AWS Serverless concepts and solutions

1. AWS Serverless
concepts and solutions

2. Agenda
1. AWS Serverless concepts
2. Serverless in the framework of business
3. AWS Serverless architectural approaches
4. AWS Lambdas overview and deployment models
5. Infrastructure as Code in AWS Serverless
6. CI/CD for AWS Serverless applications
7. AWS Serverless practical aspects
8. AWS Lambda monitoring and pitfalls

3. About me
Education:
Kharkiv National University of radio-electronics
Work experience:
3 years of software development expertise (full stack)
1 year of expertise in data engineering
Hobbies:
Cookery, cycling, skiing, painting

4. AWS Serverless
concepts

5. Serverless computing
 Dynamic resources allocation
 Stateless containers
 Various events as triggers
 "Functions as a Service"

6. Serverless advantages
Paying for value Reliability and fault tolerance
No servers to provision Scaling with usage

8. Serverless applications
Java
Python
Node.js
C#
Go
Ruby
Runtime API
- Changes in
data state
- Requests
to endpoints
- Changes in
resource state

9. Business aspects
of Serverless

10. Business benefits
Shorter time to
market
Increased
efficiency
Fixed costs
become variable
costs
Less waste More flexibility
Better service
stability
Better
management of
development
and testing

11. Serverless use cases
Web apps and back-end API Data processing and analytics
Internet of thingsChat bots
Third-party integrations
Internal tooling

12. Serverless side-effects
Vendor
lock-in
Service Level
Agreements
Maintaining
many small
services
Slower
service start &
higher latency

13. AWS Serverless
architectures

14. Serverless architectures
S3
bucket
Object
Lambda
function
1. File put into
S3 bucket
2. Lambda
invoked

15. Serverless architectures
SNS
topic
Lambda
function
Data
1. Data published
to a topic
2. Lambda
invoked

16. Serverless architectures
Message Amazon
SQS
Lambda
function
2. Lambda
polls queue
and invokes
function
1. Message
inserted to a queue
3. Function
removes
message from
queue

17. Serverless architectures
CloudWatch
events
(time-based)
Lambda
function
1. Scheduled time
occurs
2. Lambda
invoked

18. Serverless architectures
Amazon
Kinesis
Data
Stream
Lambda
function
2. Lambda
polls stream
1. Data published
to a stream
3. Amazon
Kinesis returns
stream data
Data

19. AWS Lambda
overview

20. AWS Lambda
 Concept to run the code
without provisioning or
managing servers
 Virtually supporting any
type of application or back-
end service – with zero
administration
 Resource allocation on
demand which ensures cost-
effectiveness

21. Lambda function anatomy
Handler function
function to be executed
upon invocation
Event object
data sent during
function invocation
Context object
contains runtime
information
import com.amazonaws.services.lambda.runtime.Context;
import com.amazonaws.services.lambda.runtime.RequestHandler;
public class LambdaFunction implements RequestHandler<Object, Object> {
@Override
public Object handleRequest(Object obj, Context context) {
// TODO implement
context.getLogger().log("Hello Lambda Function!");
return null;
}
}

22. Lambda lifecycle
Deployment
(code uploaded)
Trigger by
event
Container with
code created
Code execution
Re-launching or
container destruction

23. AWS Lambda config
and deployment

24. AWS Serverless Application Model
 Open-source framework for
building serverless applications
 Simple and clean syntax
 Lambda-like execution env for
local development
 Applications are defined by SAM
templates (yaml)
 Transforms SAM templates into
AWS CloudFormation syntax

25. AWS CloudFormation
 Service to model and set up AWS
resources
 Simplify infrastructure management
 Quick replication of infrastructure
 Easily control and track changes to
infrastructure
 Templates in json or yaml transform
into stacks
 Changes in stacks are tracked by
change sets

26. Lambda with AWS SAM
AWSTemplateFormatVersion: '2010-09-09'
Transform: AWS::Serverless-2016-10-31
Description : Sample SAM Template for sam-app
Globals:
Function:
Timeout: 20
Resources:
HelloWorldFunction:
Type: AWS::Serverless::Function
Properties:
Handler: helloworld.LambdaFunction::handleRequest
Runtime: java8
Environment:
Variables:
PARAM1: VALUE
sam build && sam local invoke --event event.json
sam deploy --guided

27. Lambda with AWS CloudFormation
AWSTemplateFormatVersion: "2010-09-09"
Description: Lambda template
Resources:
LambdaFunction:
Type: AWS::Lambda::Function
Properties:
FunctionName: test-function
Handler: helloworld.LambdaFunction
Role: !Sub arn:aws:iam::${AWS::Accounted}:role/lambda-role
Code:
S3Bucket: test-bucket
S3Key: SamApp-1.0.jar
Runtime: java8
Timeout: 60
MemorySize: 256
# Build artifact
mvn clean package
# Create S3 bucket for artifacts
aws s3 mb s3://test-bucket --region us-east-1
# Upload artifact to S3 bucket
aws s3 cp ./target/SamApp-1.0.jar s3://test-bucket
# Deploy Lambda template to AWS
aws cloudformation deploy --stack-name test-lambda
--template-file ./stack-lambda.yaml --capabilities CAPABILITY_NAMED_IAM

28. Serverless Application Model vs CloudFormation
SAM CloudFormation
Template format Yaml Yaml and json
Concept Framework as
CloudFormation extension
Service to manage
resources
Deployment Template is transformed
into CloudFormation one
and deployed into stack
Stack is the result of
template deployment
Function definition Function is defined by
AWS::Serverless::Function
Function is defined by
AWS::Lambda::Function
Local development Provides local lambda-like
environment
Doesn’t provide local
development features
API SAM API AWS SDK API for
CloudFormation
Supported resources Limited list of supported
resources
Extended list of supported
resources
Purpose Serverless applications Complete infrastructure

29. Infrastructure
as Code

30. Infrastructure as Code
Provisioning and managing
cloud resources by writing a
template file that is both
human readable, and machine
consumable
For AWS cloud
development the built-in
choice for infrastructure
as code is AWS
CloudFormation

31. AWSTemplateFormatVersion: "2010-09-09"
Description: Example Stack
Resources:
LambdaFunction:
Type: AWS::Lambda::Function
Properties:
FunctionName: test-function
Handler: helloworld.LambdaFunction
Role:
Fn::ImportValue: lambda-role
Code:
S3Bucket: test-bucket
S3Key: SamApp-1.0.jar
Runtime: java8
PermissionLambda:
Type: AWS::Lambda::Permission
Properties:
FunctionName: !GetAtt LambdaFunction.Arn
Action: lambda:InvokeFunction
Principal: sns.amazonaws.com
SourceArn: !Ref SnsTopic
SnsTopic:
Type: AWS::SNS::Topic
Properties:
TopicName: sns-topic
Subscription:
- Endpoint: !GetAtt LambdaFunction.Arn
Protocol: lambda
Infrastructure as Code

32. Benefits of Infrastructure as Code
VISIBILITY STABILITY SCALABILITY
SECURITY TRANSACTIONAL

33. CI/CD in Serverless

34. CI/CD in Serverless Applications
AWS CodeCommit
source control service
AWS CodeBuild
continuous integration service
AWS CodeDeploy
deployment service

35. AWS CodePipeline
 Release pipelines for fast and reliable application and infrastructure updates
 Automates the build, test, and deploy phases
 Rapid and reliable features and updates delivery
 Integration with third-party services such as GitHub or with the custom plugins

36. Build
specification
for AWS
CodeBuild
version: 0.2
env:
variables:
JAVA_HOME: /usr/lib/jvm/java-8-openjdk-amd64
phases:
install:
commands:
- echo Entered the install phase...
- apt-get update -y
- apt-get install -y maven
finally:
- echo Install phase completed
pre_build:
commands:
- echo Entered the pre_build phase...
- cd test-app
finally:
- echo Pre-build phase completed
build:
commands:
- echo Entered the build phase...
- echo Build started on `date`
- mvn install
finally:
- echo Build phase completed
post_build:
commands:
- echo Build completed on `date`
artifacts:
files:
- target/test-app-1.0.jar
discard-paths: yes

38. CodePipeline template
AWSTemplateFormatVersion: "2010-09-09"
Description: AWS Code Build Project Stack
Resources:
CodePipeline:
Type: AWS::CodePipeline::Pipeline
Properties:
…
Stages:
- Name: Source
Actions:
- Name: SourceAction
…
- Name: Build
Actions:
- Name: BuildAction
…
- Name: Deploy
Actions:
- Name: DeployAction
…

39. CodeBuild template
AWSTemplateFormatVersion: "2010-09-09"
Description: AWS Code Build Project Stack
Resources:
CodeBuildProject:
Type: AWS::CodeBuild::Project
Properties:
Name: "code-build-project"
ServiceRole:
Fn::ImportValue: "code-build-service-role"
Artifacts:
Type: CODEPIPELINE
Environment:
Type: LINUX_CONTAINER
ComputeType: BUILD_GENERAL1_SMALL
Image: aws/codebuild/standard:1.0
Source:
Type: CODEPIPELINE

40. CodePipeline Webhook
CodePipelineWebhook:
Type: AWS::CodePipeline::Webhook
Properties:
Authentication: GITHUB_HMAC
AuthenticationConfiguration:
SecretToken: '{{resolve:ssm:gitHubToken:1}}'
Filters:
- JsonPath: "$.ref"
MatchEquals: "refs/heads/{Branch}"
- JsonPath: "$.commits[*].modified[*]"
MatchEquals: !Ref FileModified
Name: "code-pipeline-webhook"
RegisterWithThirdParty: true
TargetAction: SourceAction
TargetPipeline: !Ref CodePipeline
TargetPipelineVersion: !GetAtt CodePipeline.Version

41. Lambda deployment unified approach
LAMBDA_HANDLER_VENDOR=$(LAMBDA_HANDLER_BATCH_$(VENDOR))
# Deploy Lambda template to AWS
aws cloudformation deploy --no-fail-on-empty-changeset
--stack-name $(STACK_LAMBDA_BATCH_METRICS_VENDOR)
--template-file ./lambda-
app/target/classes/$(TEMPLATE_LAMBDA_BATCH_METRICS)
--parameter-overrides "Environment=$(ENV_KEY)"
"DataSourceSuffix=$(SUFFIX_DATA_SOURCE_VENDOR)"
"LambdaHandler=$(LAMBDA_HANDLER_VENDOR)"
"LambdaFunctionName=$(FUNCTION_VENDOR)"
"LambdaScheduleExpression=rate(1 hour)"
--capabilities CAPABILITY_NAMED_IAM
Parameters are defined in separate Makefiles configured
for each vendor separately.
Vendor key is passed as parameter to command.

42. AWS Serverless
in practice

43. Serverless web application with API Gateway
Amazon S3
API Gateway AWS Lambda
Amazon
CloudFront
Amazon S3 stores all
the static content
API Gateway handles all
the application routing
Lambda runs all the
back-end logic
CloudFront acts as CDN and
is typically used to front this

44. Serverless web application with API Gateway
AWS Data Pipeline AWS Lambda
Amazon S3 acts as
a storage for new
coming data
AWS Data Pipeline
ingests new data by
scheduled interval
Lambda performs final
processing on the data
Third-party data
providers
Third-party data
providers push data to
the respective bucket
Amazon S3
CloudWatch events
(time-based)
Amazon Redshift
Final data storage
Grafana
(visualization)

45. Monitoring and
extra cases

46. Lambda monitoring
Lambda monitoring

47. Lambda monitoring

48. Lambda cold start
What is a cold start?
 When running a serverless function, it will stay active (hot) as long as
you're running it
 After a period of inactivity, your cloud provider will drop the
container, and your function will become inactive (cold)
 A cold start happens when you execute an inactive function. The
delay comes from your cloud provider provisioning your selected
runtime container and then running your function
 This process will considerably increase your execution time
!!! Provisioning of the function's container can take > 5 seconds.
That makes it impossible to guarantee < 1 second latency.

49. Lambda warm-up
How to keep Lambda warm?
 Create scheduled event to invoke Lambda in configured time interval
to keep the force the container to stay alive
 In case of Serverless Framework there’s serverless-plugin-warmup
which provides a possibility to keep Lambda warm
!!! Containers are not reused after ~ 15 minutes of inactivity.
Knowing the system features will help to answer the question
whether the warmup is needed.

50. Lambda pitfalls
Lambda function not invoked by service:
Lambda permissions must be configured to allow invocations
by certain service
Function fails by timeout or memory lack:
Timeout and MemorySize settings should be explicitly stated.
In most cases it’s better to increase Memory Size
Exception occurs during the call inside the function:
In case Lambda performs access to a service, there should be
related permissions configured in Lambda role
Logs don’t appear in CloudWatch:
Function needs permissions to call CloudWatch Logs.
Execution role has to be updated to grant the latter

51. Summary
 Serverless approach allows to pay for usage and save the money
 Fits to suitable business cases where no dedicated servers are required
 Serverless is suitable in case service can be encapsulated in single function
 No provisioning and maintenance from your side
 Easy local development and testing
 Wide range of AWS tools to build Serverless applications

52. Questions?