From Cloud to Edge: Why Cloud-Native Application Development Matters in Supporting Iot

From cloud to edge: Why cloud-native application development matters in supporting IoT

David Bericat Erik Jacobs Chief Architect Data Analytics (AI/ML) • Edge • IoT Principal Technical Marketing Manager, OpenShift Global Partner Solutions Cloud Platforms BU Red Hat Red Hat

Thursday May 9th THE INTERNET IS ALL THINGS YOU SIMPLY DON’T REALIZE IT YET... AGENDA

● What has Red Hat been doing in IoT

● From IoT to end-to-end Analytics (AI/ML) to Edge computing

● Red Hat’s next generation cloud-computing development

● Dreaming exercise: serverless & FaaS at the “edge” RED HAT’S IoT STRATEGY OVERVIEW

● Customers use our parts of our portfolio in a variety of ways to address IoT challenges on a hybrid cloud infrastructure.

● We do not claim to provide an IoT platform. We work with our commercial partner ecosystem to deﬁne more complete solutions and bring them to market.

● We take a leadership role in open source communities to build IoT technology.

Cloud Partner Open Ecosystem Source KEY FUNCTIONALITY FOR AN END-TO-END IoT ARCHITECTURE

Device Management Intelligent Edge Processing Advanced Analytics Business & Application & Connectivity & Analytics & Machine Learning Integration Securely connect, authenticate Apply analytics at the edge with Centralize IoT data processing, Enable integration with enterprise and and manage disparate machine learning and business rules analytics and machine learning business applications to bridge the connected devices that speak to enable local, low-latency decision to enable deep business insights and gap between OT and IT different protocols making actionable intelligence and reduce complexity

End-to-End Security & Compliance Tools to enable end-to-end data security, compliance, authorization and authentication OPEN END-TO-END IoT ARCHITECTURE INTEGRATING OT, IT , DATA MANAGEMENT, ANALYTICS &, APPLICATIONS

IoT IoT APPLICATION DEVELOPMENT, EDGE INTEGRATION HUB DELIVERY, & INTEGRATION

Cloud-native Traditional DATA MANAGEMENT & apps apps ANALYTICS PLATFORM

• Modular, secure, end-to-end architecture • Streaming analytics and machine learning public, private, hybrid cloud • Open, interoperable on hybrid cloud • Modern application development and agile integration END-TO-END ANALYTICS PUSHING AI/ML FROM CORE TO EDGE

Protocol Intelligent Translation Filtering Aggregation Routing APPLICATION DEVELOPMENT, CONNECTED IoT IoT DELIVERY, & INTEGRATION “THINGS” EDGE INTEGRATION HUB

Application Integration Cloud-native Traditional apps apps Application Telemetry Data Data

Real-Time Data ML Model Data Ingest Deep data Processing Storage analysis & Machine Data Actions Machine Real-Time Learning Analytics Security insights ML Model Learning Prediction / Alert DATA MANAGEMENT & ANALYTICS PLATFORM FUNCTIONALITY OVERVIEW

CONNECTED IoT IoT APPLICATION DEVELOPMENT, “THINGS” EDGE INTEGRATION HUB DELIVERY, & INTEGRATION App Cloud-native applications Traditional applications integration Developer ERP services IOT INTEGRATION Integration FRAMEWORK Management Orchestration & CRM IOT EDGE API mgmt FRAMEWORK Device DevOps DBs Field Telemetry management connectivity Device Telemetry connectivity CONTAINER-BASED Cloud APPLICATION PLATFORM connectivity Edge Data analytics Edge integration applications Machine DATA MANAGEMENT & ANALYTICS learning Management Telemetry CONTAINER-BASED Data Data APPLICATION PLATFORM engineering warehouse Security & Operational Data science governance database Machine Storage learning Machine learning model Services ENTERPRISE DATA HUB HOW RED HAT PORTFOLIO CAN HELP

CONNECTED IoT IoT APPLICATION DEVELOPMENT, “THINGS” EDGE INTEGRATION HUB DELIVERY, & INTEGRATION App integration

Apps Management

Edge Telemetry analytics Telemetry Machine learning

Management LINUX Telemetry

Machine learning model DATA MANAGEMENT & ANALYTICS AGILE INTEGRATION STANDARDIZING THE “WILD, WILD WEST”

CONNECTED IoT IoT APPLICATION DEVELOPMENT, “THINGS” EDGE INTEGRATION HUB DELIVERY, & INTEGRATION

Cloud-native Traditional MQTT applications applications Telemetry HTTP Integration AMQP & 1.0 API mgmt LoRaWAN Commands

CoAP CONTAINER-BASED APPLICATION PLATFORM Device Registry DATA MANAGEMENT & ANALYTICS PLATFORM

public, private, hybrid cloud AGILE INTEGRATION STANDARDIZING THE “WILD, WILD WEST”

CONNECTED IoT IoT APPLICATION DEVELOPMENT, “THINGS” EDGE INTEGRATION HUB DELIVERY, & INTEGRATION

Cloud-native Traditional applications applications MQTT Interconnect Integration & HTTP API mgmt

LoRaWAN Broker CONTAINER-BASED APPLICATION PLATFORM CoAP Streams Device Registry PORTABILITY ACROSS ANY INFRASTRUCTURE

CONNECTED IoT IoT DATA MANAGEMENT & “THINGS” EDGE INTEGRATION HUB ANALYTICS PLATFORM

Telemetry

• Linux containers • Kubernetes-based orchestration • Deployment ﬂexibility Management • Automation • Scalability • Persistent storage Container Container Container Container Container

IoT Services IoT Services IoT Services IoT Services IoT Services

OS dependencies OS dependencies OS dependencies OS dependencies OS dependencies

RHEL RHEL RHEL RHEL RHEL Guest VM Virtual Machine Virtual Machine Virtual Machine

LAPTOP BARE METAL VIRTUALIZATION PRIVATE CLOUD PUBLIC CLOUD APPDEV & CONTINUOUS DELIVERY

APPLICATION DEVELOPMENT, DELIVERY, & INTEGRATION BUILD TEST DEPLOY Cloud-native applications Traditional applications Developer services

Orchestration

DevOps Self-service Consistent Automated CI/CD Conﬁguration App logs & Provisioning environments build & deploy pipelines management metrics

CODE REVIEW MONITOR

SPRING & JAVA EE MICROSERVICES FUNCTIONS ● Application development & management LANGUAGES DATABASES APPLICATION SERVICES ● Polyglot, multi-language support ● Self-service provisioning LINUX WINDOWS* ● Linux containers ● Container portability * coming soon ● Deployment ﬂexibility ● Kubernetes-based orchestration ● Automation ● Scalability ● Persistent storage APPDEV WITH CODEREADY WORKSPACES PLANNING, CREATING, AND DEPLOYING HYBRID CLOUD SERVICES The collaborative OpenShift-Native IDE. Free for any customer of OpenShift Dedicated or OpenShift Container Platform.

Container Workspaces DevOps Integrations Protect Source Code

Workspace replicas to end Reference developer Full access to source code “works on my machine” and workspaces from any issue, without any of it landing on enable team collaboration. failed build, or git notiﬁcation. hard-to-secure laptops.

Based on the open Eclipse Red Hat Linux and Plugin model for Serverless support Che project Application Infrastructure extensibility (coming later)

Use It To: Replace VDI for devs, and enable true container-based DevOps. EDGE CONTINUOUS DEPLOYMENTS

1. Create App / microservice / function Who: Developers Where: CodeReady Workspaces

3. Execute at the edge

App / Microservice / Function 2. Push to the edge WHAT IS THE EDGE ANYWAYS?

What is Edge Computing Why choose Red Hat for Edge computing? RED HAT EDGE COMPUTING PoV

***

*** Minimum of 3 nodes required today BEST EDGE COMPUTING FOUNDATION? CLOUD-NATIVE DEVELOPMENT DRIVING SERVERLESS / FaaS FROM CORE TO EDGE

K KNATIVE SERVERLESS BUILDING BLOCKS "...an extension to Kubernetes exposing building blocks to build modern, source-centric, and container-based applications that can run anywhere".

Build Serving Eventing A pluggable model for An event-driven model Common infrastructure for building artifacts, like jar that serves the container consuming and producing ﬁles, zips or containers with your application and events that will stimulate from source code. can "scale to zero". applications. KNATIVE EVENTING FLOW SERVERLESS ADOPTION OK, WE HAVE THE BUILDING BLOCKS, NOW WHAT?

62.9 % Node.js

20.8 % Python

6.1 % 6.4 % Go Java 6.1 % Java

3.8 % C#

https://serverless.com/blog/2018-serverless-community-survey-huge-growth-usage/ QUARKUS SUPERSONIC SUBATOMIC JAVA

A Kubernetes Native Java stack tailored for GraalVM & OpenJDK HotSpot, crafted from the best of breed Java libraries and standards

100x faster startup, 10% of the memory in native mode 10x faster and ½ the of the memory on Hotspot/OpenJDK

Minimal footprint Java applications -> Native vs Quarkus+OpenJDK JVM vs Traditional JVM QUARKUS HOW IS THIS POSSIBLE? Polyglot, Native or JVM, Embeddable Quarkus enables Java developers to easily use the most popular frameworks and standards directly on Sulong (LLVM) SubstrateVM without any hassle. Trufﬂe Graal Compiler JVM CI Substrate VM Java HotSpot VM

BUILD HotSpot Runnable & Image Compile Provision Wiring & Assemble AOT Native Executable PROCESS Native & Image Compilation

app.jar Frameworks Runnable Java App native-app APACHE CAMEL K SERVERLESS INTEGRATION

● A lightweight platform for directly running Camel integration DSL in a cloud-native way ● Based on (ex Core OS) operator-sdk ● Works on Openshift and Kubernetes ● Create Event Sources, use EIPs, deﬁne Integration Functions

K CAMEL K OVERVIEW Time to run an integration using different strategies (in seconds) File routes.groovy from(“telegram:bots/bot-id”) .transform()... .to(“kafka:topic”);

from(“kafka:topic”) .to(“http:my-host/api/path”);

$ kamel run routes.groovy

Lower is better :) DEVICE EDGE WHAT CAN WE DO WITHOUT KNATIVE/K8s?

● Run native functions in containers at the edge

● Beneﬁt from low footprint and fast startup

IOT EDGE Edge Edge Machine FRAMEWORK applications analytics learning Field K connectivity Cloud connectivity Edge analytics Edge applications Machine learning Linux Containers Linux CALL TO ACTION

● https://try.openshift.com/ ● https://developers.redhat.com/ LET'S BUILD ● https://knative.dev/docs/ ● https://quarkus.io/ CLOUD NATIVE ● https://github.com/apache/camel-k APPS

CASE STUDY - Smart Manufacturing - Deep Dive Integrating open source IoT operating technology, data management, analytics, and applications

• Data ingest • Stream / batch processing • Persistent data storage • Machine learning and Sentry YARN real-time analytics

Spark IoT Edge IoT Integration Hub

• Device connectivity • Device management, TCP/IP • Data transformation TCP/IP security, and access control Kafka Spark Kudu Field • Intelligent routing • Data aggregation Kafka Protocol • Business logic mqtt • Event processing • Edge analytics & real-time • Integration services (API’s) Impala TCP/IP decisions Mqtt / OPC-UA

Integrate Store Analyze

Unified Services Layer

Data Science Workbench Model Deployment

30 Knative Overview - Serving

● Conﬁgurations represent the ‘ﬂoating Service HEAD’ of a history of Revisions (my-function)

● Revisions represent immutable snapshot manages of code and conﬁguration

Route ● Routes configure ingress over a collection (name) Configuration of Revisions and/or Configurations Routes traffic to 10% ● Services (nope, not K8s services) are Revision records top-level controllers that manage a set of 90% history of Routes and Configurations to implement a Revision network service Revision SERVERLESS ADOPTION

62.9 % Node.js

20.8 % Python

6.1 % 6.4 % Go Java 6.1 % Java

3.8 % C#

https://serverless.com/blog/2018-serverless-community-survey-huge-growth-usage/ ENTERPRISE JAVA WAS DESIGNED FOR 3-TIER ARCHITECTURE

Presentation Logic HTML Javascript Web

Inventory Catalog Cart Business Logic

Promo Ratings Orders

Data Access Logic Data Access

APPLICATION SERVER / JVM

OPERATING SYSTEM HOW APPLICATION SERVERS DEPLOYED JAVA APPS

HTML Javascript Web HTML Javascript Web

Inventory Catalog Cart Inventory Catalog Cart

Promo Ratings Orders Promo Ratings Orders

Data Access Data Access

APPLICATION SERVER / JVM

OPERATING SYSTEM MICROSERVICES CHANGED HOW WE DEPLOY APPS

HTML Javascript

Order Web Promo Ratings Cart Inventory Catalog

Data Store Data Grid Data Grid Data Store Data Access Micro- Spring Micro- Spring Java EE NodeJS Reactive Proﬁle Boot Proﬁle Boot

CONTAINER ORCHESTRATION THE HIDDEN TRUTH ABOUT JAVA IN CONTAINERS

Node Node Node Node NodeJS Go Go Go Quarkus Quarkus Quarkus Quarkus Quarkus Traditional Cloud-Native Java Stack NodeJS Go Go Go Quarkus Quarkus Quarkus Quarkus Quarkus Quarkus Quarkus Quarkus Quarkus Quarkus Traditional Cloud-Native NodeJS Go Go Go Java Stack Quarkus Quarkus Quarkus Quarkus Quarkus NodeJS Go Go Go Quarkus Quarkus Quarkus Quarkus Quarkus Traditional Cloud-Native NodeJS Go Go Go Java Stack Quarkus Quarkus Quarkus Quarkus Quarkus NodeJS Go Go Go Traditional Cloud-Native Quarkus Quarkus Quarkus Quarkus Quarkus Java Stack NodeJS Go Go Go Quarkus Quarkus Quarkus Quarkus Quarkus

CONTAINER ORCHESTRATION

https://developers.redhat.com/blog/2017/03/14/java-inside-docker/ FAAS & SERVERLESS CHANGES HOW WE DEPLOY APPS IN THE FUTURE

Service Service Service Service Service Service Service Service Service Service Service Service Service Service

Function as a Service QUARKUS NATIVE DEPLOYMENT

Node Node

Quarkus Quarkus Quarkus Quarkus Quarkus Traditional Cloud-Native Java Stack Quarkus Quarkus Quarkus Quarkus Quarkus

CONTAINER ORCHESTRATION HOW IS THIS POSSIBLE? Polyglot, Native or JVM, Embeddable DEVELOPING NATIVE APPLICATIONS FOR SUBSTRATEVM IS PAINFUL

Quarkus enables Java developers to easily use the most popular frameworks and standards directly on SubstrateVM without any hassle. FRAMEWORK OPTIMIZATIONS

● Moved as much as possible to build phase ● Minimized runtime dependencies ● Maximize dead code elimination ● Introduced clear metadata contracts ● Spectrum of optimization levels (all -> some -> no runtime reﬂection)

Optimizations beneﬁt both GraalVM (SVM) and HotSpot

IMAGE CREDITS

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