This was a talk presented at AnDevCon in Washington DC, July 2017. For products that are delivered on the Web, iOS and Android, there have been myriad approaches to reducing development time and the duplication of work. Sharing code between major platforms has, in some ways, felt like the search for the holy grail - hope remains, but as of today, has yet to be found. As long as there have been multiple platforms, there has been a desire to write once, deploy everywhere. In this class, we will look at accelerating cross-platform development by harnessing serverless microservices. At Hootsuite, our serverless experiment uses AWS Lambda functions. This class will cover the motivations of using AWS Lambda compared with other mobile cross-platform solutions. We will also examine the benefits and drawbacks of this approach to cross-platform development. Lastly, you will learn how Hootsuite worked to automate the deployment and versioning of its AWS Lambda function, including its integration it into our existing continuous integration pipeline. We also share the lessons learned after having an AWS Lambda deployment on iOS and Android running for many months as well as the experimentation with Amazon API Gateway to create an endpoint which invokes the Lambda function, enabling the function to be used by our web-based products as well.

1. Put iOS and Android on the
same Wavelength with
Serverless Microservices
AnDevCon - July 2017
Neil Power @neilpower (and Paul Cowles @paulrc)
https://github.com/neil-power-hs/aws-lambda-sample

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INTRODUCTION

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● Mobile Software Developer at Hootsuite.
● Live and work in Vancouver, BC, Canada.
● Previously worked in DevOps at Hootsuite before
moving to Mobile development.
Who Am I

4. Hootsuite is the world’s most widely
used social media management
platform.

5. 15+ million users
800+ fortune 1000 companies

6. Nearly 1000 employees
across 10+ offices

7. Hootsuite is a centralized hub for all
things social.

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● Core Mobile team facilitates mobile development at
Hootsuite.
● Dedicated iOS, Android, API and Services, Automation
teams.
● Continuous integration and delivery pipeline.
● iOS and Android teams focus on native
implementations (Swift/Obj-C and Java/Kotlin).
Our Team

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Library Driven Development
Core team focussed on library driven development
and being able to ‘slice’ our app into verticals.

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Library Driven Development

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● Culture
○ To work out loud (#workoutloud)
○ Experimentation
○ Innersource / Open Source
○ Giving back to the community
Why Am I Here

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Culture of Experimentation
● A new mindset: We don’t do projects, we run
experiments.
● We build, measure, learn, and repeat.
● For product, change from feature based roadmaps to
problem based roadmaps.

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Managing Change
SERVERTOSERVERLESS

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Progression of Servers
● Physical Servers
● Virtual Servers
● Containers
● Serverless

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Physical Servers
● Servers in the Basement.
○ No Disaster Recovery 👎
○ High Maintenance Cost 👎

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Virtual Servers
● Servers managed by AWS.
○ Disaster recovery 👍
○ Lower maintenance cost 👍
○ Low utilization 👎

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Containers
● Servers still managed by AWS.
○ Disaster recovery 👍
○ Lower maintenance cost 👍
○ High utilization 👍

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Serverless
● Servers managed by AWS (fully hidden)
○ Disaster recovery 👍
○ Lowest maintenance cost 👍
○ Higher utilization 👍 (pay per use)

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Managing Change
APPEXPERIMENTS

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Past Experiments at Hootsuite
● Web Views
● Cordova/Phonegap
● React Native

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Web Views
● Many limitations. 👎
● Javascript 👎

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Cordova
● Great for quickly prototyping 👍
● Challenging for complex apps, responsiveness on
gestures and touch, and clean crisp animations and
transitions 👎
● Javascript 👎

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React Native
● Ends up looking a lot like a fully native app 👍
● Needs to be stable, avoid temporary workarounds 👎
● Javascript 👎

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What Should We Try Next?
● Service oriented architecture (SOA), microservices
inspired
● Focus lower down the stack, away from the interface
● Develop and debug local, run in the cloud
● Cross Platform - Android first, iOS second, Web third

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THEEXPERIMENT

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Improved Twitter Search
● Hootsuite enables users to search Instagram and
Twitter and save those as streams for future use
○ One of our most popular stream types
● Twitter in particular provides an extensive search API
○ Unless you’re a developer, search syntax is arcane

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Twitter Search Syntax
● cats AND dogs AND (fish OR lizards)
filter:media -RT min_retweets:10
geocode:49.209389,-120.190909,15mi lang:en
-cows

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Add a Query Builder
● Query Builder allows Hootsuite users to create
complex Twitter searches using a simple graphical
interface.
● No longer have to learn and remember Twitter search
syntax.

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33. /

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Why Keep it Out of the Client?
● Twitter could change search syntax.
○ We don’t want to redeploy the apps after such a
change.
● We want to avoid computation the app side.
● We want to avoid embedded ANTLR runtime in the
app.

35. (((Social OR socialmedia OR #SocialMedia) AND (monitoring OR
analytics OR “management tool" OR compliance OR listening OR
monitoring OR publishing OR engagement OR infrastructure OR
intelligence OR "Social Media Management")) AND
(recommendation OR recommendations OR suggestion OR
suggestions OR ideas OR thoughts OR suggest OR recommend OR
promote OR advice OR "Should use" OR anyone OR Friends OR
(What's AND Favorite))) AND -RT -http -from:FiftySocialMedia
Real Customer Search

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The Tools we Used
● AWS Lambda
● API Gateway
● Terraform
● AWS CLI
● boto
● Gradle
● Jenkins

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AWS Lambda
● AWS Lambda is an event-driven, serverless computing
platform provided by Amazon.
○ Allows you to run code in the cloud without
creating servers or containers.

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API Gateway
● API Gateway is a tool for creating and managing APIs.
○ Can be easily integrated with Lambda functions.
○ Manage an API like a RESTful Endpoint.

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Terraform, AWS CLI, boto
● Terraform: a tool for Infrastructure as code. Build,
change, version infrastructure.
○ Terraform allows the testing and reproduction of
infrastructure changes.
● AWS CLI: tool for managing AWS resources through a
terminal.
● boto: Python wrapper for AWS CLI.

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Gradle
● Gradle is an open source build automation system.
○ Builds off the concepts of Ant and Maven.
○ Used frequently on Android, so natural fit for our
experiment.

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Jenkins
● Jenkins is a continuous integration application.
○ Used at Hootsuite to power our build pipelines.

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HELLOLAMBDA

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Experiment Distillation
● A “hello world” for our experiment just for you!
● Available publicly on github.
● We’ve extracted the essence of this talk from our live
experiment so that you can play with it yourself after
the conference.

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/
package com.hootsuite.example.lambda;
public class SampleLambda {
public static String invokeFunction(SampleRequest request) {
switch (request.getInput()) {
case 0: return "ZERO";
case 2: return "TWO";
case 3: return "THREE";
default: return "GREATER THAN ZERO";
}
}

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How It Fits Together

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How It Fits Together
Build Zip,
Upload to S3

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How It Fits Together
Push artifact
from S3 to Lambda

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How It Fits Together
Clients invoke
Lambda

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How It Fits Together

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How It Fits Together

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Test Locally
JUnit tests hit
the local code.

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Creating AWS Infrastructure
● Now we have an artifact built by Gradle
● We need to create the AWS Infrastructure
○ AWS Lambda Function
○ IAM resources to invoke and manage the function

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resource "aws_lambda_function" "sample_lambda" {
filename = "../build/distributions/sample-lambda-1.0.0.zip"
function_name = "sampleLambda_${var.env}"
description = "A demonstration of AWS Lambda"
runtime = "java8"
timeout = 10
role = "${aws_iam_role.sample_lambda_role.arn}"
handler = "com.hootsuite.example.lambda.SampleLambda::invokeFunction"
}

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Terraform Plan
● After fully specifying the Infrastructure we need to
build it.
● Terraform uses the concept of a “plan” (a dry run)
● Planning allows you to see what changes will be made
before making them.

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Push Artifact to Lambda

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End to End Testing
JUnit tests hit the
Lambda Function.

65. PERFORMANCE

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What About Performance?
● Evaluated before committing to the approach
● Measured “Hello World” as Lambda - iOS and Android.
Consistent?
● Measured actual function as Local vs. Lambda.
Difference? Sub second?

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Platform Min. Time (ms) Mean Time (ms) Max. Time (ms) Std. Deviation (ms)
Android 73 120 410 13
iOS 70 130 330 24

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Environment Min. Time (ms) Mean Time (ms) Max. Time (ms) Std. Deviation (ms) CoV
Local 14 16 18 1.3 7.9%
Lambda 610 740 840 70 9.5%

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MANAGINGCHANGE

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Client and Server Changes
● Older app builds in the wild, locked in time
● Changing server side APIs can break legacy app
experiences
● “Broken app until you upgrade, sorry!”

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No App Left Behind
● Lambda supports versions and aliases
● Leverage both to safely support legacy clients while
still allowing ability to evolve
● Lock to alias, control mappings to versions

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SDKs Versus API Gateway
● Started using API Gateway in iOS to reduce library
dependencies
● On Android, helped to lower method count in the app.
● Minimal increase in execution time.

84. Rest Client

85. Request

86. Lambda Function

87. Response

88. Rest Client

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AUTOMATIONAND
INTEGRATION

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Start With Automation
● Manual deployment is tedious, automate early
● Other than deployment, nothing else to manage

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xkcd: Is It Worth The Time? https://xkcd.com/1205/

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Continuous Deployment
● Manage deployment using Gradle and boto
● Jenkins for continuous integration and delivery
● Dashboards show Jenkins job results

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LEARNINGS

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Development Experience
● The Good
○ Android developers immediately productive in Java.
○ Android developers finally get to use Java 8.
○ Much easier to manage Lambda than virtual server.
● The Challenges
○ Many different technologies (polyglot development).
○ Rather than compilation, Lambda code must be deployed.

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The Sweet Spot
● Works well for complex “business logic”
● Adds safety when aggregating or integrating third party services
● Requires network availability, not a fit for offline experiences
● User experience that allows hiding latency by prefetching
● Cross platform requirement

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Downsides
● Latency to manage
● Offline use case not supported
● Investment up front to automate deployment hassles (devops)
● Fat AWS SDK on iOS makes REST interface highly desired
● Not a cross platform strategy for entire app, only layer(s)

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Benefits
● Sharing across Web and mobile
● If you’re already aligned with microservices, natural mental model
● No servers sitting idle costing you money
● Lambda ideal for low, uncertain or sporadically used services due
to pay per use however also endlessly scalable
● Sane way of versioning client server
● Low burden to support MANY versions at the same time
● Encourages encapsulation
● Easy to empower distributed teams

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SUMMARY

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Summary
● Download the sample repo yourself and run through front to
back, we use it as a workshop.
● The cross platform opportunity will continue to be a dream goal
and hotly contested in terms of how much it is worth chasing and
how to best achieve it.
● Physical servers -> Virtual Servers -> Containers -> Serverless is
an interesting journey.
● Cloud functions are a powerful enabler.
● Embrace experimentation as part of your culture.
● Share what you are doing #workoutloud!

103. Thanks!
Questions?