The document discusses serverless computing using AWS Lambda. It begins with an overview of the evolution from monolithic applications to microservices and containerization. It then covers common use cases for serverless applications including web applications, data processing, chatbots, backends, and IT automation. The document demonstrates AWS Lambda functionality through examples and demos of file processing, stream processing, and using Lambda with Amazon S3 and API Gateway. It also discusses serverless frameworks, pricing and limits of AWS Lambda, and tools for monitoring serverless applications.

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Getting Started with Serverless
Computing Using AWS Lambda
Burak ÜNÜVAR
AWS Account Manager, SA Pro
• Compute Evolution : Monolith to Microservices
• Use Cases and References
• Intro to AWS Lambda with Demonstrations
• Pricing and Limits
• Serverless Frameworks and Monitoring

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CORE SERVICES
Integrated Networking
Rules Engine
Device Shadows
Device SDKs
Device Gateway
Registry
Local Compute
Custom Model
Training & Hosting
Conversational Chatbots
Virtual Desktops
App Streaming
Schema Conversion
Image & Scene
Recognition
Sharing &
Collaboration
Exabyte-Scale
Data Migration
Text to Speech
Corporate Email Application Migration
Database Migration
Regions
Availability Zones
Points of Presence
Data Warehousing
Business Intelligence
Elasticsearch
Hadoop/Spark
Data Pipelines
Streaming Data
Collection
ETL
Streaming Data
Analysis
Interactive SQL
Queries
Queuing & Notifications
Workflow
Email
Transcoding
Deep Learning
(Apache MXNet,
TensorFlow, & others)
Server MigrationCommunications
MARKETPLACE
Business Apps Business Intelligence DevOps Tools Security Networking StorageDatabases
API Gateway
Single Integrated
Console
Identity
Sync
Mobile Analytics
Mobile App Testing
Targeted Push
Notifications
One-click App
Deployment
DevOps Resource
Management
Application Lifecycle
Management
Containers
Triggers
Resource Templates
Build & Test
Analyze & Debug
Identity
Management
Key Management
& Storage
Monitoring &
Logs
Configuration
Compliance
Web Application
Firewall
Assessment
& Reporting
Resource & Usage
Auditing
Access Control
Account
Grouping
DDOS
Protection
TECHNICAL & BUSINESS SUPPORT
Support
Professional
Services
Optimization
Guidance
Partner
Ecosystem
Training &
Certification
Solutions Management Account Management
Security & Billing
Reports
Personalized
Dashboard
Monitoring
Manage
Resources
Data Integration
Integrated Identity &
Access
Integrated Resource &
Deployment Management
Integrated Devices
& Edge Systems
Resource
Templates
Configuration
Tracking
Server
Management
Service
Catalogue
Search
MIGRATIONHYBRID ARCHITECTUREENTERPRISE APPSMACHINE LEARNINGIoTMOBILE SERVICESDEV OPSANALYTICS
APP SERVICES
INFRASTRUCTURE SECURITY & COMPLIANCE MANAGEMENT TOOLS
Compute
VMs, Auto-scaling, Load
Balancing, Containers,
Virtual Private Servers,
Batch Computing, Cloud
Functions,Elastic GPUs,
Edge Computing
Storage
Object, Blocks,File, Archivals,
Import/Export, Exabyte-scale
data transfer
CDN
Databases
Relational, NoSQL,
Caching, Migration,
PostgreSQL compatible
Networking
VPC, DX, DNS
Facial Recognition &
Analysis
Facial Search
Patching
Contact Center
M OST ROBUST, FULLY FEATURED TEC H NOLOGY INFRASTRUC TURE PLATFORM

3. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark
Serverless is an operational model that spans many
different categories of services
AWS
Lambda
AWS
Fargate
Amazon
API Gateway
Amazon
SNS
Amazon
SQS
AWS
Step Functions
COMPUTE
DATA STORES
INTEGRATION
Amazon
Aurora
Serverless
Amazon
S3
Amazon
DynamoDB
AWS
AppSync
*** Continuous scaling *** Fault tolerance built-in *** Event-driven *** Pay per usage *** Zero maintenance

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Computing evolution – A paradigm shift
FOCUS ON BUSINESS LOGIC
LEVELOFABSTRACTION
Virtual Servers
in Datacenters
Virtual Servers
in Datacenters
Physical Machines
Virtual Machines
Containerization
AWS Lambda
AWS Fargate

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When the impact of change is small,
release velocity can increase
Monolith
Does everything
Microservices
Does one thing
• API driven request response
patterns
• Event driven patterns
• Data streaming patterns

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Development transformation at Amazon: 2001–2002
monolithic application
+ teams
2001
Lesson learned: decompose for agility
2002
microservices
+ 2 pizza teams
• Full ownership
• Full accountability
• “DevOps”
• Focused innovation

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Common serverless use cases
Web
Applications
• Static
websites
• Complex web
apps
• Packages for
Flask and
Express
Data
Processing
• Real time
• MapReduce
• Batch
Chatbots
• Powering
chatbot logic
Backends
• Apps &
services
• Mobile
• IoT
Amazon Alexa
• Powering
voice-enabled
apps
• Alexa Skills
Kit
IT Automation
• Policy engines
• Extending
AWS services
• Infrastructure
management
© 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.

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Sample Use Case 1 : REAL-TIME FILE PROCESSING

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Sample Use Case 2 : STREAM PROCESSING
Reference Architecture: Sample code

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Sample Use Case 3 : MOBILE AND WEB APPLICATIONS
Reference Architecture: Sample code

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AWS customers are pioneer ing modern
applicat ions

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SERVICES (ANYTHING)
Changes in
data state
Requests to
endpoints
Changes in
resource state
EVENT SOURCE FUNCTION
Node.js
Python
Java
C#
Go (coming soon)
Using AWS Lambda

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Demo 1 : Welcome to Amazon Lambda
Bring your own code
• Node.js, Java, Python,
C#,Go ...
• Bring your own libraries
(even native ones)
Simple resource model
• Select power rating
from 128 MB to 3 GB
• Timeout up to 15min
Flexible use
• Synchronous or
asynchronous
• Integrated with other
AWS services
Event Sources and Logs
• Amazon S3, API
Gateway, DynamoDB...
• Cloudwatch and logs
• Layers

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Fine-grained pricing : Never pay for idle
Buy compute time in 100ms increments
Low request charge
No hourly, daily, or monthly minimums
No per-device fees
Free Tier
1M requests and 400,000 GB of compute.
Every month, every customer.
© 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.

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AWS Lambda Limits
Memory Size : 128 MB to 3,008 MB, in 64 MB increments.
Ephemeral Disk Capacity : 512 MB
Timeout : 900 seconds or 15 Minutes
Concurrent executions : 1000
Deployment Packagesize : 50MB zip, 250MB unzipped, 3MB via c9
© 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
https://docs.aws.amazon.com/lambda/latest/dg/limits.html

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Demo 2 : Intro to Amazon API Gateway
https://aws.amazon.com/getting-started/projects/build-serverless-web-app-lambda-apigateway-s3-
dynamodb-cognito/

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Demo 3 : Using AWS Lambda with Amazon S3
https://docs.aws.amazon.com/lambda/latest/dg/with-s3.html

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AWS Serverless Application Model (AWS SAM)
Template-driven resource management model
optimized for serverless
New serverless resource types: Functions, APIs,
and tables
Supports anything AWS CloudFormation
supports
Open specification (Apache 2.0)
https://github.com/awslabs/serverless-application-model

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Useful Frameworks
Chalice
https://serverless.com/framework/docs/providers/aws/guide/intro/

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AWS X-Ray is Built for Modern Applications
Analyze and debug
issues quickly
End-to-end view of
individual services
Identify customer
impact
Support for
Serverless

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Serverless Observability with Thundra
● Tricky: Understanding the async structure of serverless environments.
● Hard: Reduce the MTTR in serverless environments.
● Impossible: To use the already existing APM for Lambda because they’re
not lightweight.
Thundra aims to resolve the issues below by
providing light-weight libraries in Java, Node.js,
Python, .NET, and Go. With Thundra, you can
both have an overall idea in the most complex
architecture and have the power of debugging the
code even line-by-line. Plug it with Lambda
Layers and using well-known deployment tools.

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Thank you very
much for listening!
For demos : https://github.com/burakunuvar/aws-lambda-webinar