Innovation with Open Sources and App Modernization for Developers | Ian Y. Choi

1. Innovation with Open Sources and App
Modernization for Developers
Ian Choi
Developer Relations,
Microsoft (Korea, APAC)
August 24, 2019

2. Innovation with Open Sources and App
Modernization for Developers
Ian Choi
August 24, 2019

3. © Microsoft Corporation
목차
0. Preface
1. Challenge
2. Innovation and app modernization with open source tools
3. Top scenarios for containers + app modernization journey
4. Closing

4. 0. Preface

5. © Microsoft Corporation
Introduction – Ian Choi
• Developer Audience Product Marketing Manager at Microsoft (from Nov 2018)
• OpenStack community
✓ Internationalization (I18n) Project Team Lead
✓ Korea user group leader (from Jan 2017)

6. © Microsoft Corporation
The journey to the cloud & containers with open sources
“What your application works with”
Data
“What your application does”
Code
“What your application runs on”
Infrastructure
Unified Management • Security • Governance • Tools • DevOps
Migrate • Innovate
Software Development • Open Sources • Enterprise
collaboration

7. 1. Challenge

8. © Microsoft Corporation
Hybrid
by design
Infrastructure
for all workloads
Secure and
well-managed
Cost
effective
Cloud migration advantages

9. Cloud migration vs. modernization
MIGRATE MODERNIZE
Redeploy as-is to cloud
• Reduce Capex
• Free up datacenter space
• Quick cloud ROI
IaaS
IaaS: 435% ROI, 73% reduction in
datacenterfootprintand83% reduced
IT outsourcing cost.1
Minimally alter to take better
advantage of cloud
• Faster, shorter, updates
• Code portability
• Greater cloud efficiency
(resources, speed, cost)
PaaS
Containers
PaaS: 466% ROI, 80% time saved, 5.91M NPV, 50% faster deployments.1
Container: 13x more releases, 10x cost reduction, 65% faster developer onboarding, 62% better availability.2
Materially alter/decompose
application to services
• App scale and agility
• Easier adoption of new cloud
capabilities
• Mix technology stacks
PaaS
Serverless
Microservices
New code written with cloud
native approach
• Accelerate innovation
• Build apps faster
• Reduce operational cost
Description
Drivers
Technologies
Results

10. Applications have shifted to the cloud
Past
Long application cycles
Monolithic apps
Servers and VMs
Less data
Desktop
Distinct infrastructure and operations teams
Today
Rapid innovation
Loosely-coupled apps, microservices, and containers
Serverless
Big Data
Mobile
Service-focused DevOps teams
CaaS
Container Platform
On-Premises
Infrastructure Platform
PaaS
Application Platform
FaaS
Serverless Platform
IaaS
Infrastructure Platform
“lift & shift”

11. Applications have shifted to the cloud
Past
Long application cycles
Monolithic apps
Servers and VMs
Less data
Desktop
Distinct infrastructure and operations teams
Today
Rapid innovation
Loosely-coupled apps, microservices, and containers
Serverless
Big Data
Mobile
Service-focused DevOps teams
CaaS
Container Platform
On-Premises
Infrastructure Platform
PaaS
Application Platform
FaaS
Serverless Platform
IaaS
Infrastructure Platform
“lift & shift”

12. 1. Lift& Shift 2. Refactoring
3. Rearchitecting 4. Rebuild/New
Approach on App migration & modernization

13. Applications have shifted to the cloud
Past
Long application cycles
Monolithic apps
Servers and VMs
Less data
Desktop
Distinct infrastructure and operations teams
Today
Rapid innovation
Loosely-coupled apps, microservices, and containers
Serverless
Big Data
Mobile
Service-focused DevOps teams
CaaS
Container Platform
On-Premises
Infrastructure Platform
PaaS
Application Platform
FaaS
Serverless Platform
IaaS
Infrastructure Platform
“lift & shift”

14. On-premises
Cloud
Anywhere
Monolith
Microservice
Any app
.Net
Java
Python
Node
Any language
Linux
Windows
Any OS
The benefits of using containers

15. Kubernetes momentum
For the organizations running
Kubernetes today, 77%1 of
those with more than 1,000
developers are running it in
production.
Larger companies
are leading the
adoption.
77%
“By 2020, more than 50% of enterprises
will run mission-critical, containerized
cloud-native applications in production.”
1Heptio: state of Kubernetes 2018

16. Applications have shifted to the cloud
Past
Long application cycles
Monolithic apps
Servers and VMs
Less data
Desktop
Distinct infrastructure and operations teams
Today
Rapid innovation
Loosely-coupled apps, microservices, and containers
Serverless
Big Data
Mobile
Service-focused DevOps teams
CaaS
Container Platform
On-Premises
Infrastructure Platform
PaaS
Application Platform
FaaS
Serverless Platform
IaaS
Infrastructure Platform
“lift & shift”

17. Kubernetes & DevOps: better together
DevOps
AKS
AKS
DevOps

18. Applications have shifted to the cloud
Past
Long application cycles
Monolithic apps
Servers and VMs
Less data
Desktop
Distinct infrastructure and operations teams
Today
Rapid innovation
Loosely-coupled apps, microservices, and containers
Serverless
Big Data
Mobile
Service-focused DevOps teams
CaaS
Container Platform
On-Premises
Infrastructure Platform
PaaS
Application Platform
FaaS
Serverless Platform
IaaS
Infrastructure Platform
“lift & shift”

19. Build on a secure, enterprise-grade platform
Secure network
communications with
VNET and network policy
Control access through
AAD and RBAC
Put guardrails in your
development process with
Azure Policy

20. 2. Innovation and app modernization
with open source tools

21. © Microsoft Corporation
DIY vs. Managed
vs.

22. Innovation with Open Source development: OpenStack

23. Innovation with Open Source development: OpenStack

24. From infrastructure to innovation
Responsibilities DIY with Kubernetes Managed Kubernetes
Containerization
Application iteration,
debugging
CI/CD
Cluster hosting
Cluster upgrade
Patching
Scaling
Monitoring and logging
Customer Example of Managed Kubernetes
: Microsoft Azure
Managed Kubernetes
empowers you to achieve more
Focus on your containers and
code, not the plumbing of them

25. Manage Kubernetes with ease
• Automated provisioning,
upgrades, patches
• High reliability, availability
• Easy, secure cluster scaling
• Self-healing
• API server monitoring
• At no charge
API server
Controller
Manager
Scheduler
etcd
Store
Cloud
Controller
Self-managed master node(s)
Customer VMs
App/
workload
definition
User
Docker
Pods
Docker
Pods
Docker
Pods
Docker
Pods
Docker
Pods
Schedule pods over
private tunnel
Kubernetes
API endpoint
Azure managed control plane
Infrastructure automation

26. Manage Kubernetes with ease
Azure Monitor
AKS production cluster
Microservices
Azure Container
Instances (ACI)
Pods
Virtual node
Availability Reliability
Highly available, reliable service with serverless scaling
Auto scaling

27. Accelerate containerized development
Kubernetes and DevOps
better together
Develop
• Native containers and Kubernetes support in IDE
• Remote debugging and iteration for multi-
containers
• Effective code merge
• Automatic containerization
Deliver
• CI/CD pipeline with automated tasks in a few
clicks
• Pre-configured canary deployment strategy
• In depth build and delivery process review and
integration testing
• Private registry with Helm support
Operate
• Out-of-box control plane telemetry, log
aggregation, and container health
• Declarative resource management
• Auto scaling
Inner loop
Test
Debug
Azure
DevSpaces
AKS dev
cluster
Azure Pipelines
Source
code control
Azure
Container
Registry
Helm chart
Container
image
AKS
production
cluster
Azure
Monitor
Scale
Terraform
Develop Deliver Operate

28. CI/CD for open sources - https://dev.azure.com/pypa/pip

29. 3. Top scenarios for containers +
app modernization journey

30. Top scenarios for containers + App modernization journey
Cost saving
without refactoring
your app
Lift and shift
to containers
Performance
Low latency
processing
Machine
learning
Portability
Build once,
run anywhere
IoT
Agility
Faster application
development
Microservices
Automation
Deliver code faster and
securely at scale
Secure DevOps

31. App modernization without code changes
Lift and shift to
containers
Microservices Machine learning IoT
• Speed application deployments
by using container technology
• Defend against infrastructure
failures with container
orchestration
• Increase agility with continuous
integration and continuous
delivery
Azure
Container
Registry
Existing
application
Kubernetes cluster
Cloud
Database
Modernized
application
Modernized
application
Modernized
application
CI/CD
Secure DevOps

32. App modernization without code changes
Lift and shift to
containers
Microservices Machine learning IoT
Capabilities
Azure
Container
Registry
Existing
application
Virtual network
AKS
Active
Directory
Database
for MySQL
Azure
Pipelines
Secure DevOps
2. Integrate AKS with Azure Pipelines or
other Kubernetes ecosystem tooling to
enable continuous integration/continuous
delivery (CI/CD)
3. Enhance security with Azure Active
Directory and RBAC to control access to
AKS resources
1. Use Azure Container Registry to store
container images and Helm charts for your
modernized applications, replicated
globally for low latency image serving

33. Microservices: for faster app development
• Independent deployments
• Improved scale and resource
utilization per service
• Smaller, focused teams
Lift and shift to
containers
Microservices Machine learning IoT
Monolithic
APP APP APP
Microservices
Large, all-inclusive app Small, independent services
Secure DevOps

34. Microservices for faster app development
Capabilities
Lift and shift to
containers
Microservices Machine learning IoT
https://github.com/Microsoft/SmartHotel360-
AKS-DevSpaces-Demo
Inner loop Source
code control
Azure
Container
Registry
Azure Pipeline/
DevOps Project
Auto-
build
Azure
Monitor
Test
Debug
Azure
DevSpaces
AKS dev
cluster
AKS production cluster
Pods
Container instances
Pods
CI/CD
Secure DevOps
4. Azure Monitor provides a single pane of
glass for monitoring over app telemetry,
cluster-to-container level health analytics.
3. Virtual node—a Virtual Kubelet
implementation—allows fast scaling of
services for unpredictable traffic.
2. Azure DevOps has native integration with
Helm and helps simplifying continuous
integration/continuous delivery (CI/CD)
1. Use Azure Dev Spaces to iteratively
develop, test, and debug microservices
targeted for AKS clusters.

35. Data scientist in a box
• Quick deployment and high
availability
• Low latency data processing
• Consistent environment across
test, control and production
Compute
Training
data
Algorithm
GPU-enabled VMs
AKS trained
model
AI model in
production
Developer
<>
Data
Scientist
Serve the
model
Lift and shift to
containers
Microservices Machine learning IoT Secure DevOps
https://github.com/Azure/kubeflow-labs

36. Data scientist in a box
Capabilities
https://github.com/Azure/kubeflow-labs
AKS
Kubeflow
Azure Blob
Storage
GPU-enabled
VMS
Azure
Container
Registry
ML model in
containers
Query the model for AI
features in app
Serve the model
in production
Parameter
server node
Worker
nodes
Data
scientist
App
developer
Lift and shift to
containers
Microservices Machine learning IoT Secure DevOps
1. Package ML model into a container and
publish to Azure Container Registry
2. Azure Blob Storage hosts training data
sets and trained model
3. Use Kubeflow to deploy training job to
AKS, distributed training job to AKS
includes Parameter servers and Worker
nodes
4. Serve production model using Kubeflow,
promoting a consistent environment
across test, control and production
5. AKS supports GPU enabled VM
6. Developer can build features querying the
model running in AKS cluster

37. Scalable Internet of Things solutions
• Portable code, runs anywhere
• Elastic scalability and
manageability
• Quick deployment and high
availability
Lift and shift to
containers
Microservices Machine learning IoT
AKS
Database
for MySQL
Azure
Cosmos DB
SQL
Database
IoT Hub
IoT Edge
devices
IoT Edge
Connector
Secure DevOps

38. Scalable Internet of Things solutions
Capabilities
Lift and shift to
containers
Microservices Machine learning IoT
Azure IoT Edge
Compress
Encrypt
Send to Cloud
Azure
Kubernetes cluster
Node
Docker
container
Docker
container
Node
Docker
container
Docker
container
Virtual node
IoT Edge
Provider
Docker
container
Docker
containers
Decrypt
Decompress
Send to Storage
2. Virtual node, an implementation
of Virtual Kubelet, serves as the translator
between cloud and Edge
3. IoT Edge Provider in virtual node redirects
containers to IoT Edge and extend AKS cluster
to target millions of edge devices
4. Consistent update, manage, and monitoring as
one unit in AKS using single pod definition
1. Azure IoT Edge encrypts data and send to
Azure, which then decrypts the data and
send to storage
Secure DevOps

39. Secure DevOps
Lift and shift to
containers
Microservices Machine learning IoT Secure DevOps
• Deliver code faster with
Kubernetes and CI/CD
• Accelerate the feedback loop
with constant monitoring
• Balance speed and security with
continuous security and deep
traceability
</>
Source
code
Build
Pipelines
Release
Pipelines
Kubernetes
cluster
Continuous
Integration
Continuous
Delivery
Deployment
strategies
Monitor &
logging
Monitor
Iterate

40. Accept
Deny
Release
3
Release
3
Release
N
Release
3
Release
2
Release
1
Azure
Pipelines
Azure
Pipelines
</>
Secure DevOps
Capabilities
Lift and shift to
containers
Microservices Machine learning IoT
1. Developers rapidly iterate, test, and debug different parts
of an application together in the same Kubernetes cluster
Secure DevOps
2. Code is merged into a GitHub repository, after which
automated builds and tests are run by Azure Pipelines
3. Container image is pushed to Azure Container Registry
8. App telemetry, container health monitoring, and real-time
log analytics are obtained using Azure Monitor
9. Insights used to address issues and fed into next sprint plans
4. Kubernetes clusters are provisioned using tools like Terraform;
Helm charts, installed by Terraform, define the desired state of
app resources and configurations
5. Operators enforce policies to govern deployments to the
AKS cluster
6. Release pipeline automatically executes pre-defined
deployment strategy with each code change
7. Policy enforcement and auditing is added to CI/CD pipeline
using Azure Policy
Inner loop
Azure
Container
Registry
Helm chart
Container
image
Azure
Monitor
Azure
Policy
Source
code control
sample code {
iterating.with.team
// in one
// isolated
environment
}
Test
Debug
Azure
DevSpaces
AKS dev
cluster


Terraform
AKS
production
cluster
v1
v2
App
telemetry
Container
health
Real-time
log analytics

41. Case: Deploy Azure ML models at scale
Azure Machine Learning service

42. Q: How much is this car worth?
Building your own AI models
Transforming Data into Intelligence

43. Prepare data Build and train Deploy
Building your own AI models
Transforming data into intelligence

44. Prepare data Build and train Deploy
Building your own AI models
Transforming data into intelligence

45. Building your own AI models
Step 1: Prepare data

46. Building your own AI models
Transforming data into intelligence
Prepare data Build and train Deploy

47. X
Y
Model
Building your own AI models
Step 2: Build and Train

48. Building your own AI models
Step 2: Build and train
Model
Accuracy

49. Building your own AI models
Transforming data into intelligence
Prepare data Build and train Deploy

50. Docker?
On-prem deployment
Azure Container Instance
Azure IoT edge
IoT accelerated targets
Project Brainwave (FPGAs)
Machine Learning
결과
Azure Managed Kubernetes Service
Building your own AI models
Step 3: Deploy
Azure
Azure
Azure
Azure
VM?

51. Building your own AI models
Transforming data into intelligence
Prepare data Build and train Deploy

52. SQL DB
Cosmos DB
Datawarehouse
Data lake
Blob storage
…
Building your own AI models
Transforming data into intelligence
Prepare data Build and train Deploy

53. 4. Closing

54. © Microsoft Corporation
The journey to the cloud & containers with open sources
“What your application works with”
Data
“What your application does”
Code
“What your application runs on”
Infrastructure
Unified Management • Security • Governance • Tools • DevOps
Migrate • Innovate
Software Development • Open Sources • Enterprise
collaboration

55. Packaging
& distribution
Scalability
& control
Kubernetes
developer tooling
Helm
CNAB
Virtual Kubelet Open Policy Agent
Draft
Brigade
VS Code Kubernetes Extensions
Duffle
Containerd
KEDA Service Mesh Interface
Microsoft contributions to the community

56. Microsoft contributions to the community
Top
code contributor to Windows
support in Kubernetes
68%
of Kubernetes users prefer Helm
55,000
monthly downloads of Helm
1of 3
top corporate contributors
3x
growth of employee
contributors within three years
Created the
Illustrated Children’s
Guide to Kubernetes,
now part of CNCF

57. 59
Thank you!