OpenWhisk - A platform for cloud native, serverless, event driven apps

OpenWhisk
Cloud native • Serverless • Event driven • Microservices
@DanielKrook • IBM Cloud

@DanielKrookOpenWhisk.org
What you will learn today
• How cloud computing has recently evolved to enable
developers to write cloud native applications better,
faster, and cheaper using serverless technology.
• How OpenWhisk provides an open source platform to
enable cloud native, serverless, event driven applications.

What makes serverless,
event driven computing
so compelling?

Cloud evolution means developers can write apps better, faster, and cheaper
Bare
metal
Virtual
machines
Containers
Functions
Decreasing concern (and control) over stack implementation
Increasing focus on business logic

Newer workloads are a better fit for event driven programming
Execute app logic in response to database triggers
Execute app logic in response to sensor data
Execute app logic in response to cognitive trends
Execute app logic in response to scheduled tasks
Provide easy server-side backend for mobile app

Problem: It’s expensive to scale microservices
Explosion in number of
containers / processes:
1. Increase of infrastructure
cost footprint
2. Increase of operational
management cost and
complexity
Region BRegion A
Break-down into microservices
Make each micro service HA
Protect against regional outages
Monolithic application

Serverless can handle many cloud native app 12 Factors
I Codebase Handled by developer (Manage versioning of functions on their own)
II Dependencies Handled by developer, facilitated by serverless platform (Runtimes and packages)
III Config Handled by platform (Environment variables or injected event parameters)
IV Backing services Handled by platform (Connection information injected as event parameters)
V Build, release, run Handled by platform (Deployed resources are immutable and internally versioned)
VI Processes Handled by platform (Single stateless containers often used)
VII Port binding Handled by platform (Actions or functions are automatically discovered)
VIII Concurrency Handled by platform (Process model is hidden and scales in response to demand)
IX Disposability Handled by platform (Lifecycle is hidden from the user, fast startup and elastic scale is prioritized)
X Dev/prod parity Handled by developer (The developer is the deployer. Scope of what differs is narrower)
XI Logs Handled by platform (Developer writes to console.log, platform handles log streaming)
XII Admin processes Handled by developer (No distinction between one off processes and long running)

Problem: Programming and pricing models aren’t efficient
Continuous polling needed in the absence
of an event driven programming model
Charged for resources, even when idle
Worries persist about capacity management
Swif
t
Application
Container VMCF
2
Polling
1b
Request
1a

Cost model offers a better match between app and resources
Applications charged by compute
time (millisecond) rather than
reserved memory (GB/hour).
While many applications must still be deployed in a daemon
model, serverless provides an alternative that can mean
substantial cost savings for a variety of event driven workloads.
Greater linkage between cloud
resources used and business
operations executed.

Technological and business factors make serverless compelling
Serverless platforms and frameworks are gaining traction
Cost models getting more granular and efficient
Growth of event driven workloads that need automated scale
Platforms evolving to facilitate cloud native design for developers

Introducing
OpenWhisk

OpenWhisk in a nutshell
OpenWhisk is a cloud platform
that executes code
in response to events
OpenWhisk

OpenWhisk is different than other hosted services
Serverless deployment and operations model
Optimized utilization, fine grained pricing at any scale
Flexible programming model with powerful tooling
Open source and open ecosystem
Ability to run in public, private, and hybrid models
OpenWhisk

OpenWhisk supports many growing workloads
OpenWhisk can help power
various mobile, web and IoT app
use cases by simplifying the
programming model of
orchestrating various services
using events without a dedicated
backend.
Digital app workloads Big Data/Analytics pipeline
Complex data pipelines for Big
Data/Analytics tasks can be scripted
using changes in data services or
streams for near real-time analytics
and feedback.
DevOps and infrastructure as code
OpenWhisk can be used to
automate DevOps pipelines
based on events triggered from
successful builds, or completed
staging, or a go-live event.
Microservices builder
OpenWhisk can be used to easily
build microservices given the
footprint and programming model
desired by microservices

The OpenWhisk
programming model

Triggers, actions, rules (and packages)
Data sources define the events they emit as triggers.
Developers associate actions to handle the events via rules.
T A R

Triggers
A class of events that can occurT
Social events
Data changes
Device readings Location updates
User input

Actions
Code that runs in response to an event
(that is, an event handler)
A

Actions
Can be written in a variety of languages, such as
JavaScript, Python, Java, and Swift
A
function main(params) {
return { message: 'Hello, ' + params.name + ' from ' + params.place };
};

Actions
Or any other language by packaging with DockerA

Actions
Can be composed to create sequences
that increase flexibility and foster reuse
A
AA := A1 + A2 + A3
AB := A2 + A1 + A3
AC := A3 + A1 + A2

Rules
An association of a trigger to an action
in a many to many mapping.
R
R := T A

Packages
A shared collection of triggers and actionsP
A
A read
write
T changes A translate A forecast
A post
T topic
Open
Source A myAction
T myFeed
Yours
T commit
Third
Party

OpenWhisk
in action

The OpenWhisk execution model
Pool of actions
Swift DockerJS
Trigger
1
Running
action
Running
action
Running
action
3
OpenWhisk
Engine
2 A
T
AAA

OpenWhisk enables event driven applications
Event
Providers
Cloudant
GitHub
Weather
…
Which triggers execution of
associated OpenWhisk action
2
Slack
JS Swift Docker …
An event occurs, for example
• Commit pushed to GitHub repository
• Data changed in Cloudant
1
OpenWhisk

OpenWhisk can implement REST microservices
Send HTTP request
HTTP GET
app.com/customers
1
Invoke OpenWhisk
action get-customers
Browser
Mobile App
Web App
2
JS Swift Docker …
OpenWhisk
API
Proxy

Watson IOT OpenWhisk
Customer
registry
Shipping
system
SendGrid
Service
reports
actions
IBM Cloud
LOB, SoR
systems &
databases
Need a
new filter
Email: Filter
on its way!
bit.ly/open-fridge

analyze
reading
OpenWhisk
create
order
alert
customer
alarm
changes changes
service order appliance
feed
Watson
IoT
A A AT
T T
T
P
P
P
bit.ly/open-fridge

OpenWhisk CLI: Create and test action
Create the Action that analyzes IoT readings, then stores in the database
wsk action create analyze-service-event analyze-service-event.js
--param cloudant_user $CLOUDANT_USER
--param cloudant_pass $CLOUDANT_PASS
Invoke the Action manually with sample message data to test
wsk action invoke --blocking --result analyze-service-event
--param service '{"appliance_serial": "xxxxyyyyzzzz", "part_number":
"ddddeeeeffff", "reading": 13, "timestamp": 1466188262}'
A

OpenWhisk CLI: Link trigger to action
Create the Trigger that subscribes to an MQTT topic pattern
wsk trigger create openfridge-feed-trigger
--feed mqtt/mqtt-feed-action
--param topic 'iot-2/type/+/id/+/evt/+/fmt/json'
--param url 'ssl://example.messaging.internetofthings.ibmcloud.com:8883’
Link the Trigger to the action using a Rule
wsk rule create --enable openfridge-feed-rule
openfridge-feed-trigger analyze-service-event
R := T A

OpenWhisk
high level
implementation
architecture

OpenWhisk design principles
1. Provide an open interface for event providers
2. Offer polyglot support and simple extensibility for new runtimes
3. Support higher level constructs as appropriate (e.g. action sequences)
4. Scale dynamically on a per request basis
5. Enable sharing of actions and event providers
6. Leverage best of breed open source software (Docker, Kafka, Consul, …)
7. Use the Apache 2 License

OpenWhisk under the hood
Consul
Couch
DB
Router (NGINX)
Controller
Kafka
Invoker Invoker
Docker
Executor Executor
Docker
Java Swift
Executor Executor
NodeJS Python
1. Router receives request to API
via CLI or UI
2. Controller checks entitlement and
dispatches requests to Kafka
3. Invokers pull requests and start
execution of the action

Summary

What you learned today
• We’re in the early days of an evolution that is
empowering developers to write cloud native
applications better, faster, and cheaper
• OpenWhisk provides an open source platform to enable
cloud native, serverless, event driven applications

Join us to build a cloud native platform for the future!
OpenWhisk.org
dwopen.slack.com #openwhisk
bluemix.net

See a demo at
the IBM booth!

OpenWhisk
Cloud native • Serverless • Event driven • Microservices

OpenWhisk - A platform for cloud native, serverless, event driven apps

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