" : {
  "Type" : "AWS::IAM::User",
  "Properties" : {
    "Path": "/",
    "Policies": [{
      "PolicyName": "root",
      "PolicyDocument": {
        "Statement":[{
          "Effect":"Allow",
          "Action":"*",
          "Resource":"*"
        }
      ]}
    }]
  }
},

"HostKeys" : {
  "Type" : "AWS::IAM::AccessKey",
  "Properties" : {
    "UserName" : { "Ref": "CfnUser" }
  }
},

"# Add AWS Credentials to Tomcat\n",
"echo \"AWS_ACCESS_KEY=", { "Ref" : "HostKeys" }, "\" >> /etc/sysconfig/tomcat6\n",
"echo \"AWS_SECRET_ACCESS_KEY=", {"Fn::GetAtt": ["HostKeys", "SecretAccessKey"]}, "\" >> /etc/sysconfig/tomcat6\n",

We can then use these access keys in other scripts by referencing the $AWS_ACCESS_KEY and $AWS_SECRET_ACCESS_KEY environment variables.

How is this different from typical configuration management?

Typically in many organizations, there’s a big property with hard coded key/value pairs that gets passed into the pipeline. The pipeline executes using the given parameters and cannot scale or change without a user modifying the property file. They are unable to scale or adapt because all of the properties are hard coded, if the property file hard codes the IP to an EC2 instance and it goes down for whatever reason, their pipeline doesn’t work until someone fixes the property file. There are more effective ways of doing this when using the cloud. The cloud is provides on-demand resources that will constantly be changing. These resources will have different IP addresses, domain names, etc associated with them every time.

With dynamic configuration, there are no property files, every property is generated as part of the pipeline.

With this dynamic approach, the pipeline values change with every run. As new cloud resources are allocated, the pipeline is able to adjust itself and automatically without the need for users to constantly modify property files. This leads to less time spent debugging those cumbersome property file management issues that plague most companies.

In the next part of our series – which is all about Deployment Automation – we’ll go through scripting and testing your deployment using industry-standard tools. In this next article, you’ll see how to orchestrate deployment sequences and configuration using Capistrano.



Published at DZone with permission of Paul Duvall, author and DZone MVB. (source)

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