Serverless Architectural Patterns

@theburningmonk#VoxxedBristol #serverless
Serverless Design Patterns
Yan Cui

Gojko Adzic
It is serverless the same way
WiFi is wireless.
http://bit.ly/2yQgwwb

Serverless means…
don’t pay for it if no-one uses it
don’t need to worry about scaling
don’t need to provision and manage servers

“Function-as-a-Service”
AWS Lambda
Azure Functions
Google Cloud Functions
Auth0 Webtask
Spotinst Functions Kubeless
IBM Cloud Functions

AWS Lambda
API Gateway IOT SNS Kinesis CloudWatch

IaaS
Function
Application
Runtime
Container
OS
Virtualization
Hardware
CaaS
Function
Application
Runtime
Container
OS
Virtualization
Hardware
PaaS
Function
Application
Runtime
Container
OS
Virtualization
Hardware
FaaS
Function
Application
Runtime
Container
OS
Virtualization
Hardware
User User (scalable unit) Provider

Serverless
FaaS
other services…
Database
Storage
BI

SERVERLESS WILL FUNDAMENTALLY
CHANGE HOW WE BUILD BUSINESS
AROUND TECHNOLOGY AND HOW YOU
CODE.
Simon Wardley

more Scalable
(and scales faster!)

Cheaper
(don’t pay for idle servers)

Resilience
(built-in redundancy and multi-AZ)

idea production
choose language
+ framework
master language
+ framework
figure out
deployment
configure AMI
configure ELB
configure
autoscaling
capacity planning
over-provision for
launch
are we doing
microservices?
configure CI/CD

idea production
greater Velocity from idea to product

minimise Undifferentiated
heavy-lifting

Less ops responsibility on
your shoulders

events are an enabler for
COMPOSABILITY

DESIGN PATTERNS DO NOT GUARANTEE SUCCESS

Pattern
/pat(ə)n/
A pattern is the repeated or
regular way in which something
happens or is done.

UNDERSTAND YOUR PROBLEMS
AND CONSTRAINTS OVER
FOLLOWING A PATTERN.
me

Yan Cui
http://theburningmonk.com
@theburningmonk
Principal Engineer @

available in Austria, Switzerland, Germany,
Japan, Canada, Italy and US

We’re hiring! Visit
engineering.dazn.com
to learn more.
follow @dazneng for
updates about the
engineering team

follow @dazneng for
updates about the
engineering team
We’re hiring! Visit
engineering.dazn.com
to learn more.
WE’RE HIRING!

https://www.youtube.com/watch?v=pptsgV4bKv8

https://bit.ly/production-ready-serverless

Cron

Ops Automation

AWS Lambda CloudWatch Logs AWS Lambda

AWS Lambda CloudWatch Logs
CloudTrail

CloudWatch Events
CloudTrail
AWS Lambda

CloudWatch Events
CloudTrail
AWS Lambda
AWS Lambda

auto-update CloudWatch retention policy
auto-create alarms for new APIs
auto-create dashboards for new APIs
alert on suspicious console logins
alert on EC2 activities in unused regions
…

Web Apps

API Gateway AWS Lambda DynamoDBRoute53
CloudFront S3
Browser

API Gateway AWS Lambda DynamoDBRoute53
CloudFront S3
Browser
Cognito

Federated
Identities
Sync
User Flows
Registration
Verify email/phone
Secure sign-in
Forgotten password
Change password
Sign out
Cognito User
Pools

Federated
Identities
Sync
Leading Practices
Secure password handling
with SRP protocol
Encrypt all data server-side
Password policies
Token-based authentication
MFA
Support CAPTCHA
Cognito User
Pools

Cognito
Federated Identities
Cognito
User Pools
Facebook TwitterGoogle
…
identity providers
authenticate

Cognito
Cognito
User Pools
…
identity providers
authenticate token

Cognito
Cognito
User Pools
…
identity providers
authenticate token
token

validate
Cognito
Cognito
User Pools
…
identity providers
authenticate token
token

validate
Cognito
Cognito
User Pools
…
identity providers
authenticate token
token
IAM credential

validate
Cognito
Cognito
User Pools
…
identity providers
API Gateway S3 DynamoDB SNSIOT Kinesis
authenticate token
token
IAM credential
IAM credential

what about Multi-Region support?

https://aws.amazon.com/dynamodb/global-tables

API Gateway AWS Lambda
DynamoDB
Route53
CloudFront S3
Browser
API Gateway AWS Lambda
eu-west-1
us-east-1

Data Lakes

S3 BucketsKinesis Streams Kinesis Firehose
KMS MacieIAM

S3 BucketsKinesis Streams
AWS Lambda
KMS MacieIAM
Kinesis Firehose

AWS Lambda
KMS MacieIAM
AWS Lambda
Kinesis Firehose

AWS Lambda AWS Lambda
KMS MacieIAM
AWS Lambda
Kinesis Firehose

KMS MacieIAM
AWS Lambda
DynamoDB
ElasticSearch
Kinesis Firehose

KMS MacieIAM
AWS Lambda Google BigQuery
Kinesis Firehose

Athena QuickSight
KMS MacieIAM
AWS Lambda
Kinesis Firehose

Event Driven

Kinesis
API Gateway AWS Lambda API GatewayAWS Lambda
service-A service-B

Kinesis
service-A service-B
AWS Lambda
AWS Lambda
AWS Lambda

Kinesis
service-A service-B
AWS Lambda
AWS Lambda
AWS Lambda DynamoDBIOT

build loosely-coupled system
through events

service A service B
service C service D
bounded context
bounded context

service A service B
service C service D

service A service B
service C service Dbackward-compatible?

bounded context
DON’T use events to
orchestrate workﬂows
within the same
bounded context

bounded context
adds unnecessary
complexity to logging,
tracing, and end-to-end
reporting

bounded context
the workﬂow doesn’t exist
as a standalone concept,
but as the sum of a series of
loosely connected parts

Step Functions
use Step Functions instead

Step Functions
don’t forget to emit events
from the workﬂow

Step Functions
so others can react to state
changes that happened as
part of the workﬂow

Decoupled Invocation

Decoupled Invocation
How can a service handle normal
request loads, peak request loads,
and a continuous period of high
load without failing?

business logic requires expensive processing

API Gateway
max integration timeout is 29 seconds
http://amzn.to/2BwW5Bx

downstream systems not as scalable

decouple reply from the initial request

workerAPIClient
POST /do_something
202 /result_location
do work

workerAPIClient
POST /do_something
GET /result_location
do work

workerAPIClient
POST /do_something
do work
work done

workerAPIClient
POST /do_something
do work
work done
200 OK

allows fast response back to caller whilst
promises to ﬁnish work later

allows ﬂexible retry strategies by removing the
urgency of having to reply to caller right away

DynamoDB
API Gateway
POST
task id created at result
xxx xxx <null>
xxx xxx <null>
… … …
task results
not ready
PutItem

DynamoDB
API Gateway
POST
xxx xxx <null>
xxx xxx <null>
… … …
task results
not ready
SQS

DynamoDB
API Gateway
202
xxx xxx <null>
xxx xxx <null>
… … …
task results
not ready
SQS

use “created at” timestamp to timeout
polling requests and avoid inﬁnite retry

DynamoDBAPI Gateway
GET
xxx xxx <null>
xxx xxx <null>
… … …
task results
not ready
SQS

DynamoDBAPI Gateway
202
xxx xxx <null>
xxx xxx <null>
… … …
task results
not ready
SQS

DynamoDB
xxx { … }
xxx <null>
… …
task results
done
UpdateItem
xxx
xxx
…
SQS

DynamoDBAPI Gateway
GET
xxx xxx { … }
xxx xxx <null>
… … …
task results
done

DynamoDBAPI Gateway
200 { … }

control parallelism with Lambda reserved concurrency setting

also consider using Kinesis Streams or
DynamoDB Streams as queue

if you use SNS, make sure to enable
maxReceivesPerSecond delivery policy
(otherwise, invocation-per-message means no amortisation)

Pub-Sub

msg broker
subscriber
subscriber
subscriber
subscriber
…

good for decoupling data processing

independent failures
partial failures are easier to manage

SNS, Kinesis Streams, DynamoDB Streams, etc…

2 retries then DLQ
invocation per msg
SNS

2 retries then DLQ
invocation per msg
might run into
throttling limits
consider impact on
downstream
SNS

msg/s
time
max throughput
erred and retried

msg/s
time
max throughput
downstream outage

retried until success
invocation per shard
Kinesis

better handling of temporary issues

msg/s
time
processed
max throughput amortised
received

msg/s
time
max throughput
downstream outage
processed
received

Kinesis Streams or DynamoDB Streams?

limited to events from one table

records describe DynamoDB events,
not events from your domain

cannot extend data retention beyond 24 hours

charged based on no. of requests
($0.02 per 100,000 read request units)

1 msg/s for a month, 1KB per msg
$0.47
1 x 60s x 60m x 24hr x 30days
@ $0.014 per mil
+
24hrs x 30days
@ $0.015 per hr
$10.836
1 x 60s x 60m x 24hr x 30days
@ $0.5 per mil
$1.296
DynamoDB StreamsSNSKinesis Streams
1 Write Capacity Unit
@ $0.47 per unit

1k msg/s for a month, 1KB per msg
1k x 60s x 60m x 24hr x 30days
@ $0.014 per mil
+
24hrs x 30days
@ $0.015 per hr
$47.088
1k x 60s x 60m x 24hr x 30days
@ $0.5 per mil
$1296.00
DynamoDB StreamsSNSKinesis Streams
$470.00
1k Write Capacity Unit
@ $0.47 per unit

DON’T take these projections at face value!

no restriction on
destination target
SNS

no restriction on
destination target
need to handle partial
failures & retries
SNS

Saga

pattern for managing failures where each action
has a compensating action for rollback

https://www.youtube.com/watch?v=xDuwrtwYHu8

Begin transaction
Start book hotel request
End book hotel request
Start book ﬂight request
End book ﬂight request
Start book car rental request
End book car rental request
End transaction

model actions and compensating actions
as Lambda functions

state machine in AWS Step Functions as
the coordinator for the saga

AWS Step Functions
http://bit.ly/2uTJBE3

source code available here:
https://github.com/theburningmonk/lambda-saga-pattern

API Gateway and Kinesis
Authentication & authorisation (IAM, Cognito)
Testing
Running & Debugging functions locally
Log aggregation
Monitoring & Alerting
X-Ray
Correlation IDs
CI/CD
Performance and Cost optimisation
Error Handling
Configuration management
VPC
Security
Leading practices (API Gateway, Kinesis, Lambda)
Canary deployments
http://bit.ly/prod-ready-serverless
get 40% off
with: ytcui

#VoxxedBristol #serverless @theburningmonk
Thank You!

Serverless Architectural Patterns

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