This document discusses the opportunities offered by Google Cloud Platform (GCP). It describes how infrastructure provisioning, software deployment, outages, and scaling were challenging prior to cloud computing. GCP provides capabilities like auto-scaling, load balancing, monitoring and self-healing that address these issues. It also offers serverless architectures, containers, machine learning APIs, and tools to automate infrastructure that improve agility, performance and costs. While some concerns about cloud adoption include security, lock-in and speed, the document argues GCP addresses these through encryption, open standards and massive parallelism.

1. La nube como ventaja competitiva.
Un repaso a las oportunidades que ofrece
Google Cloud Platform
javier ramirez - @supercoco9
https://teowaki.com

2. how we developed and
deployed software in the 90s

3. Adding a new server:
* call (using a landline) or send a fax to
the provider
* pay via bank transfer
* wait for a few days/weeks
* set up the server on your own server
room
* hope it won't break

4. deploying software:
* code locally on your OS
* submit to CVS and manually build
* send package and SQL separately to IT
* wait until the time slot they give you
(next week, probably)
* test (by hand) everything is working
* hope it won't break

5. HOPE
IS NOT
A STRATEGY

6. systems & development

7. A platform with interesting
systems and development
tools

8. Infraestructura como servicio:
C mo dej deó é
preocuparme por
el hardware
y su complicada log sticaí

9. Provisioning infrastructure: AppEngine
“Zero ops” applications. Just deploy
and forget*
Of course you still need to worry about
monitoring, backups, security.. but
infrastructure and scaling are automatic
*you need to adjust to the sandbox

12. Provisioning infrastructure:
Compute Engine
Virtual Machines. Total freedom to do as
you wish.
Powerful networking. Networks,
subnetworks, VPNs, forwarding rules,
routes...

17. Cuatro cosas imposibles antes de la
merienda
* Mi servicio siempre disponible,
aunque un volc n est escupiendo datos sobre miá é
centro de datos
* Sobrevivir al black friday, la superbowl o el brexit
* Acabar el trabajo de una semana en 20 minutos
* Consultar “toda la informaci n del mundo” en 5 segundosó

20. A squirrel did take out half of our
Santa Clara data centre two years back
Mike Christian, Yahoo Director of Engineering

22. Hayastan
Shakarian
a.k.a.
The Spade
Hacker

23. Cut-off
Armenia
from
the Internet
for almost
one day*
* By accident, while scavenging copper

24. Some data center outages reported in 2015:
* Amazon Web Services
* Apple iCloud
* Microsoft Azure
* IBM Softlayer
* Google Cloud Platform
* And of course every hosting with scheduled
maintenance operations (rackspace, digital
ocean, ovh...)

25. Complex systems can and will fail

27. Self-healing

28. Self-healing

29. Auto scaling.
* Sobrevivir al black friday, la superbowl o el brexit
Add auto-scaling capabilities depending
on
* CPU usage
* Requests
* Your own custom metrics

30. When self-healing
and auto-scaling are
not enough

31. With http/https global load balancing
https://www.youtube.com/watch?v=HGdKHqMTAko

32. * Acabar el trabajo de una semana en 20 minutos

34. * 7 horas de 16 CPUs procesando sin parar
despu s...é

35. Each second of screen time would require 5,000 processor hours to
realize. Given the nature of the deadlines, our teams needed the
ability to spike to 15,000 cores simultaneously on-demand just to stay
on schedule. And because we don’t realize profits until the end of the
project, we needed to spend as little as possible to get up and
running.

37. * Consultar “toda la informaci n del mundo”ó
en 5 segundos

39. Google BigQuery

41. A nadie le gusta tener que despertarse a las cinco de la
ma ana para reiniciar un servidor porque sus clientesñ
est n sin servicio: monitorizaci n, alertas, y sistemasá ó
auto-reparables.

42. Monitoring

43. Alerts

44. Performance analysis

45. Performance analysis

46. tendencias en nube:
* Machine Learning
* Contenedores
* Arquitectura sin servidores

47. Machine Learning
* Train first
* Ask later
* or use a pre-trained model
- google Vision API
- google Speech API
- google Translate API
- google Prediction API
http://www.pivothead.com/build/
https://www.youtube.com/watch?time_continue=119&v=eve8DkkVdhI

48. Container Engine. Managed
kubernetes clusters

49. Container Engine. Managed load
balanced kubernetes clusters

50. Container Engine. Managed
load balanced, self healing,
auto scaling kubernetes clusters

51. Container Engine. Managed
kubernetes clusters

52. Automate all the things.
Cloud Deployment Manager

53. Automate all the things.
Cloud Deployment Manager

56. Serverless architectures

57. Why not the cloud
It's too slow
I am limited in what I can do
I will get vendor lock-in
I cannot legally host my data in the cloud
Google will spy on my data

58. Google will spy on my data
* GCP is not Gmail. SLA
* Encryption at rest and in transit
* Bring your own keys
* ISO standards

59. Cannot host my
data on the cloud
public/private hybrid clouds
Cloud carrier interconnect,
direct peering and
CDN interconnect

60. it's too slow
but it's massively
parallel

61. Vendor Lock-in:
Open source
(Kubernetes, google
dataflow...)

62. Vendor Lock-in:
terraform for
infrastructure
as code

63. Vendor Lock-in
spinnaker for multi-
cloud immutable
infrastructure and
deployments

64. Limited in what I can do

66. Limited in what I can do

67. Serial
port
output

68. Serial
port
output

69. A platform with interesting
tools. Try it maybe?

70. Gracias!
javier ramirez - @supercoco9
https://teowaki.com