To the Clouds: Why you should deploy to the cloud even if you don't want to
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| Title | To the Clouds: Why you should deploy to the cloud even if you don't want to |
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| Part Number | 33 |
| Number of Parts | 173 |
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| License | CC Attribution - NonCommercial - ShareAlike 3.0 Unported: You are free to use, adapt and copy, distribute and transmit the work or content in adapted or unchanged form for any legal and non-commercial purpose as long as the work is attributed to the author in the manner specified by the author or licensor and the work or content is shared also in adapted form only under the conditions of this license. |
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| Production Place | Bilbao, Euskadi, Spain |
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| Abstract | Michael Foord - To the Clouds: Why you should deploy to the cloud even if you don't want to
Do you deploy your Python services to Amazon EC2, or to Openstack, or
even to HP cloud, joyent or Azure? Do you want to - without being tied
into any one of them? What about local full stack deployments with lxc
or kvm containers?
Even if you're convinced you don't need "the cloud" because you manage
your own servers, amazing technologies like Private clouds and MaaS,
for dynamic server management on bare metal, may change your mind.
Fed up with the cloud hype? Let us rehabilitate the buzzword! (A bit anyway.)
A fully automated cloud deployment system is essential for rapid
scaling, but it's also invaluable for full stack testing on continuous
integration systems. Even better, your service deployment and
infrastructure can be managed with Python code? (Devops distilled)
Treat your servers as cattle not as pets, for service oriented
repeatable deployments on your choice of back-end. Learn how service
orchestration is a powerful new approach to deployment management, and
do it with Python! If any of this sounds interesting then Juju maybe
for you!
In this talk we'll see a demo deployment for a Django application and
related infrastructure. We'll be looking at the key benefits of cloud
deployments and how service orchestration is different from the
"machine provisioning" approach of most existing cloud deployment
solutions. |
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