// November 21st, 2011 // 1 Comment » // Uncategorized
The Ubuntu Developer Summit – UDS – is a major event in the Canonical calendar. Taking place every six months, it is the Ubuntu event which defines the focus and plans for our up-coming version of Ubuntu. In the first week of November, over 800 people, from Canonical engineers and employees, Ubuntu community members, partners, ISVs, upstreams and many more gathered to discuss and plan for the upcoming Ubuntu 12.04, code-named Precise Pangolin.
UDS covered 420 sessions, under nine tacks, from desktop to design, community to server and cloud. Attendees worked in the usual collaborative and open environment and spent the week pooling their experience and expertise and sharing best practise resulting, as always, in the very best ideas. Right now, those ideas are are represented in hundreds of blueprint documents and are being put into action by developers, community and Canonical, who are already driving forward for April’s launch. As a practical demonstration of that openness you can track our progress here (note, it’s early days!): http://status.ubuntu.com/ubuntu-precise/.
Focus on desktop and the cloud
Over the coming months, we’ll see much more of the fruits of UDS’ labour as new features are developed and collaborations and partnerships formed. Right now, the focus is on refinement, quality and stabilisation. As Ubuntu 12.04 will be a LTS release, which, for the first time, will be supported for five years, getting performance and stability right will be extremely important. For businesses, cloud is becoming ever more important, so we’ll be looking at building out a robust test infrastructure; there will be continued support for the latest releases of OpenStack and much effort will be put into improving Juju and developing the Charms collection.
For our desktop users, refinement of the interface is a continued focus and we’ll regularly run usability testing to make sure Ubuntu looks and feels great. For ubuntu 12.04, there will be a lot of developments for power users, including multi-monitor support, and improvements to boot speed, text-free boot and power consumption. And of course, the community centres around the developer programme, design, governance and loco teams. Engaging and embracing developers continues to be important (for free software) as we seek to bring new and exciting applications to the Ubuntu platform.
Our wonderful sponsors
We also wanted to take this opportunity to extend a special thank you to all of our sponsors who helped us accomplish this monumental task. Cloud Foundry, Rackspace, Google, System 76, Freescale, Nebula, as well as our media partners, Ubuntu User, Linux Pro Magazine, all attended and contributed to the success of UDS in different ways. Some gave plenary sessions;
Brian Thomason and Juan Negron – Cloudfoundry Server deployments using Juju
James Blair and Monty Taylor – Rackspace – Distributed QA in the OpenStack Project
It’s Linaro’s summit too
Also, for the second time, UDS was co-hosted with the Linaro Connect event, where the best software developers met to plan out and code the future of Linux on ARM. Canonical has been actively participating in the Linaro project since it began in 2010, and having both events run in parallel is a good opportunity to share new ideas and collaborate. ARM continues to gain more traction in traditional PC areas, such as the data center and Ubuntu continues to contribute to the enablement of ARM. You can hear more from David Brash’s Linaro plenary, An ARM Technology Update.
And a vision for what’s next
While the focus for Canonical and the Ubuntu community is firmly on the next launch , we’ve already started to think beyond this release. In Mark’s opening keynote, he talked of extending the Ubuntu mission; “‘Linux for Human Beings’ cannot end at the desktop, but needs to take into account the devices that will be used by human beings in the years to come….”. In the coming two years, we’ll start to see Ubuntu powering tablets, phones, TVs and smart screens from the car to the office kitchen, and it will connect those devices cleanly and seamlessly to the desktop, the server and the cloud. You can read more on Mark’s vision for the future of Ubuntu on his blog: or see the full keynote.
For lots more video and insight you can check out the excellent Ubuntu Developers Channel on YouTube
// November 16th, 2011 // 6 Comments » // Uncategorized
Updated 2013/04/17: Reflect Charm Store, updated links, removed several out of date paragraphs.
For the past three weeks I’ve been working with Charms, which are part of the Juju project. I love charms, I even went so far as to join the Charmers group on Launchpad. During the Ubuntu Developer Summit I was lucky enough to sit down with a few of the Juju hackers and get a first hand look at developing an deploying charms. There are lots of videos showing how quick and easy it is to deploy Hadoop, WordPress, and MySQL to the cloud but those demos always just kind of sailed over my head, because I didn’t really care about that kind of infrastructure.
So, you want to run a Minecraft server in the cloud. First you’ll need to grab juju – if you’re running the latest and greatest Ubuntu release then installation is a pretty straight forward process execute the following lines to add the Juju PPA and install Juju along with the additional charm tools.
Finally, we need to setup an environment for which to deploy these charms to! Run juju once to have Juju create it’s environments file, which is placed in ~/.juju/environments.yaml Since I use Amazon’s Web Services (AWS) EC2, all I had to do was add two extra keys one for access-key and the other secret-key. These are the access and secret keys (respectively) from your Amazon Web Service account. All of this can be found in the documentation
Now you’re ready for some charming!
There are a whole bunch of directions you can go in now. You can pull down all the charms in the Charm Browser, you can checkout the list of charms that are still in development/awaiting approval, or you can just deploy the totally awesome Minecraft charm. Lets do that! You’ll need to setup the cloud for deployment. This is done via bootstrapping, which will create an instance on the cloud that acts as the gatekeeper and manager for all services and charms you deploy with Juju to the cloud.
juju bootstrap
Bootstrapping can take up to five minutes to complete and it runs in the background. So even though the command completed doesn’t always mean the environment is ready! You can check on the Juju environment anytime by issuing the juju status command. Output, when bootstrapping is completed, will look like this
2011-11-1613:18:27,464 INFO Connecting to environment.
machines:
0: {dns-name: ec2-50-19-58-136.compute-1.amazonaws.com, instance-id: i-45bdd926}2011-11-1613:18:28,408 INFO 'status' command finished successfully
So we’ve got one machine (our bootstrap!) and it’s all ready to rock and roll. So, lets deploy!
juju deploy minecraft
When that command completes, it’ll send a request to the bootstrap machine to spin up a minecraft service (just so you know, charms that are deployed are called services). It’s almost ready to rock and roll! Check on the machine periodically using the juju status command, eventually you’ll end up with the following:
2011-11-1613:28:14,584 INFO Connecting to environment.
machines:
0: {dns-name: ec2-50-19-58-136.compute-1.amazonaws.com, instance-id: i-45bdd926}1: {dns-name: ec2-50-17-53-192.compute-1.amazonaws.com, instance-id: i-fdb8dc9e}
services:
minecraft:
charm: local:oneiric/minecraft-1
exposed: false
relations: {}
units:
minecraft/0:
machine: 1
open-ports:
public-address: ec2-50-17-53-192.compute-1.amazonaws.com
relations: {}
state: started
2011-11-1613:28:15,711 INFO 'status' command finished successfully
As is shown, there are two machines now, bootstrap and the newly created minecraft machine. We have one service running, minecraft, and a bunch of other information, most importantly the state and public-address. As is shown, the machine is started! So everything went A-OK! All that needs to happen now: Expose the server to the outside world. Exposing simply opens the appropriate ports for a service, if required. In this case we want our server to be available to the rest of the world so they can play! You can do this by running
juju expose minecraft
Running juju status one more time will show that the Minecraft service is now exposed and ready to rock and roll
Now, the machine is available on port 25565 (the default port!) Try to connect and this is what you get:
I would have written this post sooner, but I was too busy “testing”
Now, I know what you’re thinking. “But Marco, I want to configure the server, now I have to log in and configure it.” Nope! Juju Charms are configurable! To get a list of configuration options just run juju get minecraft which should produce the following list
2011-11-1613:31:06,718 INFO Connecting to environment.
charm: minecraft-1
service: minecraft
settings:
allow-nether:
description: Allow generation of the nether, true or false
type: string
value: 'True'
difficulty:
description: Level of complexity 1-5
type: int
value: 1
level-name:
description: Name of the level, will be generated if it doesn't exist
type: string
value: world
max-players:
description: Maximum players allowed on the server
type: int
value: 10
motd:
description: Message of the day displayed to users in the server list
type: string
value: Juju Powered Minecraft Server
port:
description: Port for which Minecraft runs upon
type: int
value: 25565
spawn-animals:
description: Generate animals, true or false
type: string
value: 'True'
spawn-monsters:
description: Generate monsters, true or false
type: string
value: 'True'
2011-11-1613:31:07,473 INFO 'config_get' command finished successfully
At this point you can update the configuration at any time using juju set minecraft option=value option2=value [...] an example to change the maximum players and the MOTD would be
juju set minecraft motd="Juju I love you" max-players=5
And in no time flat you’ll see something like this
That about sums up getting started with launching Minecraft in Juju. It may seem like a lot but the majority of this was a one time setup. This is also just the tip of the iceburg when it comes to charms and Juju. I strongly recommend checking out their site and asking questions in the #juju room on freenode.
// November 15th, 2011 // 6 Comments » // Uncategorized
This year’s Ubuntu Hardware Summit (UHS) will take place on December 8th at the Grand Victoria Hotel in Taipei. You can register your place at www.ubuntu.com.uhs
Building on the success of 2010 (with over 200 attendees), the 2011 Ubuntu Hardware Summit promises to deliver more. With keynote speeches from various members of the Canonical team and a more focused technical delivery, UHS is created especially for product managers and engineers at ODMs and OEMs, with interest or responsibility in deploying Ubuntu on new computers and devices.
Highlights will include presentations on Ubuntu Server, deploying Ubuntu Cloud, QA, power management, hardware enablement….and much more! Details of the event can also be found on the new Ubuntu Hardware Debugging website at http://odm.ubuntu.com/portal/
UHS is sponsored by Canonical and free of charge.
To reserve your space, visit www.ubuntu.com/uhs today as registrations will close on 29th November 2011.
Do you want to run short jobs on Amazon EC2 on a recurring schedule, but
don’t want to pay for an instance running all the time?
Would you like to do this using standard Amazon AWS services without
needing an external server to run and terminate the instance?
Amazon EC2 Auto Scaling is normally used to keep a
reasonable number of instances running to handle measured or expected
load (e.g., web site traffic, queue processing).
In this article I walk through the steps to create an Auto Scaling
configuration that runs an instance on a recurring schedule (e.g.,
four times a day) starting up a pre-defined task and letting that
instance shut itself down when it is finished. We tweak the Auto
Scaling group so that this uses the minumum cost in instance run time,
even though we may not be able to predict in advance exactly how long
it will take to complete the job.
Here’s a high level overview for folks familiar with Auto Scaling:
The instance is started using a recurring schedule action that
raises the min and max to 1.
The launch configuration is set to pass in a user-data script that
runs the desired job on first boot. There’s no need to build our
own AMI unless the software installation takes too long.
The user-data script runs shutdown at the end to move the instance
to the “stopped” state, suspending hourly run charges.
Another recurring schedule action lowers the min and max to 0.
This is done long after the job should have completed, just to
clean up the stopped instance or to terminate an instance that
perhaps failed to shut itself down. It also resets the min/max
count so a new instance will be started the next time they are
raised.
The missing key I found through experimentation is that we need to
also suspend Auto Scaling’s (usually valid) desire to replace any
unhealthy instances. If we don’t turn off this behavior, Auto Scaling
will start another instance as soon as the first one shuts itself
down, causing the job to be run over and over.
Prerequisites
The examples in this article assume that you have:
Installed and set up the EC2 command line tools
Installed and set up the EC2 Auto Scaling command line tools
The first step in setting up this process is to create a user-data
script that performs the tasks you want your scheduled
instance to execute each time it runs.
This user-data script can do anything you want as long as it runs this
command after all the work has beeen completed:
shutdown -h now
I have created a demo user-data script for this article
which you can download to your local computer now, saving it as
demo-user-data-script.sh
WARNING: Do not attempt to run this user-data script on your local computer!
Edit the downloaded demo-user-data-script.sh file and change this
line at the top of the script to reflect your email address:
EMAIL=youraddress@example.com
This demo user-data script:
Upgrades the Ubuntu instance
Installs Postfix with a generic configuration so that it can send email
Sends you a demo informative message about the instance at the
email address you edited in the script.
Sleeps for 5 minutes giving the email a chance to be delivered
Shuts down the EC2 instance
The first time you run this demo, try using the script as it stands,
only changing your email address. Then, try adjusting the script
little by little to make it do tasks that you would find more useful.
If you’d like, you can test the user-data script by itself running an
instance of Ubuntu 11.10. Please update the AMI id to use the latest
release:
You should see an email from the instance and then it should terminate
itself about 5 minutes later. Make sure you terminate it manually if
it stays running after 10 minutes.
Auto Scaling Group
With the user-data script in hand, we are now ready to create the Auto
Scaling setup.
Set some variables used in the commands below. Make sure you are
using the latest release of the appropriate AMI.
ami_id=ami-a7f539ce # Ubuntu 11.10 Oneiric server region=us-east-1 # Region for running the demo zone=${region}a # A zone in that region export EC2_URL=https://$region.ec2.amazonaws.com export AWS_AUTO_SCALING_URL=https://autoscaling.$region.amazonaws.com launch_config=demo-launch-config auto_scale_group=demo-auto-scale-group
This lauch configuration describes how we want our instance run each
time including the AMI id, instance type, ssh key, and most
importantly, our user-data script we edited above:
The Auto Scaling group keeps track of many things including how many
instances we want to have running, how they should be run (launch
config above), and what instances are currently running.
Here’s a non-obvious but key part of this approach! Tell the Auto
Scaling group that we don’t want it to restart our instance right
after the instance intentionally shuts down (or fails):
Now we’re finally ready to tell EC2 Auto Scaling when we want to run
the instance launch configuration in the Auto Scaling group.
Here’s an example that starts one instance four times a day to run the
above user-data script:
And, we need to create a matching action to make sure the instance is
terminated at some point after the longest time the job could take. For
this demo, we’ll trigger it 55 minutes later, but it could just as
easily be 3 hours and 55 minutes later:
The recurrence value is in a cron format using UTC.
You are welcome to change the specs in the above commands to any time
you want to run the demo, especially if you don’t want to wait up to
six hours for it to trigger.
Before setting new schedules, make sure you delete the existing
schedule (see the next section). Don’t forget to make the stop
time(s) match up appropriately with the start time(s).
Clean up
Once you’re done with this demo, you can delete the AWS resources we
created by following these steps:
Delete the schedule start and stop actions:
Everything takes a little time to filter through the system including:
scheduled action to raise min/max
triggering the start of an instance after a min/max is raised
starting an instance
booting an instance, installing software
running your job
shutting down an instance
scheduled action to lower min/max
triggering the termination of an instance after a min/max is lowered
When you set up the schedules, remember to make room for these
things. For example, don’t schedule the termination of your instance
too early or it could kill your job before it has a chance to
complete.
Notes
Here are some great resources from Amazon for getting started with
and learning about Auto Scaling:
Watching the output of the user-data script lets you monitor its
progress as well as debug where things might be going wrong.
I haven’t run the above approach except in testing, and would welcome
any pointers or improvements folks might have to offer.
Original article:
http://alestic.com/2011/11/ec2-schedule-instance
// November 15th, 2011 // 2 Comments » // Uncategorized
I’m always interested in what’s happening at Canonical and with Ubuntu. Last week at Hadoop World I ran into a couple of folks from the company (coincidentally both named Mark but neither Mr. Shuttleworth). Mark Mims from the server team was willing to chat so I grabbed some time with him to learn about what he was doing at Hadoop World and what in the heck is this “charming” Juju?
Some of the ground Mark covers
Making the next version of Ubuntu server better for Hadoop and big data
(0:34) What are “charms” and what do they have to do with service orchestration
(2:05) Charm school and learning to write Juju charms
(2:54) Where does “Orchestra” fit in and how can it be used to spin up OpenStack
(3:40) What’s next for Juju
But wait, there’s more!
Stay tuned for more interviews from last week’s Hadoop world. On tap are:
// November 14th, 2011 // Comments Off // Uncategorized
Last week saw the delivery of the first milestone of the Essex development cycle for Keystone, Glance, Horizon and Nova. This early milestone collected about two months of post-Diablo work… but it’s not as busy in new features as most would think, since a big part of those last two months was spent releasing OpenStack 2011.3 and brainstorming Essex features.
Glance developers were busy preparing significant changes that will land in the next milestone. Several bugfixes and a few features made it to essex-1 though, including the long-awaited SSL client connections. It also moved to UUID image identifiers.
// November 8th, 2011 // Comments Off // Uncategorized
I’ve been playing with juju for a few months now in different contexts and I’ve really enjoyed the ease with which it allows me to think about services rather than resources.
More recently I’ve started thinking about best-practices for deploying services using juju, while still using puppet to setup individual units. As a simple experiment, I wrote a juju charm to deploy an irssi service [1] to dig around. Here’s what I’ve found so far [2]. The first is kind of obvious, but worth mentioning:
Normally the corresponding manifest (see initial_state.pp) would be a little more complicated, but in this example it’s hardly worth mentioning.
Juju config changes can utilise Puppet’s Facter infrastructure:
This enables juju config options to be passed through to puppet, so that config-changed hooks can be equally simple:
#!/bin/bash
juju-log "Getting config options"
username=`config-get username`
public_key=`config-get public_key`
juju-log "Configuring irssi for user"
# We specify custom facts so that they're accessible in the manifest.
FACTER_username=$username FACTER_public_key=$public_key puppet apply $PWD/hooks/configured_state.pp
In this example, it is the configured state manifest that is more interesting (see configured_state.pp). It adds the user to the system, sets up byobu with an irssi window ready to go, and adds the given public ssh key enabling the user to login.
The same would go for other juju hooks (db-relation-changed etc.), which is quite neat – getting the best of both worlds: the charm user can still think in terms of deploying services, while the charm author can use puppets declarative syntax to define the machine states.
Next up: I hope to experiment with an optional puppet master for a real project (something simple like the Ubuntu App directory), so that
a project can be deployed without the (probably private) puppet-master to create a close-to-production environment, while
configuring a puppet-master in the juju config would enable production deploys (or deploys of exact replicas of production to a separate environment for testing).
If you’re interested in seeing the simple irssi charm, the following 2min video demos:
# Deploy an irssi service
$ juju deploy --repository=/home/ubuntu/mycharms local:oneiric/irssi
# Configure it so a user can login
$ juju set irssi username=michael public_key=AAAA...
# Login to find irssi already up and running in a byobu window
$ ssh michael@new.ip.address
[1] Yes, irssi is not particularly useful as a juju service (as I don’t want multiple units, or relating it to other services etc.), but it suited my purposes for a simple experiment that also automates something I can use for working in the cloud.
[2] I’m not a puppet or juju expert, so if you’ve got any comments or improvements, don’t hesitate.
// November 8th, 2011 // Comments Off // Uncategorized
A while back I started experimenting with Juju and was intrigued by the notion of services instead of machines.
A bit of background on Juju from their website:
Formerly called Ensemble, juju is DevOps DistilledTM. Through the use of charms(renamed from formulas), juju provides you with shareable, re-usable, and repeatable expressions of DevOps best practices. You can use them unmodified, or easily change and connect them to fit your needs. Deploying a charm is similar to installing a package on Ubuntu: ask for it and it’s there, remove it and it’s completely gone.
I come from a DevOps background and know first hand the troubles and tribulations of deploying production services, webapps, etc. One that's particularly "thorny" is hadoop.
To deploy a hadoop cluster, we would need to download the dependencies ( java, etc. ), download hadoop, configure it and deploy it. This process is somewhat different depending on the type of node that you're deploying ( ie: namenode, job-tracker, etc. ). This is a multi-step process that requires too much human intervention. It is also a process that is difficult to automate and reproduce. Imagine 10, 20 or 50 node cluster using this method. It can get frustrating quickly and it is prone to mistake.
With this experience in mind ( and a lot of reading ), I set out to deploy a hadoop cluster using an Juju charm.
First things first, let's install Juju. Follow the Getting Started documentation on the Juju site here.
According to the Juju documenation, we just need to follow some file naming conventions for what they call "hooks" ( executable scripts in your language of choice that perform certain actions ). These "hooks" control the installation, relationships, start, stop, etc of your charm. We also need to summarize the description of the formula in a file called metadata.yaml. The metadata.yaml file describes the formula, it's interfaces, what it requires and provides among other things. More on this file later when I show you the one for hadoop-master and hadoop-slave.
Armed with a bit of knowledge and a desire for simplicity, I decided to split the hadoop cluster in two:
hadoop-master (namenode and jobtracker )
hadoop-slave ( datanode and tasktracker )
I know this is not an all-encompassing list but, this will take care of a good portion of deployments and, the Juju charms are easy enough to modify that you can work your changes into them.
One of my colleagues, Brian Thomason did a lot of packaging for these charms so, my job is now easier. The configuration for the packages has been distilled down to three questions:
namenode ( leave blank if you are the namenode )
jobtracker ( leave blank if you are the jobtracker )
hdfs data directory ( leave blank to use the default: /var/lib/hadoop-0.20/dfs/data )
Due to the magic of Ubuntu packaging, we can even "preseed" the answers to those questions to avoid being asked about them ( and stopping the otherwise automatic process ). We'll use the utility debconf-set-selections for this. Here is a piece of the code that I use to preseed the values in my charm:
Thanks to Brian's work, I now just have to install the packages ( hadoop-0.20-namenode and hadoop-0.20-jobtracker). Let's put all of this together into a Juju charm.
Create a directory for the hadoop-master formula ( mkdir hadoop-master )
Make a directory for the hooks of this charm ( mkdir hadoop-master/hooks )
Let's start with the always needed metadata.yaml file ( hadoop-master/metadata.yaml ):
ensemble: formula
name: hadoop-master
revision: 1
summary: Master Node for Hadoop
description: |
The Hadoop Distributed Filesystem (HDFS) requires one unique server, the
namenode, which manages the block locations of files on the
filesystem. The jobtracker is a central service which is responsible
for managing the tasktracker services running on all nodes in a
Hadoop Cluster. The jobtracker allocates work to the tasktracker
nearest to the data with an available work slot.
provides:
hadoop-master:
interface: hadoop-master
Every Juju charm has an install script ( in our case: hadoop-master/hooks/install ). This is an executable file in your language of choice that Juju will run when it's time to install your charm. Anything and everything that needs to happen for your charm to install, needs to be inside of that file. Let's take a look at the install script of hadoop-master:
#!/bin/bash
# Here do anything needed to install the service
# i.e. apt-get install -y foo or bzr branch http://myserver/mycode /srv/webroot
There a few other files that we need to create ( start and stop ) to get the hadoop-master charm installed. Let's see those files:
start
#!/bin/bash
# Here put anything that is needed to start the service.
# Note that currently this is run directly after install
# i.e. 'service apache2 start'
set -x
service hadoop-0.20-namenode status && service hadoop-0.20-namenode restart || service hadoop-0.20-namenode start
service hadoop-0.20-jobtracker status && service hadoop-0.20-jobtracker restart || service hadoop-0.20-jobtracker start
stop
#!/bin/bash
# This will be run when the service is being torn down, allowing you to disable
# it in various ways..
# For example, if your web app uses a text file to signal to the load balancer
# that it is live... you could remove it and sleep for a bit to allow the load
# balancer to stop sending traffic.
# rm /srv/webroot/server-live.txt && sleep 30
set -x
juju-log "stop script"
service hadoop-0.20-namenode stop
service hadoop-0.20-jobtracker stop
Let's go back to the metadata.yaml file and examin it in more detail:
ensemble: formula
name: hadoop-master
revision: 1
summary: Master Node for Hadoop
description: |
The Hadoop Distributed Filesystem (HDFS) requires one unique server, the
namenode, which manages the block locations of files on the
filesystem. The jobtracker is a central service which is responsible
for managing the tasktracker services running on all nodes in a
Hadoop Cluster. The jobtracker allocates work to the tasktracker
nearest to the data with an available work slot.
provides:
hadoop-master:
interface: hadoop-master
The emphasized section ( provides ) tells juju that this formula provides an interface named hadoop-master that can be used in relationships with other charms ( in our case we'll be using it to connect the hadoop-master with the hadoop-slave charm that we'll be writing a bit later ). For this relationship to work, we need to let Juju know what to do ( More detailed information about relationships in charms can be found here ).
Per the Juju documentation, we need to name our relationship hooks hadoop-master-relation-joined and it should also be an executable script in your language of choice. Let's see what that file looks like:
#!/bin/sh
# This must be renamed to the name of the relation. The goal here is to
# affect any change needed by relationships being formed
# This script should be idempotent.
set -x
juju-log "joined script started"
# Calculate our IP Address
IP_ADDRESS=`unit-get private-address`
# Preseed our Namenode, Jobtracker and HDFS Data directory
juju add-relation hadoop-slave hadoop-master # ( connects the hadoop-slave to the hadoop-master )
As you can see, once you have the charm written and tested, deploying the cluster is really a matter of a few commands. The above example gives you one hadoop-master ( namenode, jobtracker ) and one hadoop-slave ( datanode, tasktracker ).
To add another node to this existing hadoop cluster, we add:
juju add-unit hadoop-slave # ( this adds one more slave )
Run the above command multiple times to continue to add hadoop-slave nodes to your cluster.
Juju allows you to catalog the steps needed to get your service/application installed, configured and running properly. Once your knowledge has been captured in an Juju charm, it can be re-used by you or others without much knowledge of what's needed to get the application/service running.
In the DevOps world, this code re-usability can save time, effort and money by providing self contained charms that provide a service or application.
// November 5th, 2011 // 2 Comments » // Uncategorized
It’s late, I’m tired, so this is going to be brief. But if I didn’t put something up now, chances are I’d procrastinate to the point where it didn’t matter anymore, so something is better than nothing.
JuJu
So the buzz all week was about Juju and Charms. It’s a very cool technology that I think is really going to highlight the potential of cloud computing. Until now I always had people comparing the cloud to virtual machines, telling me they already automate deploying VMs, but with Juju you don’t think about machines anymore, virtual of otherwise. It’s all about services, which is really what you want, a service that is doing something for you. You don’t need to care where, or on what, or in combination with some other thing, Juju handles all that automatically. It’s really neat, and I’m looking forward to using it more.
Summit
Summit worked this week. In fact, this is the first time in my memory where there wasn’t a problem with the code during UDS. And that’s not because we left it alone either. IS actually moved the entire site to a new server the day before UDS started. We landed several fixes during the week to fix minor inconveniences experienced by IS or the admins. And that’s not even taking into consideration all the last-minute features that were added by our Linaro developers the week prior. But through it all, Summit kept working. That, more than anything else, is testament to the work the Summit developers put in over the last cycle to improve the code quality and development processes, and I am very, very proud that. But we’re not taking a break this cycle. In fact, we had two separate sessions this week about ways to improve the user experience, and will be joined by some professional designers to help us towards that goal.
Ubuntu One eBook syncing
So what started off as an casual question to Stuart Langridge turned into a full blown session about how to sync ebook data using Ubuntu One. We brainstormed several options of what we can sync, including reading position, bookmarks, highlights and notes, as well as ways to sync them in an application agnostic manner. I missed the session on the upcoming Ubuntu One Database (U1DB), but we settled on that being the ideal way of handling this project, and that this project was an ideal test case for the U1DB. For reasons I still can’t explain, I volunteered to develop this functionality, at some point during the next cycle. It’s certainly going to be a learning experience.
Friends
Friends! It sure was good to catch up with all of you. Both friends from far-away lands, and those closer to home. Even though we chat on IRC almost constantly, there’s still nothing quite like being face to face. I greatly enjoyed working in the same room with the Canonical ISD team, which has some of the smartest people I’ve ever had the pleasure of working with. It was also wonderful to catch up with all my friends from the community. I don’t know of any other product or project that brings people together the way Ubuntu does, and I’m amazed and overjoyed that I get to be a part of it.
// November 4th, 2011 // 2 Comments » // Uncategorized
If you’ve been doing anything with Ubuntu lately, chances are you’ve been hearing a lot of buzz about Juju. If you’re attending UDS, then there’s also a good chance that you’ve been to one or more sessions about Juju. But do you know it?
The building blocks for Juju are it’s “charms”, which detail exactly how to deploy and configure services in the Cloud. Writing charms is how you harness the awesome power of Juju. Tomorrow (Friday) there will be a 2 hour session all about writing charms, everything from what they do and how they work, to helping you get started writing your own. Questions will be answers, minds will be inspired, things will be made, so don’t miss out.
