CloudStack Installation from GIT repo for Developers

This guide is aimed at CloudStack developers who need to build the code. These instructions are valid on a Ubuntu 22.04 and 24.04 systems and were tested with the 4.19 release of Apache CloudStack. Community maintained CloudStack self-learning course is also available at CloudStack HackerBook.

Please adapt them if you are on a different operating system or using a newer/older version of CloudStack. This book is composed of the following sections:

  1. Installation of the prerequisites

  2. Compiling and installation from source

  3. Using the CloudStack Simulator

  4. Using Appliance for development

  5. Building your own packages

  6. The CloudStack API

Prerequisites

In this section we’ll look at installing the dependencies you’ll need for Apache CloudStack development.

To build and test CloudStack from source you will need the following installed: * jdk 11+ (openjdk-11-jdk) * maven 3+ * git * python3-pip * python3-setuptools * mkisofs * MySql 8x Server

Example Ubuntu

sudo apt update
sudo apt install git openssh-client openjdk-11-jdk maven mysql-client mysql-server nfs-kernel-server quota genisoimage python3 python3-pip

Note: ensure to install python 3.8/3.9/3.10, as required you can install specific Python3 versions using pyenv. Similarly, Java versions can be installed and managed using jenv.

Installing CloudStack from Source

CloudStack uses git for source version control, if you know little about git is a good start. Once you have git setup on your machine, pull the source with:

git clone https://github.com/apache/cloudstack.git

To build a stable release, checkout the branch for that version:

git checkout 4.19

Optional, you can install noredist/nonoss dependencies:

git clone https://github.com/shapeblue/cloudstack-nonoss
cd cloudstack-nonoss && bash -x install-non-oss.sh

To compile Apache CloudStack, go to the cloudstack source folder and run:

mvn -Pdeveloper,systemvm clean install

If you want to skip the tests add -DskipTests to the command above. Do NOT use -Dmaven.test.skip=true because that will break the build. To build noredist/nonoss add -Dnoredist flag to the command.

If you have set a root mysql password, you will need to adjust the password in utils/conf/db.properties

Deploy the database next:

mvn -P developer -pl developer -Ddeploydb

Run Apache CloudStack with jetty for testing

mvn -pl :cloud-client-ui jetty:run

To build and run the UI, do this:

curl -sL https://deb.nodesource.com/setup_16.x | sudo -E bash -
sudo apt install nodejs
cd cloudstack/ui
npm install
npm run serve

Log Into Apache CloudStack:

Open your Web browser and use this URL to connect to CloudStack:

http://localhost:5050 # this runs the UI
http://localhost:8080/client/ # this is the API backend

Replace localhost with the IP of your management server if need be.

Note

If you have iptables enabled, you may have to open the ports used by CloudStack. Specifically, ports 8080, 8250, and 9090.

You can now start configuring a Zone, playing with the API. Of course we did not setup any infrastructure, there is no storage, no hypervisors…etc. However you can run tests using the simulator. The following section shows you how to use the simulator so that you don’t have to setup a physical infrastructure.

Using the Simulator

CloudStack comes with a simulator for hosts, Instances and Network infrastructure, allowing you to use the CloudStack management server without using real servers. It also comes with Marvin, which can create a set of infrastructure based on a configuration file that defines the number of zones/pods/clusters/hosts, types of storage etc. Marvin combined with the simulator enable you to develop and test the CloudStack management server as if it was managing production infrastructure.

Stop jetty (from any previous runs, if running)

mvn -pl :cloud-client-ui jetty:stop

Do a clean build with the simulator option enabled:

mvn -Pdeveloper -Dsimulator -DskipTests clean install

Deploy the database (skip first line if you did this earlier):

mvn -Pdeveloper -pl developer -Ddeploydb
mvn -Pdeveloper -pl developer -Ddeploydb-simulator

Start jetty with the simulator enabled

mvn -Dsimulator -pl :cloud-client-ui jetty:run

Setup a basic or advanced zone with Marvin. In a separate shell://

python3 tools/marvin/marvin/deployDataCenter.py -i setup/dev/basic.cfg
OR
python3 tools/marvin/marvin/deployDataCenter.py -i setup/dev/advanced.cfg

At this stage log in the CloudStack management server UI at http://localhost:5050 or using CLI with the API endpoint at http://localhost:8080/client with the credentials admin/password, you should see a fully configured zone infrastructure.

You can now run integration tests, use the API etc.

Using Appliance for development

The Installing from source section will only get you to the point of runnign the management server, it does not get you any hypervisors. The simulator section gets you a simulated datacenter for testing. An appliance based development such as using mbx can allow you to run at least one hypervisor and add it to your management server the way you would a real physical machine.

MonkeyBox or mbx enable VM/appliance-based CloudStack development. It is tested with Ubuntu and uses KVM and prebuilt images to deploy QA and dev environments for anybody to try out CloudStack with a range of hypervisors, local and NFS storage.

Please refer to the project for more details: https://github.com/shapeblue/mbx

Building Packages

Working from source is necessary when developing CloudStack. As mentioned earlier this is not primarily intended for users. However some may want to modify the code for their own use and specific infrastructure. The may also need to build their own packages for security reasons and due to network connectivity constraints. This section shows you the gist of how to build packages. We assume that the reader will know how to create a repository to serve this packages. The complete documentation is available in the Building DEB packages section.

To build debian packages you will need couple extra packages that we did not need to install for source compilation:

apt-get install python-mysqldb
apt-get install debhelper

Then build the packages with:

dpkg-buildpackage -uc -us

One directory up from the CloudStack root dir you will find:

cloudstack_|release|_amd64.changes
cloudstack_|release|.dsc
cloudstack_|release|.tar.gz
cloudstack-agent_|release|_all.deb
cloudstack-cli_|release|_all.deb
cloudstack-common_|release|_all.deb
cloudstack-docs_|release|_all.deb
cloudstack-management_|release|_all.deb
cloudstack-usage_|release|_all.deb

Of course the community provides a repository for these packages and you can use it instead of building your own packages and putting them in your own repo. Instructions on how to use this community repository are available in the installation book.

The CloudStack API

The CloudStack API is a query based API using http that return results in XML or JSON. It is used to implement the default web UI. This API is not a standard like OGF OCCI or DMTF CIMI but is easy to learn. Mapping exists between the AWS API and the CloudStack API as will be seen in the next section. Recently a Google Compute Engine interface was also developed that maps the GCE REST API to the CloudStack API described here. The API docs are a good start to learn the extent of the API. Multiple clients exist on GitHub to use this API, you should be able to find one in your favorite language. The reference documentation for the API and changes that might occur from version to version is availble on-line. This short section is aimed at providing a quick summary to give you a base understanding of how to use this API. As a quick start, a good way to explore the API is to navigate the dashboard with a firebug console (or similar developer console) to study the queries.

In a succint statement, the CloudStack query API can be used via http GET requests made against your cloud endpoint (e.g http://localhost:8080/client/api). The API name is passed using the command key and the various parameters for this API call are passed as key value pairs. The request is signed using the access key and secret key of the user making the call. Some calls are synchronous while some are asynchronous, this is documented in the API docs. Asynchronous calls return a jobid, the status and result of a job can be queried with the queryAsyncJobResult call. Let’s get started and give an example of calling the listUsers API in Python.

First you will need to generate keys to make requests. Going through the dashboard, go under Accounts select the appropriate account then click on Show Users select the intended users and generate keys using the Generate Keys icon. You will see an API Key and Secret Key field being generated. The keys will be of the form:

API Key : XzAz0uC0t888gOzPs3HchY72qwDc7pUPIO8LxC-VkIHo4C3fvbEBY_Ccj8fo3mBapN5qRDg_0_EbGdbxi8oy1A
Secret Key: zmBOXAXPlfb-LIygOxUVblAbz7E47eukDS_0JYUxP3JAmknOYo56T0R-AcM7rK7SMyo11Y6XW22gyuXzOdiybQ

Open a Python shell and import the basic modules necessary to make the request. Do note that this request could be made many different ways, this is just a low level example. The urllib* modules are used to make the http request and do url encoding. The hashlib module gives us the sha1 hash function. It used to geenrate the hmac (Keyed Hashing for Message Authentication) using the secretkey. The result is encoded using the base64 module.

$python
Python 2.7.3 (default, Nov 17 2012, 19:54:34)
[GCC 4.2.1 Compatible Apple Clang 4.1 ((tags/Apple/clang-421.11.66))] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> import urllib2
>>> import urllib
>>> import hashlib
>>> import hmac
>>> import base64

Define the endpoint of the Cloud, the command that you want to execute, the type of the response (i.e XML or JSON) and the keys of the user. Note that we do not put the secretkey in our request dictionary because it is only used to compute the hmac.

>>> baseurl='http://localhost:8080/client/api?'
>>> request={}
>>> request['command']='listUsers'
>>> request['response']='json'
>>> request['apikey']='plgWJfZK4gyS3mOMTVmjUVg-X-jlWlnfaUJ9GAbBbf9EdM-kAYMmAiLqzzq1ElZLYq_u38zCm0bewzGUdP66mg'
>>> secretkey='VDaACYb0LV9eNjTetIOElcVQkvJck_J_QljX_FcHRj87ZKiy0z0ty0ZsYBkoXkY9b7eq1EhwJaw7FF3akA3KBQ'

Build the base request string, the combination of all the key/pairs of the request, url encoded and joined with ampersand.

>>> request_str='&'.join(['='.join([k,urllib.quote_plus(request[k])]) for k in request.keys()])
>>> request_str
'apikey=plgWJfZK4gyS3mOMTVmjUVg-X-jlWlnfaUJ9GAbBbf9EdM-kAYMmAiLqzzq1ElZLYq_u38zCm0bewzGUdP66mg&command=listUsers&response=json'

Compute the signature with hmac, do a 64 bit encoding and a url encoding, the string used for the signature is similar to the base request string shown above but the keys/values are lower cased and joined in a sorted order

>>> sig_str='&'.join(['='.join([k.lower(),urllib.quote_plus(request[k].lower().replace('+','%20'))])for k in sorted(request.iterkeys())])
>>> sig_str
'apikey=plgwjfzk4gys3momtvmjuvg-x-jlwlnfauj9gabbbf9edm-kaymmailqzzq1elzlyq_u38zcm0bewzgudp66mg&command=listusers&response=json'
>>> sig=hmac.new(secretkey,sig_str,hashlib.sha1).digest()
>>> sig
'M:]\x0e\xaf\xfb\x8f\xf2y\xf1p\x91\x1e\x89\x8a\xa1\x05\xc4A\xdb'
>>> sig=base64.encodestring(hmac.new(secretkey,sig_str,hashlib.sha1).digest())
>>> sig
'TTpdDq/7j/J58XCRHomKoQXEQds=\n'
>>> sig=base64.encodestring(hmac.new(secretkey,sig_str,hashlib.sha1).digest()).strip()
>>> sig
'TTpdDq/7j/J58XCRHomKoQXEQds='
>>> sig=urllib.quote_plus(base64.encodestring(hmac.new(secretkey,sig_str,hashlib.sha1).digest()).strip())

Finally, build the entire string by joining the baseurl, the request str and the signature. Then do an http GET:

>>> req=baseurl+request_str+'&signature='+sig
>>> req
'http://localhost:8080/client/api?apikey=plgWJfZK4gyS3mOMTVmjUVg-X-jlWlnfaUJ9GAbBbf9EdM-kAYMmAiLqzzq1ElZLYq_u38zCm0bewzGUdP66mg&command=listUsers&response=json&signature=TTpdDq%2F7j%2FJ58XCRHomKoQXEQds%3D'
>>> res=urllib2.urlopen(req)
>>> res.read()
{
   "listusersresponse" : {
      "count":1 ,
      "user" : [
         {
            "id":"7ed6d5da-93b2-4545-a502-23d20b48ef2a",
            "username":"admin",
            "firstname":"admin",
            "lastname":"cloud",
            "created":"2012-07-05T12:18:27-0700",
            "state":"enabled",
            "account":"admin",
            "accounttype":1,
            "domainid":"8a111e58-e155-4482-93ce-84efff3c7c77",
            "domain":"ROOT",
            "apikey":"plgWJfZK4gyS3mOMTVmjUVg-X-jlWlnfaUJ9GAbBbf9EdM-kAYMmAiLqzzq1ElZLYq_u38zCm0bewzGUdP66mg",
            "secretkey":"VDaACYb0LV9eNjTetIOElcVQkvJck_J_QljX_FcHRj87ZKiy0z0ty0ZsYBkoXkY9b7eq1EhwJaw7FF3akA3KBQ",
            "accountid":"7548ac03-af1d-4c1c-9064-2f3e2c0eda0d"
         }
      ]
   }
}

All the clients that you will find on GitHub will implement this signature technique, you should not have to do it by hand. Now that you have explored the API through the UI and that you understand how to make low level calls, pick your favorite client of use CloudMonkey. CloudMonkey is a sub-project of Apache CloudStack and gives operators/developers the ability to use any of the API methods. It has nice auto-completion and help feature as well as an API discovery mechanism since 4.2.

Conclusions

CloudStack is a mostly Java application running with Jetty and Mysql. It consists of a management server and depending on the hypervisors being used, an agent installed on the hypervisor farm. To complete a Cloud infrastructure however you will also need some Zone wide storage a.k.a Secondary Storage and some Cluster wide storage a.k.a Primary storage. The choice of hypervisor, storage solution and type of Zone (i.e Basic vs. Advanced) will dictate how complex your installation can be. As a quick start, you might want to consider KVM+NFS and a Basic Zone.

If you’ve run into any problems with this, please ask on the cloudstack-dev mailing list.