Getting Started with

Serverless Architectures

Email: anything@jedberg.net

Twitter: @jedberg

Web: www.jedberg.net

Facebook: facebook.com/jedberg

Linkedin:

www.linkedin.com/in/jedberg

Jeremy Edberg

CoFounder

https://www.cloudnative.io

λ

Test and prod are different

Prod is in need of constant

updates

Slow iteration and deployment

Polyglot unfriendly

Deploy in weeks, live for years

Physical Servers

Prod is immutable

Rapid iteration and deployment

Multi-tenancy

Polyglot friendly

Deploy in minutes, live for weeks

Virtual Machines

Test and prod are the same

Prod is immutable

Rapid(er) iteration and deployment

High multi-tenancy

Polyglot friendly

Deploy in seconds, live for hours

Containers

Smallest unit of compute

Super scalable

Rapid iteration

Extreme multi-tenancy

Very polyglot friendly

Easier to collaborate

Deploy independently, live for

seconds

Serverless

A whole lot of choices

Amazon’s EcosystemHodgepodge of services

A whole lot of choices

Amazon’s Serverless

Ecosystem

Lambda

SNS

DynamoDB

SQS

S3

Kenisis

Continuous

scaling

No servers to

manage

Never pay for

idle – No cold

servers (only

happy

accountants)

Benefits of AWS Lambda

What is serverless anyway?

• There are still servers, you just

don’t manage them anymore

• It also means you don’t access

them anymore

• So you don’t need to (or get to)

optimize them.

What is Serverless Computing?

• VMs

• Machine as the unit of scale

• Abstracts the hardware

• Containers

• Application as the unit of scale

• Abstracts the OS

• Serverless

• Functions as the unit of scale

• Abstracts the language runtime

EC2

ECS

Lambda

How do I choose?

• VMs

• “I want to configure machines,

storage, networking, and my OS”

• Containers

• “I want to run servers, configure

applications, and control scaling”

• Serverless

• “Run my code when it’s needed”

EC2

ECS

Lambda

Serverless computing is

all about speeding up

development by allowing

rapid iteration and

removing management

overhead

A brief journey through history

80’s Mainframe Cycle

• Cost $1MM to $100MM

• 1 to 5 years to execute

• Usually had to bet the whole

company

• Cost of failure -- Bankruptcy

90‘s Client/Server Cycle

• Cost $100K to $10MM

• 3 to 6 months to execute

• Usually had to bet a product or

division

• Cost of failure -- Revenue hit, CXX

job

00‘s Agile Cycle

• Cost $10K to $1MM

• 3 to 6 weeks to execute

• Bet a product feature

• Cost of failure -- product manager

reputation

Product Manager

Developer

QA

Ops

BI / Analytics

Cost and size

of risk

decreased

Rate of

change

increased

ReleaseTestBuild

ReleaseTestBuild

ReleaseTestBuild

ReleaseTestBuild

ReleaseTestBuild

ReleaseTestBuild

Multiple services

Internal Microservices Platform

Monolithic

Success follows a standard

pattern

Distributed Computing and a

Distributed Workforce

• The two go hand in

hand when you have

a good distributed

systems culture

• Microservices and

Micro Teams

• Services are built by different

teams who work together to

figure out what each service

will provide.

• The service owner publishes

an API that anyone can use

and returns proper response

codes

Highly aligned, loosely

coupled

The Microservices Architecture

Microservices Tools

Web Servers

Code Libraries

Frameworks

Config Management

API Management

Deployment, CI/CDContainers

etc.

etc.

etc.

Amazon’s Microservices

Tools

What do all the parts of

microservices have in common?

Servers

Capacity planning

Right-sizing

Autoscaling

Load and performance

Patches

Tuning

Configuration

Utilization

Access control

Packages and AMIs

Serverless

Right-sizing

Autoscaling

Load and performance

Patches

Tuning

Configuration

Utilization

Access control

Packages and AMIs

Fully managed

Continuous Scaling

Function is the deployment unit

Capacity planning

What is Lambda?

Serverless, event-driven compute service

Lambda == microservice without managing servers

What does Lambda do for you?

• Scales server capacity

automatically

• API to trigger execution

• Ensures function is executed in

parallel and at scale

• Logging, monitoring, etc

• Easy pricing

Monitoring• Everything is in Cloudwatch or Cloudwatch logs

Pricing

• Choose your RAM

from 128MB to

1500MB

• CPU and Network

scaled based on

RAM

Cost Comparison

Cost Comparison

There’s about 2.5M seconds in a month, so 3M requests is about 1.2 per second

The T2.Small is $18.98 a month, more than Lambda already

Lambda allows for a

tight feedback loop

• We turned around

both these

requests in less

than a day

How does work?λ

Author your code

• AWS SDK built in

• Access to /tmp,

processes,

threads, etc

λ

• NodeJS, Python

• Java and any JVM

language

• Use any library you

want

Choose an event source

• S3

• Kinesis

• SNS

• DynamoDB

• CloudWatch

λ

• Config Rules

• Amazon Echo

• API Gateway

• Lambda

functions

• More coming

Choose a Network

• Default

• All functions have

internet access

• No access to your

other VPCs

• Still in a VPC

λ

• Customer VPC

• Private communication

within your VPC

• Same configuration as

your other VPCs (ENI,

route table, security

groups, NAT)

Deploy your code

• Use the GUI or

• Upload to S3 or

Lambda directly

λ

Write the function

Create the IAM role

Add extra permissions for a push model

Zip the function and dependencies

Test the function with mock data

Add an event source to the function

View the output of the live function

Write the function

Create the IAM role

Add extra permissions for a push model

Zip the function and dependencies

Test the function with mock data

Add an event source to the function

View the output of the live function https://cloudnative.io/oss/

Word Generator

• Generate some number of English

looking words using an ngram

database

• Allow a prefix to be specified

Demo

ECS

Architecture

Lambda

Lambda DynamoDB

SNS

Kinesis

Slack

router.py

Call out to other Lambda

functions

Add their results as attachments

to the message

router.py

Demo

From conception to prod

in 5 minutes

Red/Black,

Blue/Green,

Mauve/Chartreuse

Codebase

Structure

Frontend vs Backend

Repos

Lambda lets you manage your

code and infrastructure in the

same place (as long as you use

Kappa or something like it).

Example use cases

Live video stream processing

Cloudfront S3

Ingest

Lambda Functions

HQ Copy

480p

Transcode

360p

Transcode

Audio Only

Transcode

Thumbnails

S3

Playbac

k

Cloudfront

Streaming

Serverless Website

S3

Static

Content

Dynamic

Content

API Gateway Lambda DynamoDB

Use Cases

• Application Backend

• Data Processing

• Command and Control

• Any functional or event

based system

Tips and Tricks

• Limit your function size (JVM

startup time especially)

• Remember execution is async

• Don’t assume function container

reuse but take advantage of it

Tips and Tricks

• Remember the 500MB in /tmp

• Use function aliases

• Use the included logger

Tips and Tricks

• Set up alarms on all Lambda

Cloudwatch metrics

• Avoid throttling by using SNS

between any service, such as

S3

• Beware of infinite loops by

having functions call each other.

Avoiding Infinte Loops

• With a distributed

team, this is an easy

mistake to make

• To avoid it, pass a call

stack and check for

self in the stack

Store your data properly

• No local instance

access

• Store everything in

S3, DynamoDB, or

Elasticache

DynamoDB S3

• zip up with

dependencies

• roles and permissions

• dev vs prod

• aliases

Difficulties we’ve solved

Problems we still have

• efficient dependency usage

• local dev environments

• making sure we have the same

dependencies

• knowing when someone else is

deploying the same function

ReleaseTestBuild

ReleaseTestBuild

ReleaseTestBuild

ReleaseTestBuild

ReleaseTestBuild

Next Steps

• efficient dependency usage

• local dev environments

• making sure we have the same

dependencies

• knowing when someone else is

deploying the same function

Problems we still have

• efficient dependency usage

• local dev environments

• making sure we have the same

dependencies

• knowing when someone else is

deploying the same function

Problems we still have

Testing

• You can’t test the

network, but a good

application test should

obviate the need to do so.

• Not really a solved

problem. Can do local

testing.

• Can also send json to the

function and compare the

results.

Questions?

Email: anything@jedberg.net

Twitter: @jedberg

Web: www.jedberg.net

Facebook: facebook.com/jedberg

Linkedin:

www.linkedin.com/in/jedberg

Company: cloudnative.io

Thank You!