The document discusses best practices for accelerating the transformation to mature software manufacturing using DevOps principles. It recommends adopting modern approaches like microservices, serverless architectures, infrastructure as code, and event-driven architectures to increase speed and agility. Automating testing and deployments through continuous integration/delivery (CI/CD) pipelines is key. The document advocates treating infrastructure like code and using tools like AWS CodePipeline and GitLab to enable self-service platforms and faster delivery through automation.

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Born for DevOps CI CD:
Accelerating the Transformation to
Mature Software Manufacturing
Darwin Sanoy, Senior Solutions Architect, GitLab
James Bland, Ph.D., Sr. Solutions Architect, AWS

2. © 2020, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
What is DevOps?
DevOps is the combination of cultural philosophies,
processes, people, and technology that increases an
organization’s ability to deliver applications and services
at high velocity: evolving and improving products at a
faster pace than organizations using traditional software
development and infrastructure management processes.
This speed enables organizations to better serve their
customers and compete more effectively in the market.

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What is DevOps today
DevOps = Modernization

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• Shrink the scope
• Offload the undifferentiated pieces
• Choose the right tool for the job
• Automate everything
A modern approach allows you to:

5. © 2020, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Why are customers choosing to build modern apps?
Faster to
Market
More reliable
applications
Increased rate of
innovation
Reduced
costs

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Best practices from AWS

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Two-pizza teams are fast & agile
• Full ownership & autonomy
• You build it, you run it
• DevOps – small, nimble teams
• Focused innovation

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Structure apps as collections of microservices
When the impact of change is small,
release velocity can increase
Monolithic application
Does everything
Shared release pipeline
Rigid scaling
High impact of change
Hard to adopt new technologies
Microservices
Does one thing
Independent deployments
Independent scaling
Small impact of change
Choice of technology

9. © 2020, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Structure apps as collections of microservices
APIs and decoupled communications enable automation
and improves reliability
FUNCTION
API
API
MICROSERVICE
FUNCTION
EVENT
API
MICROSERVICE
EVENT
API
MICROSERVICE
APPLICATION

10. © 2020, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Use code to model applications and infrastructure
Treating everything as software increases the speed and
agility of infrastructure deployments
Design
Write application
code
Create infrastructure
templates
Create stacks Iterate

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LEVELOFABSTRACTION
FOCUS ON BUSINESS LOGIC
SERVERLESS
P H Y S IC A L
M A C H IN E S
V IR T U A L
M A C H IN E S
C O N T A IN E R IZ A T IO
N
AWS
Lambda
AWS
Fargate
• Continuous scaling
• Fault tolerance built-in
• Pay for value
• Zero maintenance
• Focus on business value
Serverless architectures provide the greatest agility with the least effort

12. © 2020, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Directed
Commands
Observable
Events
Event-driven architectures
Events are observable, not directed

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Event-driven Benefits: Break up the work
Decoupled and
distributed
Decrease waste Pay for value
Event-driven architectures

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Creating powerful self-service platforms
that enable builders to use the right tool for
the right job
Self-service platforms without gatekeepers

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developers
delivery pipelines
services
monitorreleasetestbuild
Deployment: Monolith development lifecycle

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developers services
monitorreleasetestbuild
delivery pipelines
monitorreleasetestbuild
monitorreleasetestbuild
monitorreleasetestbuild
monitorreleasetestbuild
monitorreleasetestbuild
Deployment: Microservice development lifecycle

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Security in the CI/CD
pipeline
Artifact validation
Static code analysis
Security of the CI/CD
pipeline
Access roles
Hardening build
servers/nodes
1 2
Automated and Secure Pipelines

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A shift to microservices
• Single-purpose
• Connect only through hardened APIs
• Largely “black boxes” to each other
• Business logic and data only accessible
through APIs

19. © 2020, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Deployment at scale
1,000s of
teams
Micro-
services
CI/CD Serverless = 190Million
Deployments / Year

20. © 2020, Amazon Web Services, Inc. or its Affiliates.
Want to learn more

21. © 2020, Amazon Web Services, Inc. or its Affiliates.
Architecture, software delivery, and operations
By Amazon’s senior technical executives and engineers
Real-world practices with detailed explanations
Content available for free on the website
The Amazon Builders’ Library
How Amazon builds and operates software

22. © 2020, Amazon Web Services, Inc. or its Affiliates.
AWS Modernization Workshops
Curated workshops created by AWS Partners
https://awsworkshop.io

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How To Have a Tortured Software Manufacturing Transformation
Avoiding The DevSecOps Russian Nesting Doll
Born for DevOps CI CD
Accelerating the Transformation to a Mature Culture of Software Manufacturing
Parallel Worlds: The Evolution of Automated Manufacturing
Inherent DevOps Transformation Throughput Limits
The Russian Nesting Doll Effect (Matryoshka)
GitLab and AWS – Better Together!

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Everywhere Else Do Engineered Automation
(as Much as Possible)
Focus Craftsmanship On Innovations That Delight Customers
Henry Ford: Manufacturing Transformation

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Benefits of Pulling A “Henry Ford” On Software Manufacturing
● Speed of innovations to market
● Improving predictability and quality
● Lowering cost of production and maintenance (after surge investment)
● Encoding of tacit human knowledge into Intellectual Property
● Removal of drudgery
Let’s look at some key elements affecting the transition from
the practice of software craftmanship to
the practice of software manufacturing.

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Car Manufacturing as Craft
Challenges:
● Skilling Workers (Skill Breadth=Time)
● Scaling Production
● Consistent Quality
● Serviceability of Product
● Know How as a Corporate Asset
Integrated: Know How + Manufacturing
Labor

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Automation Maturity Wave 1
Making product from engineered plans using an assembly line
Product
Engineer

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Key Craft Transformations and Limits
- Tacit Knowledge
- Individual Knowledge
- Implicit processes
- Product Designed for Craft Assembly
- Integrated Manufacturing Labor (Drudgery)
- Explicit Knowledge
- Shared Knowledge
- Explicit processes
- Product Re-Designed for Automated Assembly
- Externalized & Automated Manufacturing Labor
Maximum Bandwidth of
Deep Know How Extraction
Maximum Bandwidth of Reskilling
Product Refactoring for Assembly Line Production
Crafting Engineering & Automation
Inherent Limits (While Continuing To Deliver Customer Value with Current Means)

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The Russian Nesting Doll Effect
Maturity Level 1
Product Engineered From
Standard Parts
Maturity Level 4: The Above for Infrastructure as Code (IaC)
Product Craft
Iterate!
Maturity Level 2
Parts Build Automation
Machine Op Craft
Maturity Level 3
Assembly Lines
Engineered from
Standard Components
or Functional
Templates
Factory Craft
(DevOps ToolChain)

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DevSecOps / AppSec - Skip the Russian Dolls
● Many companies efforts are in a Craftsmanship stage
○ Limited automation
○ Throughput limited by size of Security team
○ Manual reports, reviews and processes.
Do a 3 Year DevSecOps Integrated Maturity & TCO Plan to compare
Mature DIY DevSecOps to GitLab’s Prefabricated DevSecOps Assembly Line (Maturity Level 3)
● Multiple tools knitted together with complex manual
processes and some hand off automation
Late discoveries due to non-planned journey to maturity:
● Consumption based scanning license models
● Tool implementation & training costs
● Cost of non-integrated CI code review
Why Play With Dolls At All?

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GitLab Prefabricated Sub-
Assemblies (e.g. SAST
Scanning)
Primitives to Build Sub-Assemblies and Lines Templates
Your Prefabricated
Sub-Assemblies &
Lines
Prefabricated Partner
Sub-Assemblies
Prefabricated Assembly Lines (AutoDevOps, DevSecOps)
Skip the Russian Dolls
by starting as high in this
stack as you can.
Unboxing The
GitLab Factory
Making Kit

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Self-Managed SaaS
3 Paid
Enterprise Tiers
Free Enterprise
(Public, OSS,
Edu, Startup)
Free
Community
Edition
(100% OSS)
Lots of Options To Get Involved
30 Day Trials
- Self-Run
- Sales Assisted

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Production Grade CI / CD Automation
Prefabricated
Modular
Scalable
Highly Available
100% CI CD Automated
Enables Building Your Own CI CD Primitives When Required
Pipeline As Code

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How to Have a Tortured Software Manufacturing Transformation
● Not accounting for both coding domains: Application Coding (CI), Infrastructure Coding (CD)
● Not skipping the DevSecOps Russian Doll
● Not allocating surge time and resources for culture, skill and technical transformation
● Not allocating refactor time for product code that is not DevOps assembly line friendly (12-
factor.net)
● Not driving knowledge extraction, skilling or product refactoring to done-done.
● Not automating all the Russian dolls (Is QA or AppSec still the semi-manual bottleneck?)
● Not using off the shelf tooling to skip Craft => Engineering cycles as much as possible
● Not remembering craft is what creates all innovation - you must have it - but not where
industry has or is reducing it to engineered automation.

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All Branches
SCM
CI Job
BranchA
CI Job
BranchB
CI Job CI Job CD Integration
Job
BranchA Background AWS Services Config (Per-Service + Per-Branch / Per-Pipeline)
IAM Role
Per Service
BranchA CodePipeline Per-Branch / Per-Pipeline)
Code
Pipeline
CodeBuild
CodeCommit
CodeDeployCodeBuild CodeBuild
S3
CloudWatch CloudFormation IAM
CodeDeploy
3. Repo Mirroring Trigger
- Full CodePipeline Integration
- Leverage Superior GitLab SCM
- Phased Migration Step (migration)
1. CodeDeploy Direct Integration
- for Superior AWS Specific CD
- for true Build/Pipeline as Code
- No IaC for pipelines
- Dynamic, per-branch pipelines
Integration Options
ECR
2. Artifact Depositing Trigger
- CodePipeline for Deploy Only
- Leverage Superior GitLab SCM
- for Superior AWS Specific CD
- S3 or ECR triggers
S3
AWS
Amplify
AWS Elastic
Beanstalk

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Feature (many) (with builds)
Rich Workflow Gating Controls for “Code Review” and “Environment Change Control”
Push Rules
(entire repo)
Pre-prod (Deploy)
Environment Deployment Branches
Integration (Code Review & Validate)
Code Review
Branch Protections
w/ Custom Groups
Stage (Deploy Branch)
Independent Branch Protections by Role by Users & Custom Groups by CODEOWNERS
Prod (Deploy)
Security & Compliance
Scanning & Dashboard
Custom Groups
BS
GU
Verified Committers
Signed Commits
SP
Lock Files / Dirs SP
BSFC SP
Repo-Wide
Merge Approvals
Tag Protections
w/ Custom Groups
BS
BS
Multiple Merge Approval Rules
w/ Custom Groups SP
GitLab CI
FC
BS
AWS
CodeDeploy
Amazon
ECS
AWS
CodeDeploy
AWS
CodePipelin
e
Amazon
ECS AWS
CodeDeploy
AWS
CodePipelin
eAmazon
ECS
AWS
CodeDeploy
AWS
CodePipelin
e
Amazon
ECS
ECS is built in,
CodeDeploy and CodePipeline
are Easy to Add

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Resources
Wire GitLab and
AWS CodePipeline Together
Integrate GitLab with AWS CodePipeline
https://docs.gitlab.com/ee/user/project/repository/repository_mirroring.html
Rich Change Controls for Building Workflows You Can Trust
https://www.youtube.com/watch?v=uW95PV8d-w8

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Solution Architects
Partnering In Your
Success With GitLab
Need Help Understanding or Trying Out GitLab CI?
https://about.gitlab.com/sales/
Darwin Sanoy, Senior Solutions Architect, GitLab
James Bland, Ph.D., Sr. Solutions Architect, AWS
DarwinJS @DarwinTheorizes missionimpossiblecode.io linkedin.com/in/DarwinSanoy
linkedin.com/in/jamesbland123