Cloud

Creating and Deploying a private catalog on the Rancher Platform

With the announcement of private catalog support in the Rancher platform we decided to create a custom catalog for our application stack.

If you are looking for a complete overview and step by step on how to create a private catalog the best place is the January online meetup Building a Docker Application Catalog

In the post I'll guide you through the steps I took to create a catalog for our application, the Aytra Cloud.

The main concepts behind a Catalog on Rancher are

  • Expose docker and rancher compose frameworks to define a catalog blueprint
  • Store templates on git repo
  • Allow configuration and deployment of stacks
  • Support versioning and upgrades

Creating the Catalog file structure

So in a nutshell you will need to have a git repo with the following directory structure

In the config.yml file you can define the basic configuration for you catalog, eg;

name: Aytra  
description: |  
  Aytra Cloud enables our customers to fully realize the potential of cloud computing by allowing them to automatically migrate application workloads across public and private clouds to achieve an ideal balance of security, cost, and performance.
version: 7.5  
category: "Cloud Management Platform"  

To define different versions of the same catalog Rancher uses the concept of numbered directories containing different versions of a docker-compose and rancher-compose templates.

One point to note about the rancher-compose file is that a .catalog section must be defined as well as a questions attribute, for example:

.catalog:
  name: Aytra
  version: 7.5
  description: |
    Aytra Cloud enables our customers to fully realize the potential of cloud computing by allowing them to automatically migrate application workloads across public and private clouds to achieve an ideal balance of security, cost, and performance.
  uuid: aytra-0
  questions:
    - variable: "exo-scale"
      description: "Number of exosphere nodes."
      label: "Number of Exosphere Nodes:"
      required: true
      default: 1
      type: "int"

Adding the Catalog to Rancher

Now with all the catalog file structure defined you can add your private git repo to Rancher under the Admin -> Settings tab.

A couple of tweaks you need to make to enable private git repos:

1. Add the username and password of your git user in the git url: https://username:password@bitbucket.org/org/catalogs.git

2. Bind-mount ssh keys for your git repo in the rancher server container. This approach will work after v056 is released since currently the server container doesn't come with with the openssh binaries installed

Ideally you would be able to configure git users similar to how Jenkins git plugins do it but is not supported at the time.

Viewing the Catalog

The rancher catalog service has a mechanism that polls periodically the git repo for new changes to keep the catalogs up to date. So right after adding the git repo to Rancher you should see your catalog listed under the Applications -> Catalogs menu

Launching the Catalog

Now you should be able to launch your application catalog and get a running stack with your micro services

OpenStack High Availability Features

Until the moment we have been researching possible solutions to make an OpenStack Cloud deployment have as much high availability features as possible.

Before the Folsom release H.A features were not built in the OpenStack service components.
With a large number of requests from the OpenStack community, starting with the Folsom release H.A is being addressed as part of the project. The features are still being introduced and in test phase, there aren’t a lot of production deployments out there yet, but with the help and feedback of the community the OpenStack developers believe that by the time the next version is release (Grizzly) OpenStack H.A features will be automated and ready to get in production mode from the get go.

Getting into the details of the H.A features available in Folsom:
Instead of reinventing the wheel, OpenStack decided to go with a proven and robust H.A provider available in the market: Pacemaker was their choice. With more than half a decade of production deployments, Pacemaker is a proven solution when it comes to providing H.A features to a vast range of services.

Specifically looking at the technologies involved with OpenStack, the role of H.A would be to prevent:

  • System downtime — the unavailability of a user-facing service beyond a specified maximum amount of time, and
  • Data loss — the accidental deletion or destruction of data.

In the end the focus is to eliminate Single Points of Failures in the cluster architecture.
A few examples:

  • Redundancy of network components, such as switches and routers,
  • Redundancy of applications and automatic service migration,
  • Redundancy of storage components,
  • Redundancy of facility services such as power, air conditioning, fire protection, and others.

Pacemaker relies on the Corosync project for reliable cluster communications. Corosync implements the Totem single-ring ordering and membership protocol and provides UDP and InfiniBand based messaging, quorum, and cluster membership to Pacemaker.

An OpenStack high-availability configuration uses existing native Pacemaker RAs (such as those managing MySQL databases or virtual IP addresses), existing third-party RAs (such as for RabbitMQ), and native OpenStack RAs (such as those managing the OpenStack Identity and Image Services).

Even though high availability features exist for native OpenStack components and external services they are not automated in the project yet so there is a need for manual installation and configuration of whatever H.A features are needed in the cloud deployment

A quick summary of how a Pacemaker setup would look is:
pacemaker-cluster

PaceMaker creates a cluster of nodes and uses Corosync to establish a communication between them.

Besides working with RabbitMQ, Pacemaker can also bring H.A features to a MySQL cluster, the steps would be:

  • configuring a DRBD (Distributed Replicated Block Device) device for use by MySQL,
  • configuring MySQL to use a data directory residing on that DRBD device,
  • selecting and assigning a virtual IP address (VIP) that can freely float between cluster nodes,
  • configuring MySQL to listen on that IP address,
  • managing all resources, including the MySQL daemon itself, with the Pacemaker cluster manager.

More information can be found:
DRBD
RabbitMQ
Towards a highly available (HA) open cloud: an introduction to production OpenStack
Stone-IT
Corosync

OpenStack Overview

Recently we started moving away from our original setup plan that was to have an OpenNebula cloud running on CentOS boxes, to an OpenStack Cloud running on Ubuntu boxes.

I’ll try to give a quick overview of what is OpenStack and talk a little bit about some of its main components.

Before I get started, I really like this diagram that demonstrates what problem OpenStack is trying to solve.

This is a basic diagram demonstrating the basic usage/need of a cloud platform.
OpenStack works on all levels of the cloud set up, from the low level libraries that interact with the HyperVisors to the Web Dashboard that allows users to interact with the cloud.
In the end OpenStack aggregates different solutions to offer a simple way to build public and private cloud platforms.

Some OpenStack history

Back in 2010 NASA and RacKSpace started the OpenStack Cloud project with the goal of having an open standard for both hardware and software cloud solutions.
Currently there are more than 150 companies involved with the project, such as Intel, IBM, Cisco and HP to name a few.

As far as activity, OpenStack seems to be very active with two major releases per year.
Their release history:

  1. Austin 21 October 2010
  2. Bexar 3 February 2011
  3. Cactus 15 April 2011
  4. Diablo 22 September 2011
  5. Essex 5 April 2012
  6. Folsom 27 September 2012
  7. Grizzly 4 April 2013

OpenStack is divided into three different categories:

Computing

  • Nova – OpenStack Compute
  • Glance – OpenStack Image Service

Storage

  • Swift – OpenStack Object Storage
  • Cinder – OpenStack Block Storage

Common Projects

  • Keystone – OpenStack Identity
  • Horizon – OpenStack Dashboard

Network

  • Quantum – OpenStack Networking

Now lets took into more details on the components listed above:

Nova – Compute

Nova can be summarized as a cloud controller.
It centralizes the management of a cloud and communicates between all different components, a good diagram that illustrate its role:

The main components of Nova are:

  1. API server: handles requests from the user and relays them to the cloud controller.
  2. Cloud controller: handles the communication between the compute nodes, the networking controllers, the API server and the scheduler.
  3. Scheduler: selects a host to run a command.
  4. Compute worker: manages computing instances: launch/terminate instance, attach/detach volumes
  5. Network controller: manages networking resources: allocate fixed IP addresses, configure VLANs

List of features:

  • Manage virtualized commodity server resources
  • Manage Local Area Networks (LAN)
  • API with rate limiting and authentication
  • Distributed and asynchronous architecture
  • Virtual Machine (VM) image management
  • Live VM management
  • Floating IP addresses
  • Security Groups
  • Role Based Access Control (RBAC)
  • Projects & Quotas
  • VNC Proxy through web browser
  • Store and Manage files programmatically via API
  • Least privileged access design
  • Dashboard with fully integrated support for self-service provisioning
  • VM Image Caching on compute nodes

Glance – Image Service

Glance takes care of managing virtual machine images.
Some of its functionality:

  • List Available Images
  • Retrieve Image Metadata
  • Retrieve Raw Image Data
  • Add a New Image
  • Update an Image
  • List Image Memberships
  • List Shared Images
  • Add a Member to an Image
  • Remove a Member from an Image
  • Replace a Membership List for an Image

Glance is only responsible for creating and managing virtual machine images, the deployment and maintenance of the VMs is taken care by Nova

Swift – Object Storage

The Swift  component is a Container/Object storage system.
Different from SAN and NAS file systems, Swift cannot be mounted, since it is not a file system itself.
You can think of Swift as a distributed storage system for static data, such as images, videos, archive data, etc
All the files are exposed through an HTTP interface, typically with a REST API

A good analogy is to think of Containers as folders as in a regular OS such as Windows
Objects are chunks of data living inside containers.
So when you upload a picture to Swift it will be wrapped in an Object and placed inside a container.
The object can contain some metadata in the form of key value pairs.
No encryption or compression is performed on objects upon storage.
List of features:

  • Leverages commodity hardware
  • HDD/node failure agnostic
  • Unlimited storage
  • Multi-dimensional scalability (scale out architecture)
  • Account/Container/Object structure
  • Built-in replication
  • Easily add capacity unlike RAID resize
  • No central database
  • RAID not required
  • Built-in management utilities
  • Drive auditing
  • Expiring objects
  • Direct object access
  • Realtime visibility into client requests
  • Supports S3 API
  • Restrict containers per account
  • Support for NetApp, Nexenta, SolidFire
  • Snapshot and backup API for block volumes
  • Standalone volume API available
  • Integration with Compute

Keystone – Identity

To summarize what Keystone does in one sentence:

keep track of users and what they are permitted to do

Keystone handles the user management of the cloud system, allowing different permissions to be configured for different users.
One of the keywords they use when talking about Keystone is Tenants.
Their explanation of tenants is something that can be thought of as a project, group, or organization

A diagram demonstrating the basic flow of Keystone:

Horizon – Dashboard

Horizon is the web interface available for OpenStack,  it’s very much like what OpenStone is for OpenNebula.

Quantum – Networking

Quantum is a new addition to OpenStack.
Up to the Essex release Quantum was built in the Nova component. However to provide more functionality in terms of network management Quantum was created with the focus on managing a network of an OpenStack solution

Conclusion

After all that being said, based on the image from the beginning of the blog post, we can have a better idea of where the OpenStack components fit in the overall cloud set up:

openstack-logical-arch-folsom

Thoughts

From somebody who is just getting started with cloud computing I would say that between OpenNebula and OpenStack the later is a better option. Even though OpenNebula is an older project OpenStack seems more mature.
A few things I noticed:
There is a lot more uptodate information about OpenStack, plus it is very easy to navigate through their website and find information about the different solutions they provide.
The community appears to be a lot more active with OpenStack than with OpenNebula.
Maybe it is just me, but after a few minute reading about OpenStack I was lead to their official repo on github where all the related projects are hosted.
I really like that since it is an easy way to stay in close touch with the project and follow the latest additions, plus it provides a channel of communication between the users and the developer and makes a lot easier for people to contribute back to the project.
I didn’t have the same feeling when it came to OpenNebula, the project didn’t feel as open as OpenStack, I felt there were a lot more hurdles to get started with OpenNebula.

Talking strictly technical it’s hard for me to say which one is better.
Reading about them both I could definitely see a lot of areas where they overlap, for example, they both use noVnc for the visualization of VMs and libvirt to communicate with the hypervisors.
They both have a web interface to manage the cloud and they both have options to configure VM templates.

A big difference is that OpenNebula is written in ruby while OpenStack is in python
And I’m sure they must differ in other architectural decisions as well, but for the most part they are very similar

For more information about OpenStack:
OpenStack wiki
Keystone basic concepts
Underlying technologies
Architecture overview
Documentation
OpenStack Storage
Very good blog about python & openstack
OpenStack Wikipedia
RackSpace Wikipedia
AMQP