This talk, a case study in application deployment models, was given at IBM InterConnect 2017 in Las Vegas, NV on March 21, 2017 by Lin Sun & Phil Estes of IBM Cloud. In this talk, Lin & Phil provided a background of IBM Bluemix compute offerings across Cloud Foundry, Containers + Kubernetes, and FaaS/serverless via OpenWhisk and then used a demo application to describe the tradeoffs between using the various deployment models and technology. The application is open source and available at https://github.com/estesp/flightassist

1. InterConnect
2017
Containerize, PaaS or Go
Serverless?
Phil Estes @estesp
Lin Sun @linsun_unc
A Case Study in Application
Deployment Models
1

2. Application Deployment Models:
A Brief Overview
2

3. Your compute options
in the post VM world
can be confusing.
PaaS (Cloud Foundry) <
Containers <
[Orchestration] <
FaaS/“Serverless” <
3

4. 4
Cloud Foundry Overview

5. 5
IBM is leading 3 projects,
has 2 in incubation &
contributes to 10 overall
IBM has been the #2
contributor since the
community was established,
behind only Pivotal.
Clouds
Services
Buildpacks
Bluemix PaaS Leverages Cloud Foundry
> Continuing IBM’s history of embracing Open Source

6. 6
Bluemix Cloud Foundry Quick Start
> A range of sophisticated programming language & quick start boilerplates:

7. 7
Fast, lightweight, isolated application containers
“Docker containers spin up fast and provide a layer of isolation from other services running in containers.”
“The lightweight containers can spin up in a matter of seconds without consuming a lot of resources.”
Containers: Based on Docker

8. 8
Read-only template used to create Docker containers
Build new images by modifying existing images
Find and share images on a registry (Docker Hub)
Containers: Images

9. 9
Beta available March 20th.
Combining Docker and Kubernetes to deliver powerful tools,
an intuitive user experience, and built-in security and isolation
to enable rapid delivery of applications - all while leveraging
IBM Cloud Services including cognitive capabilities from
Watson.
www.ibm.com/cloud-computing/bluemix/containers
IBM Bluemix Container Service

10. 10
Intelligent Scheduling Automated rollouts and rollbacks Container Security & PrivacyDesign Your Own Cluster
Self-healing Horizontal scaling Leverages IBM Cloud & Watson Integrated Operational Tools
S
M
L
Service discovery & load balancing Secret & configuration management Simplified Cluster Management Native Kubernetes Experience
IBM Bluemix Container Service

11. New Section

12. New Section

13. 13
+ =
www.ibm.com/cloud-computing/bluemix/containers
IBM Bluemix
Container Service

14. 14
Commonly referred to as “serverless” computing, the function/event-oriented
computing model takes focus away from deploying application components onto
servers
Function-as-a-Service: Overview
„Event-action platform
to execute code in
response to events“

15. 15
Serverless deployment & operations model
We hide infrastructural and operational complexity allowing you to focus on coding:
You provide code – we execute it!
Optimal utilization, fair pricing at any scale
We provide you exactly with the resources you need; and charge you when your for
code is executed
Flexible programming model & powerful tooling
We support multiple languages (incl. Swift) and even the execution of custom logic
via Docker containers plus SDK/tools to declaratively chain your code snippets
Open source & open ecosystem
Open to run anywhere (on-premises vs. Bluemix hosted), no vendor lock-in and a
growing ecosystem of contributors and partners
OpenWhisk: Details
1
2
3
4

16. 16
}1 Associated Services
OpenWhisk Bluemix
Runtime
Cloudant
Data event occurs:
- git commit
- CloudantDB operation
- etc.
Event triggers:
- An associated
OpenWhisk action
2
Node.js Swift Docker
OpenWhisk: How does it work?
Registered Actions
Git
Weather API
…
OR direct execution:
- Web Action endpoint
- `wsk` action execute
- etc.

17. 17
Consistent experience:
Common service binding & consumption model
Common user ID & permissions model
Common routing layer
Consistent experience
• Common service binding & consumption model
• Common user ID & permissions model
• Common routing layer
Level of
abstraction
Flexibility
OpenWhisk
FaaS
flexibility vs ease of use/abstraction trade-off
Bluemix: Compute Models
Cloud Foundry
PaaS
Docker/Containers
CaaS
Kubernetes/Containers
CaaS

18. 18
Execute code on-demand in a highly scalable, managed environment through event
driven triggers. Functions can be written in Javascript, Apple Swift, or custom
Docker images. SDK with service binding and API gateway (beta) support available.
OpenWhisk
Build and deploy portable applications with significant flexibility and control over
content that run anywhere without having to reconfigure and deploy for different
environments. Orchestrate using available technologies, including Kubernetes.
Containers
Deploy and scale applications using a broad set of runtimes, binding to a rich set of
cloud services, without having to manually configure and manage servers.
Cloud
Foundry
Infrastructure
Control
Bluemix: Compute Model Comparison

19. Demo Application: FlightAssist
A practical comparison of the three
compute models discussed
19

20. Uses several APIs/services:
> TripIt API
> FlightStats API
> Weather Company API
> Cloudant NoSQL DB
A Node.js application; default deploys as a CloudFoundry
application. Easily decomposable into a set of service
queries after retrieving trip data.
https://github.com/estesp/flightassist/
20
FlightAssist: Overview

21. 21
FlightAssist: Application Layout
FlightAssist
Language: Node.js
Monolithic CF app
TripIt API
Bluemix Services
Weather
Company
Data
External API/Services
Cloudant
FlightStats API
http://localhost:3000/
http://localhost:3000/authenticate
http://localhost:3000/flights
view index.ejs
oAUTH w/TripIt
TripIt oAUTH callback > view trips.ejs
AJAX calls:
/i/tripdata
/i/flightinfo
/i/weather
/i/conninfo

22. 22
FlightAssist: Application Demonstration
FlightAssist
Language: Node.js
Monolithic CF app
AJAX calls:
/i/tripdata
/i/flightinfo
/i/weather
/i/conninfo
http://localhost:3000/
FlightAssist
Language: Node.js
Monolithic
Containerized App
http://localhost:3000/
FlightAssist
Language: Node.js
App Container
http://localhost:3000/
WeatherService
Language: Python
Container
http://localhost:5000/
/i/weather
WeatherService
Language: Swift
OpenWhisk Action
See: https://github.com/estesp/flightassist/

23. Demo
Deploying FlightAssist with various
application models
23

24. Understanding Your Compute
Options
Trade-offs for deployment
methodologies
24

25. 25
Deployment Model Comparison
Containers PaaS/Cloud Foundry FaaS/OpenWhisk
• Full control over runtime
environment (minimal OS)
• Lends itself towards reuse/
organizational control (e.g.
common base image for
application dev/test/prod)
• Portable runtime packaging (dev.
laptop, production server, public
cloud)
• Orchestration platforms and
paradigms support micro service
architectures well (service
discovery, load balancing, etc.)
• No requirement to understand/
manage OS layer; CF buildpacks
• Platform handles routing, scaling,
logging, health check with little
to no involvement from developer.
• Service catalog/service binding
model highly beneficial for ease of
consuming and configuring
external capabilities (APIs,
databases, platform capabilities)
• Infrastructure not even a
discussion point with function
developer. “PaaS on steroids”
• Highly granular “utility” model for
pricing (100ms) means short-lived
functions incur minimal cost. Very
low latency + “infinite” scaling.
• Custom [Docker image]
runtime support for non-standard
use cases (bash script, compiled
code) with same workflow
• Encourages good micro service
architecture flows with action
trigger and sequence capabilities• OS layer updates/patching
• More developer/operator concerns:
build, service configuration, custom
middleware/backends (instead of
provided services)
• Little to no visibility into platform
(OS image, library/runtime versions,
etc.); mercy of build pack updates?
• Tends to guide developer towards
monolithic app development
• App routing/interactions limited to
HTTP/HTTPS
• Some limitations in runtime support
(complexity in using libs/frameworks)
• Actions via HTTP still maturing; can be
complex to configure.
• Visibility/debug can be difficult

26. 26
Notices and disclaimers
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27. 27
Notices and disclaimers
continued
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28. InterConnect
2017
Thank You!
28
Phil Estes @estesp
Lin Sun @linsun_unc
Check out/enhance/contribute to our demo
application:
https://github.com/estesp/flightassist
https://github.com/estesp/flightassist-weather