Big Data on the Cloud using Ansible, RHadoop, AppScale, and AWS/Eucalyptus


Big Data has been a hot topic over the last few years.  Big Data on public clouds, such as AWS’s Elastic MapReduce, has been gaining even more popularity as cloud computing becomes more of an industry standard.

R  is an open source project for statistical computing and graphics.  It has been growing in popularity for doing  linear and nonlinear modeling, classical statistical tests, time-series analysis and others, at various Universities and companies.

R Project
R Project

RHadoop was developed by Revolution Analytics to interface with Hadoop.  Revolution Analytics builds analytic software solutions using R.

Revolution Analytics
Revolution Analytics

AppScale is an open source PaaS that implements the Google AppEngine API on IaaS environments.  One of the Google AppEngine APIs that is implemented is AppEngine MapReduce.   The back-end support for this API that AppScale using Cloudera’s Distribution for Apache Hadoop.

AppScale Inc.
AppScale Inc.

Ansible is an open source orchestration software that utilizes SSH for handling configuration management for physical/virtual machines, and machines running in the cloud.

Ansible Works
Ansible Works

Amazon Web Services is a public IaaS that provides infrastructure and application services in the cloud.  Eucalyptus is an open source software solution that provides the AWS APIs for EC2, S3, and IAM for on-premise cloud environments.

Amazon AWS EC2
Amazon AWS EC2
Eucalyptus Systems Inc.
Eucalyptus Systems Inc.

This blog entry will cover how to deploy AppScale (either on AWS or Eucalyptus), then use Ansible to configure each AppScale node with R, and the RHadoop packages in order allow programs written in R to utilize MapReduce in the cloud.


To get started, the following is needed on a desktop/laptop computer:

*NOTE:  These variables are used by AppScale Tools version 1.6.9.  Check the AWS and Eucalyptus documentation regarding obtaining user credentials. 



After installing AppScale Tools and Ansible, the AppScale cluster needs to be deployed.  After defining the AWS/Eucalyptus variables,  initialize the creation of the AppScale cluster configuration file – AppScalefile.

$ ./appscale-tools/bin/appscale init cloud

Edit the AppScalefile, providing information for the keypair, security group, and AppScale AMI/EMI.  The keypair and security group do not need to be pre-created. AppScale will handle this.  The AppScale AMI on AWS (us-east-1) is ami-4e472227.  The Eucalyptus EMI will be unique based upon the Eucalyptus cloud that is being used.  In this example, the AWS AppScale AMI will be used, and the AppScale cluster size will be 3 nodes.  Here is the example AppScalefile:

group : 'appscale-rmr'
infrastructure : 'ec2'
instance_type : 'm1.large'
keyname : 'appscale-rmr'
machine : 'ami-4e472227'
max : 3
min : 3
table : 'hypertable'

After editing the AppScalefile, start up the AppScale cluster by running the following command:

$ ./appscale-tools/bin/appscale up

Once the cluster finishes setting up, the status of the cluster can be seen by running the command below:

$ ./appscale-tools/bin/appscale status

R, RHadoop Installation Using Ansible

Now that the cluster is up and running, grab the Ansible playbook for installing R, and RHadoop rmr2 and rhdfs packages onto the AppScale nodes.  The playbook can be downloaded from github using git:

$ git clone

After downloading the playbook, the ansible-r-appscale-playbook/production file needs to be populated with the information of the AppScale cluster.  Grab the cluster  node information by running the following command:

$ ./appscale-tools/bin/appscale status | grep amazon | grep Status | awk '{print $5}' | cut -d ":" -f 1

Add those DNS entries to the ansible-r-appscale-playbook/production file.  After editing, the file will look like the following:


Now the playbook can be executed.  The playbook requires the SSH private key to the nodes.  This key will be located under the ~/.appscale folder.  In this example, the key file is named appscale-rmr.key.  To execute the playbook, run the following command:

$ ansible-playbook -i r-appscale-deployment/production 
--private-key=~/.appscale/appscale-rmr.key -v r-appscale-deployment/site.yml

Testing Out The Deployment – Wordcount.R

Once the playbook has finished running, the AppScale cluster is now ready to be used.  To test out the setup, SSH into the head node of the AppScale cluster.  To find out the head node of the cluster, execute the following command:

$ ./appscale-tools/bin/appscale status

After discovering the head node, SSH into the head node using the private key located in the ~/.appscale directory:

$ ssh -i ~/.appscale/appscale-rmr.key

To test out the R setup on all the nodes, grab the wordcount.R program:

root@appscale-image0:~# tar zxf rmr2_2.0.2.tar.gz rmr2/tests/wordcount.R

In the wordcount.R file, the following lines are present

rmr2:::hdfs.put("/etc/passwd", "/tmp/wordcount-test")
out.hadoop = from.dfs(wordcount("/tmp/wordcount-test", pattern = " +"))

When the wordcount.R program is executed, it will grab the /etc/password file from the head node, copy it to the hdfs filesystem, then run wordcount on /etc/password to look for the pattern ” +”.   NOTE: wordcount.R can be edited to use any file and pattern desired.

Run wordcount.R:

root@appscale-image0:~# R

R version 2.15.3 (2013-03-01) -- "Security Blanket"
Copyright (C) 2013 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

  Natural language support but running in an English locale

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

[Previously saved workspace restored]

> source('rmr2/tests/wordcount.R')
Loading required package: Rcpp
Loading required package: RJSONIO
Loading required package: digest
Loading required package: functional
Loading required package: stringr
Loading required package: plyr
13/04/05 02:33:41 INFO security.UserGroupInformation: JAAS Configuration already set up for Hadoop, not re-installing.
13/04/05 02:33:43 INFO security.UserGroupInformation: JAAS Configuration already set up for Hadoop, not re-installing.
packageJobJar: [/tmp/RtmprcYtsu/rmr-local-env19811a7afd54, /tmp/RtmprcYtsu/rmr-global-env1981646cf288, /tmp/RtmprcYtsu/rmr-streaming-map198150b6ff60, /tmp/RtmprcYtsu/rmr-streaming-reduce198177b3496f, /tmp/RtmprcYtsu/rmr-streaming-combine19813f7ea210, /var/appscale/hadoop/hadoop-unjar5632722635192578728/] [] /tmp/streamjob8198423737782283790.jar tmpDir=null
13/04/05 02:33:44 WARN snappy.LoadSnappy: Snappy native library is available
13/04/05 02:33:44 INFO util.NativeCodeLoader: Loaded the native-hadoop library
13/04/05 02:33:44 INFO snappy.LoadSnappy: Snappy native library loaded
13/04/05 02:33:44 INFO mapred.FileInputFormat: Total input paths to process : 1
13/04/05 02:33:44 INFO streaming.StreamJob: getLocalDirs(): [/var/appscale/hadoop/mapred/local]
13/04/05 02:33:44 INFO streaming.StreamJob: Running job: job_201304042111_0015
13/04/05 02:33:44 INFO streaming.StreamJob: To kill this job, run:
13/04/05 02:33:44 INFO streaming.StreamJob: /root/appscale/AppDB/hadoop-0.20.2-cdh3u3/bin/hadoop job  -Dmapred.job.tracker= -kill job_201304042111_0015
13/04/05 02:33:44 INFO streaming.StreamJob: Tracking URL: http://appscale-image0:50030/jobdetails.jsp?jobid=job_201304042111_0015
13/04/05 02:33:45 INFO streaming.StreamJob:  map 0%  reduce 0%
13/04/05 02:33:51 INFO streaming.StreamJob:  map 50%  reduce 0%
13/04/05 02:33:52 INFO streaming.StreamJob:  map 100%  reduce 0%
13/04/05 02:33:59 INFO streaming.StreamJob:  map 100%  reduce 33%
13/04/05 02:34:02 INFO streaming.StreamJob:  map 100%  reduce 100%
13/04/05 02:34:04 INFO streaming.StreamJob: Job complete: job_201304042111_0015
13/04/05 02:34:04 INFO streaming.StreamJob: Output: /tmp/RtmprcYtsu/file1981524ee1a3
13/04/05 02:34:05 INFO security.UserGroupInformation: JAAS Configuration already set up for Hadoop, not re-installing.
13/04/05 02:34:07 INFO security.UserGroupInformation: JAAS Configuration already set up for Hadoop, not re-installing.
13/04/05 02:34:08 INFO security.UserGroupInformation: JAAS Configuration already set up for Hadoop, not re-installing.
13/04/05 02:34:10 INFO security.UserGroupInformation: JAAS Configuration already set up for Hadoop, not re-installing.
Deleted hdfs://

Thats it!  The AppScale cluster is ready for additional R programs that utilize MapReduce.   Enjoy the world of Big Data on public/private IaaS.

Big Data on the Cloud using Ansible, RHadoop, AppScale, and AWS/Eucalyptus

Test Drive: Drupal Deployment on Eucalyptus using Stackato, Amazon Route 53 and the Eucalyptus Community Cloud

Recently, I did a blog discussing how to deploy a Jenkins server using Stackato, running on Eucalyptus.  At the end of that blog, I mentioned how the Eucalyptus Community Cloud (ECC) could be used for testing out the Stackato Microcloud image on Eucalyptus.   The previous blog – I felt – was more for DevOps administrators who had access to their own on-premise Eucalyptus clouds.  The inspiration of this blog comes from the blog on ActiveBlog entitled “Deploy & Scale Drupal on Any Cloud with Stackato” to show love to Web Developers, and show the power of Amazon’s Route 53.

Test Drive Pre-Reqs

The prerequisites for this blog are the same that are mentioned in my previous blog regarding using Stackato on Eucalyptus (for the Eucalyptus pre-reqs, make sure the ECC is being used).  In addition to the prerequisites mentioned above, the following is needed:

After the prerequisites have been met, its time to setup the Drupal environment.

Test Drive Engage!

Since the ECC is being used, there is no need to worry about bundling, uploading and registering the Stackato image.  The Stackato image used for this blog is as follows:

IMAGE emi-859B3D5C stackato_v2.6.6/stackato-cloudinit.manifest.xml
150820662310 available public x86_64 machine eki-6FBE3D2D eri-67463B77 instance-store

Next, lets make sure the user has an elastic IP that will be used in AWS Route 53, and a security group to allow proper network traffic to the instance.  Do the following:

  1. Make sure the user credentials are sourced correctly, and euca2ools is installed correctly.
  2. Grab an elastic IP using euca-allocate-address (in this example was allocated):

    # euca-allocate-address

  3. If the user already doesn’t have a keypair, create a keypair for the user by using euca-create-keypair, and make sure the permission of the file is 0600:  

    # euca-create-keypair hspencer-stackato > hspencer-stackato.priv 
    # chmod 0600 hspencer-stackato.priv

  4. Create a security group for the instance to use:

    # euca-create-group stackato-test -d "Test Security Group for Stackato PaaS"
    GROUP stackato-test Test Security Group for Stackato PaaS

  5. Authorize ping, ssh, http, and https ports:

    # euca-authorize -P icmp -t -1:-1 -s stackato-test
    GROUP stackato-test
    PERMISSION stackato-test ALLOWS icmp -1 -1 FROM CIDR
    # euca-authorize -P tcp -p 22 -s stackato-test
    GROUP stackato-test
    PERMISSION stackato-test ALLOWS tcp 22 22 FROM CIDR
    # euca-authorize -P tcp -p 80 -s stackato-test
    GROUP stackato-test
    PERMISSION stackato-test ALLOWS tcp 80 80 FROM CIDR
    # euca-authorize -P tcp -p 443 -s stackato-test
    GROUP stackato-test
    PERMISSION stackato-test ALLOWS tcp 443 443 FROM CIDR

  6. Now, launch the instance, specifying the keypair name to use, and a VM type.  On the ECC, only m1.xlarge and c1.xlarge meet the requirements of launching the Stackato image:

    # euca-run-instances -k hspencer-stackato -t c1.xlarge emi-859B3D5C -g stackato-test
    RESERVATION r-66EE4030 628376682871 stackato-test
    INSTANCE i-E85843C4 emi-859B3D5C euca-0-0-0-0.eucalyptus.internal
     pending hspencer-stackato 0 c1.xlarge 2013-02-24T19:40:35.516Z partner01 eki-6FBE3D2D
     eri-67463B77 monitoring-disabled instance-store

  7. Once the instance gets to a running state, associate the elastic IP that the user owns to the instance:

    # euca-describe-instances
    RESERVATION r-66EE4030 628376682871 stackato-test
    INSTANCE i-E85843C4 emi-859B3D5C
     euca-10-9-190-24.eucalyptus.internal running hspencer-stackato 0 c1.xlarge 
    2013-02-24T19:40:35.516Z partner01 eki-6FBE3D2D eri-67463B77 monitoring-disabled instance-store
    # euca-associate-address -i i-E85843C4
    ADDRESS i-E85843C4
    # euca-describe-instances
    RESERVATION r-66EE4030 628376682871 stackato-test
    INSTANCE i-E85843C4 emi-859B3D5C
     euca-10-9-190-24.eucalyptus.internal running hspencer-stackato 0 c1.xlarge 2013-02-24T19:40:35.516Z
     partner01 eki-6FBE3D2D eri-67463B77 monitoring-disabled instance-store

  8. Log into the AWS management console,  select Route 53, and setup the A and CNAME records in your domain as mentioned here under the Stackato Documentation regarding detailed DNS configuration.  In this example, the DNS name associated with the elastic IP is
  9. Next ssh into the instance, and proceed to follow the steps for setting up the Stackato instance that is mentioned in my previous blog under the section Configuration of the Stackato Instance.  Make sure the DNS name setup in AWS Route 53 is used with “kato rename public-DNS-name” and “kato setup core api.public-DNS-name” configuration steps.
  10. After the instance is configured, just open up the browser and go to the DNS name set up for the Stackato instance in AWS Route 53, as mentioned in the Stackato Documentation regarding configuration via the Management Console.
  11. Once logged into the Stackato Management Console, select “App Store” in the lefthand menu and select “Drupal” to install

    App Store - Drupal Application
    App Store – Drupal Application


  12. After Drupal has installed, start the application.  Once it has started successfully, select the URL that shows up in the right-hand menu box.  The Drupal log-in page will appear in your browser

    Drupal Landing Page
    Drupal Landing Page

Thats it!  Now Drupal is ready for any web developer to test out on the ECC.  If there is any questions/comments/suggestions, please feel free to leave comments.  Enjoy!

Test Drive: Drupal Deployment on Eucalyptus using Stackato, Amazon Route 53 and the Eucalyptus Community Cloud

Jenkins, Stackato, Cloud-Init and Eucalyptus == Potent Combination for an On-Premise Continuous Integration Environment

The Ingredients


An extendable open source continuous integration server.


The Enterprise Private PaaS that makes it easy to deploy, manage, and monitor applications on any cloud.


The Ubuntu package that handles early initialization of a cloud instance. It is installed in the Ubuntu Cloud Images and also in the official Ubuntu images available on EC2.


Allows you to build production-ready, AWS-compatible private and hybrid clouds by leveraging your existing virtualized infrastructure to create on-demand cloud resource pools.

What happens when you combine all three of these tools?  A potent combination for continuous integration on a easy-to-configure PaaS and an on-premise, AWS-compatible IaaS.  With this combination, developers can take advantage of easy configuration that Stackato brings to the table, running on top of Eucalyptus – bringing an AWS-like cloud environment into your datacenter.

This blog entry will discuss the steps that I took to get Jenkins installed on a Stackato instance store-backed instance running on Eucalyptus.  But before I get started, I would like to thank the folks from ActiveState for all their guidance.  Their support staff is really top notch, and very helpful.  Check them out in #stackato on  They can also be checked out on Twitter at @ActiveState. Now on to the dirty work…..

The Recipe for Success

The Stackato Microcloud Image and Cloud-Init

To begin, the following is needed:

After downloading the Stackato VM for KVM and unzipping the file, we will need to pull out the root file system, the kernel and ramdisk.  These will be uploaded, bundled and registered as the EMI, EKI, and ERI.  To extract the root filesystem, do the following:

  1. Use parted to locate the root filesystem as follows:    
    # parted stackato-img-kvm-v2.6.6.img
    GNU Parted 2.1
    Using /root/images/Stackato-VM/stackato-img-kvm-v2.6.6.img
    Welcome to GNU Parted! Type 'help' to view a list of commands.
    (parted) U
    Unit? [compact]? b
    (parted) p
    Model: (file)
    Disk /root/images/Stackato-VM/stackato-img-kvm-v2.6.6.img: 10737418240B
    Sector size (logical/physical): 512B/512B
    Partition Table: msdos
    Number Start End Size Type File system Flags
    1 1048576B 200278015B 199229440B primary ext3 boot
    3 200278016B 1237319679B 1037041664B primary linux-swap(v1)
    2 1237319680B 10736369663B 9499049984B primary ext4
    (parted) quit
  2. In this example, the root filesystem is partition 2.  The value for “Start” and “Size” will need to be used.  Next, run dd to extract the root filesystem:
    dd if=stackato-img-kvm-v2.6.6.img of=stackato-rootfs.img
     bs=1 skip=1237319680 count=9499049984
  3. Once it has completed, mount  stackato-rootfs.img to the loopback device:
    mount -o loop stackato-rootfs.img /mnt/
  4. Copy out initrd.img-3.2.0-27-virtual  and vmlinuz-3.2.0-27-virtual from /mnt/boot.
  5. In /mnt/etc/fstab, replace the UUID entry with LABEL.  The LABEL will look simliar to the following:  
    LABEL=cloudimg-rootfs    /               ext4   defaults     1       1
  6. Chroot to /mnt – there may be a need to do a mount -o bind for sys, dev, and proc.
  7. Run “dpkg-reconfigure cloud-init”, and make sure that the EC2 Data Source is selected.
  8. Unmount stackato-rootfs.img (if sys, dev, and proc were mounted, unmount them before unmounting stackato-rootfs.img).  After it has been unmounted, run tune2fs to change the label of the image:
    tune2fs -L cloudimg-rootfs stackato-rootfs.img

After following these steps, the following should be available:

  • initrd.img-3.2.0-27-virtual – to be bundled, uploaded and registered as the ERI
  • vmlinuz-3.2.0-27-virtual – to be bundled, uploaded and registered as the EKI
  • stackato-rootfs.img – to be bundled, uploaded and registered as the EMI

Go through the steps of bundling, uploading and registering the ERI, EKI, and EMI.  For additional information, please refer to the Add an Image section of the Eucalyptus 3.2 User Guide.

Launching the Stackato Image

Now its time to launch the Stackato image on Eucalyptus.  Since cloud-init has the enabled EC2 data source now, when the image is launched, the instance will grab ssh keys, and mount the ephemeral storage.  Also, additional configuration can be passed using the user-data file option.  More information regarding this can be found on Stackato’s documentation in reference to using cloud-init.  Key thing to remember here is that the minimum RAM requirement for the Stackato image is 2 gigs.  Make sure the VM type used for launching the Stackato image has at least 2 gigs of RAM or more.  In this example, the image ID is emi-DAB23A8A.  The ramdisk and kernel are registered as eri-9B453C09 and eki-ADF640B0.   The VM type c1.xlarge is used, which has 4 CPU,  4096 MB of RAM,  and    50 Gigs of disk space.

euca-run-instances -k admin emi-DAB23A8A -t c1.xlarge 
--kernel eki-ADF640B0 --ramdisk eri-9B453C09

Use euca-describe-instances to check to see when the instance reaches a running state:

euca-describe-instances i-100444EF
RESERVATION r-CC69438B 345590850920 default
INSTANCE i-100444EF emi-DAB23A8A 
euca-10-106-101-17.wu-tang.internal running admin 0 c1.xlarge 2013-02-23T00:34:07.436Z enter-the-wu eki-ADF640B0 
eri-9B453C09 monitoring-disabled instance-store

The key thing for running a Stackato instance is setting up the correct DNS entries.  For more information regarding setting up DNS with regards to a Stackato instance, please read the Detail Configuration section on DNS in the Stackato online documentation.  For this example, instead of using an external DNS service using a tool like nsupdate, to configure the A record and CNAME records, we will use is a magic domain name that provides wildcard DNS for any IP address.  Next, its time to configure the Stackato instance.

Configuration of the Stackato Instance

To configure the Stackato instance, do the following:

  1. SSH into the instance.  

    ssh -i creds/admin.priv
  2. Make note of the ip address associated with eth0 and the netmask using ifconfig.  Also note the gateway IP by using the route command.
  3. Run “kato op static_ip” to configure the static IP address for eth0.  Make sure and add as the first entry as part of the nameservers, and add “containers.” as the first entry under the search domains.
  4. Run “kato rename public DNS name “, where public DNS name includes the public IP of the instance, using (e.g.
  5. Run “kato disable mdns”, then run “sudo reboot” to reboot the instance.
  6. Once the instance has come back up, ssh into the instance, and run the following command  “kato setup core api.public DNS name” where public DNS name is the same value used for the “kato rename” step (e.g.
  7. Next, edit /etc/resolv.conf and make sure that the value for the search option is “containers.”, and the first entry for the nameservers is
  8. Finally, run “kato enable –all-but mdns”

Thats it!  Now go to the public DNS name that was used in your favorite browser.  For this example, was used.  The following landing page should look similar to what you see here in the Stackato documentation regarding accessing the instance through the management console.

Setting Up Jenkins

After setting up the admin account, navigate to the “App Store” on the lefthand menu.  Once selected, navigate to find the Jenkins application:


Jenkins Application
Jenkins Application


After selecting to install Jenkins, select “Yes” to install.  After the installation takes place,  select “Applications” in the left hand menu.  From there, select the Jenkins application, and select “Start” (its the green arrow to the right of the application window).   Once it has started, you will see the following:

Jenkins Running in Stackato
Jenkins Running in Stackato


Now Jenkins is ready to be used.

If anyone wants to test this out on Eucalyptus but doesn’t have access to their own Eucalyptus cloud, fear not, the Eucalyptus Community Cloud has the Stackato image available.  After applying to get access to the Community Cloud, follow the steps above.  The image for Stackato is as follows:

IMAGE emi-859B3D5C stackato_v2.6.6/stackato-cloudinit.manifest.xml 150820662310 available public x86_64 machine eki-6FBE3D2D eri-67463B77 instance-store

And as always, this image and steps can be used on AWS EC2 as well.🙂

Let me know if there are any questions.  Feedback is always welcome.  Enjoy!

Jenkins, Stackato, Cloud-Init and Eucalyptus == Potent Combination for an On-Premise Continuous Integration Environment

OpenLDAP Sandbox in the Clouds


I really enjoy OpenLDAP.  I think folks really don’t understand the power of OpenLDAP, concerning its robustness (i.e. use multiple back-ends), speed and efficiency.

I think its important to have sandboxes to test various technologies.  The “cloud” is the best place for this.  To test out the latest builds provided by OpenLDAP (via git), I created a cloud-init script that allows me to configure, build, and install an OpenLDAP sandbox environment in the cloud (on-premise and/or public).  This script has been tested on AWS and Eucalyptus using Ubuntu Precise 12.04 LTS.   This blog entry is a compliment to my past blog regarding overlays, MDB and OpenLDAP.

Lean Requirements – Script, Image, and Cloud

When thinking about this setup, there were three goals in mind:

  1. Ease of configuration – this is why cloud-init was used.  Its very powerful in regards to bootstrapping instances as they boot up.  You can use Puppet, Chef or others (e.g. Salt Stack, Juju, etc.), but I decided to go with cloud-init.  The script does the following:
    • Downloads all the prerequisites for building OpenLDAP from source, including euca2ools.
    • Downloads OpenLDAP using Git
    • Set up ephemeral storage to be the installation point for OpenLDAP (e.g. configuration, storage, etc.)
    • Adds information into /etc/rc.local to make sure ephemeral gets re-mounted on reboots of the instance, and hostname is set.
    • Configures, builds and installs OpenLDAP.
  2. Cloud image that is ready to go – Ubuntu has done a wonderful job with their cloud images.  They have made it really easy to access them on AWS. These images can be used on Eucalyptus as well.
  3. Public and Private Cloud Deployment – Since Eucalyptus follows the AWS EC2 API very closely, it makes it really easy to test on both AWS and Eucalyptus.

Now that the background has been covered a bit, the next section will cover deploying the sandbox on AWS and/or Eucalyptus.

Deploy the Sandbox

To set the sandbox setup, use the following steps:

  1. Make sure and have an account on AWS and/or Eucalyptus (and the correct AWS/Eucalyptus IAM policies are in place so that you can bundle, upload and register images to AWS S3 and Eucalyptus Walrus).
  2. Make sure you have access to a registered AMI/EMI that runs Ubuntu Precise 12.04 LTS.  *NOTE* If you are using AWS, you can just go to the Ubuntu Precise Cloud Image download page, and select the AMI in the region that you have access to.
  3. Download the openldap cloud-init recipe from Eucalyptus/recipes repository.
  4. Download and install the latest Euca2ools (I used  the command-line tool euca-run-instances to run these instances).
  5. After you have downloaded your credentials from AWS/Eucalyptus, define your global environments by either following the documentation for AWS EC2 or the documentation for Eucalyptus.
  6. Use euca-run-instances with the –user-data-file option to launch the instance:  

    euca-run-instances -k hspencer.pem ....
     --user-data-file cloud-init-openldap.config [AMI | EMI]

After the instance is launched, ssh into the instance, and you will see something similar to the following:

ubuntu@euca-10-106-69-149:~$ df -ah
Filesystem Size Used Avail Use% Mounted on
/dev/vda1 1.4G 1.2G 188M 86% /
proc 0 0 0 - /proc
sysfs 0 0 0 - /sys
none 0 0 0 - /sys/fs/fuse/connections
none 0 0 0 - /sys/kernel/debug
none 0 0 0 - /sys/kernel/security
udev 494M 12K 494M 1% /dev
devpts 0 0 0 - /dev/pts
tmpfs 200M 232K 199M 1% /run
none 5.0M 0 5.0M 0% /run/lock
none 498M 0 498M 0% /run/shm
/dev/vda2 8.0G 159M 7.5G 3% /opt/openldap

Your sandbox environment is now set up.  From here, just following the instructions in the OpenLDAP Administrator’s Guide on configuring your openldap server, or continue from the “Setup – OLC and MDB” section located in my previous blog.  *NOTE* As you configure your openldap server, make sure and use euca-authorize to control access to your instance.


OpenLDAP Sandbox in the Clouds