© 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark
Tom Laszewski – Enterprise Technologist
March 12, 2019
AWS Application
Modernization
Strangler Pattern

© 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark
Legacy

© 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark
Strangler Pattern

© 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark
Strangler Pattern
1. Incrementally migrate a legacy system
2. Gradually replacing specific pieces of functionality
with new applications and services
3. Features from the legacy system are replaced by
the new system features eventually
4. Strangling the old system and allowing you to
decommission it

© 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark
Strangler Pattern – When not to use
1. When requests to the back-end system cannot be
intercepted
2. For smaller systems where the complexity of
wholesale replacement is low

© 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark
Data-driven augmentation
COBOL, PL/I, Assembler, JCL, Rexx
CICS IMSTM Batch
Data files
(VSAM…) Database
(DB2, IMS DB…)
Monitoring
RACF
Security
Scheduler
Output
Printing
z/OS
LPARs PR/SM
IBM Z
Amazon Kinesis
Streams
Reduce MIPS usage for new services
Eventually replace some mainframe functions
Innovate with Machine Learning or APIs
Augment the mainframe with new functions
Expand from the data analytics enablement
Leverage core business data from mainframe
Amazon Lambda
microservices
Amazon
Machine Learning
Amazon
DynamoDB
AmazonAPI
Gateway
Amazon
Aurora DB

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Batch job migration
JCL, Rexx, Sort, Report
Utilities Logs MQ
Data files
(VSAM…) Database
(DB2, IMS DB…)
Monitoring
RACF
Security
Scheduler
Output
Printing
z/OS
LPARs PR/SM
IBM Z
Amazon
DynamoDB
Amazon
Redshift
Amazon Lambda
processing
Amazon
QuickSight
Output files
Amazon EMR
processing
Reports
Amazon Kinesis
Streams
Amazon S3
storage
Batch job candidates:
 Data transformation jobs
 Data distribution and transmission jobs
 Reporting and archival jobs
 Data warehouse load jobs
Periodic or near real-time batch processing
Remove mainframe processing (MIPS)
Enable agile data processing, visualization
Expand data analytics scope and value
Leverage cloud-native architecture

© 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark
1. Use API Gateway to front existing backends
InternetClient
API Gateway
Hosted service 1
Hosted service 2
AWS cloud
corporate data center

© 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark
2. Lift & shift service to AWS
InternetClient
API Gateway
Hosted service 1
Service 2
on EC2
AWS cloud
corporate data center

© 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark
3. Lift & re-architect
InternetClient
API Gateway
Service 2
on EC2
AWS cloud
Microservice 1
Microservice 2
Microservice 3
Re-architected Service 1
Applying theTwelve-Factor App Methodology to
ServerlessApplications

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© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.

© 2019, 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.

© 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark
© 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Services Used
• Amazon S3
– Used to store the file feeds coming in from the Core Systems, also
used for archiving these files for now.
• Amazon SNS
– notification to humans
– notification to Lambdas to signal file arrival
• Lambda
– Event based architecture where compute resources are created only
when needed
– Orchestration layer for batch jobs (DAILY, MEMO, and HISTORICAL)
• Amazon CloudWatch rule
– used to check for batch work
• Amazon RDS
– Used to persist the state of batch jobs
• EC2/ASG/ELB
– Used to run spring-batch jobs, spring-boot containers for
MQ Listener and APIs.
• DynamoDB
– Used to store the transaction data
• CloudWatch
– Used to collect application logs, server logs, application
metrics, etc.
• IAM/KMS
– Used to manage encryption keys

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Transactions Hub Batch—Serverless
DynamoDB

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Statements API as Lambda
DynamoDB DynamoDB
AWS Lambda AWS Lambda

© 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark
Vanguard
Features:
• Replicate data to the
cloud
• Refactor the monolithic
apps so web pages
makeAJAX calls to
microservices
• Migrate batch
processes to the cloud,
using data in the cloud
• Gold copy in cloud—
Reverse replication
• Treat mainframe record
keeping systems as
bounded contexts
o Integrate with
them from the
cloud
μservice
CDC
CDC
μservice
Replicator
Dispatcher
DB Writers
Event Writers
Big Data
ExtendedHub

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Fender - Monolith Architecture
Browser
Juniper
Firewall
F5 Load
Balancer
Web Servers (Apache)
SQL Server
NetApp
(SAN)
Solr Server Master
Solr Server Slave
ATG

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Fender – Cloud Native Architecture
users Classic Load
Balancer
Amazon
ElastiCache
Postgre
SQL
instance
Amazon
SES
Amazon
S3
Amazon
CloudFront
Order
Creation
Invoices
Online
Payments
Warranty
Claims
Finance
Details
API
Gateway
AWS Direct
Connect
Amazon
CloudFront
Amazon
DynamoDB

© 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark
Lift and Forget, Containers, and Serverless
• Where to start?
• What to break out?
• Dependencies?
• Works as expected?
• Users happy?
• Does it scale?
• Does it perform?
• How to automate?
• Works as expected?
• Users happy?
• How to optimize?
Does it perform?
• How to automate?
? ? ?
?
?
?
?
? ?
?
?
??
? ?
?
?
? ?
? ?
?
? ? ?
?
?
?
?
From
On-Premise Monolith
Via
Containerized Services
To
Functions &Cloud Services

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Dynatrace – Analysis and Discovery
Dynatrace Smartscape
We tell youWHAT to migrate andWHERE to break the
monolith!
Dynatrace AI
Automatic End User, Service and Infrastructure Root Cause
Analysis
Dynatrace AutomationAPI
Automate Rollout in your Containers & Functions.
Automate Shift-Left and Self-Healing
• Where to start?
• What to break out?
• Dependencies?
• Works as expected?
• Users happy?
• Does it scale?
• Does it perform?
• Works as expected?
• Users happy?
• How to optimize?
Does it perform?
• How to automate?

© 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark
Dynatrace – Decide what to migrate
Dynatrace
Smartscape
• Auto-
dependency
mapping of
internal &
external
services
• Auto-load
detection and
baselining
• Auto-resource
consumption
detection

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Reference Material
Cloud Native Architectures : Design high-availability and cost-effective applications
for the cloud
• https://tinyurl.com/yczo3goa
The Art of Scalability
•http://theartofscalability.com/
Pros and Cons of a MicroServices Architecture talk at AWS ReInvent
•http://www.slideshare.net/stonse/pros-and-cons-of-a-microservices-
architecture-talk-at-aws-reinvent
MicroServices at Netflix - challenges of scale
•http://www.slideshare.net/stonse/microservices-at-netflix
From SOA to MSA - Creating Adaptive and Innovation Supportive Architecture and
Organization
•http://www.slideshare.net/yang75108/from-soa-tomsa

© 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark
Reference Material
Microservices Resource Guide
•http://martinfowler.com/microservices/
•https://queue.acm.org/detail.cfm?id=1142065
Pattern: Monolithic Architecture
•http://microservices.io/patterns/monolithic.html
Pattern: Microservices Architecture
•http://microservices.io/patterns/microservices.html
Migrating to Cloud-Native Application Architectures
•by Matt Stine, O’Reilly Media, Inc.
12 Factor App
•http://12factor.net/