G111614 top-trends-sydney2019-v1910a

2019 Top IT Trends -
Understanding the
fundamentals of the next
generation IT Environment
Tony Pearson
IBM Master Inventor,
Senior IT Management Consultant,
TechU Content Manager
2019 IBM Systems Technical University
15-17 Oct 2019 | Sydney, Australia

Agenda
IBM Systems Technical University © Copyright IBM Corporation 2019 2
Internet of Things (IoT)
Big Data Analytics
Artificial Intelligence
Containers and
Orchestration
Blockchain
Hybrid Multicloud

IoT Platform
Message Queuing Telemetry
Transport (MQTT) is an ISO
standard publish-subscribe
(Pub/Sub) based messaging
protocol on top of the TCP/IP
protocol. It is designed for
connections with remote locations
where a "small code footprint" is
required or the network bandwidth
is limited. The publish-subscribe
messaging pattern requires a
message broker.
IoT Protocols
• AMQP (Advanced Message
Queuing Protocol)
• CoAP (Constrained Application
Protocol
• DDS (Data Distribution Service)
• MQTT (Message Queue
Telemetry Transport)
• XMPP (Extensible Messaging
and Presence Protocol)

IoT: Considerations
Volume and pace
— Data governance policies
— Storage infrastructure
Security vulnerabilities
— Hijacked devices used to send spam, act as botnet, or overtake
other functions
— IoT search engine exposures
— Privacy leaks and unsecured devices
Address
— Due diligence on device security capabilities
— VPN
— Change default passwords
6

Agenda
Big Data Analytics
Containers and
Orchestration
Blockchain
Hybrid Multicloud

What is Big Data?

What is Big Data?
DATA is the new OIL
In its raw form,
oil has little value…
Once processed and refined,
it helps to power the world!
Analysis of a single large set of related
data allows correlations to be found
Big Data analytics can identify trends,
patterns and insights to make better
decisions

A new way at Looking at Data
Transaction and
Application data
Database
Administrators
System of Record
Gather data into
databases
1
ReportsBatch
Processing
Business
Analysts
Analyze reports
2
Business Executives
Make decisions
3
statistical
models Dashboard
Analyze data2
Data
Scientists
Empowered Employees
Make Decisions
and Take Action
3
System of Insight
Gather and Identify sources of data
1
Storage
Administrators

What does a Data Scientist do?
— “It’s no longer hard to find the answer to a given
question; the hard part is finding the right question.
And as questions evolve, we gain better insight into our
ecosystem and our business.”
-- Kevin Weil, Lead Analyst at Twitter
— A data scientist must have…
• Strong business acumen
• Modeling, statistics, analytics and math skills
• Ability to communicate findings, tell a story from the
data, to both business and IT leaders
— Inquisitive: exploring, doing “what if?” analyses,
questioning existing assumptions and processes to spot
trends, patterns and hidden insight.
Computers are useless.
They can only give you
answers.
– Pablo Picasso
Source: IBM, ClouderaIBM Systems Technical University © Copyright IBM Corporation 2019 11

Agenda
Big Data and Analytics
Containers and
Orchestration
Blockchain
Hybrid Multicloud

• Computers can be trained to “Sense”
• Airport security inspecting luggage
• Maintenance crew listening to railcars
• Temperature sensors to adjust fan controls
• Computers can be trained to “Mimic” human expertise
• Text analysis, automatic translation, text summarization
• Fraud detection in financial transactions
• Chatbots to support customer service calls
Artificial Intelligence brings new Cognitive Capabilities
• Classification – determine category or species
• Decision – such as loan or employment decision
• Detection – detect fraud, bias, or defect
• Prediction – predict future based on historical data

The many branches of Artificial Intelligence (AI)
80% of AI is Machine Learning (ML)
Speech processing is part of NLP,
but is big enough to warrant its own
branch
The “Watson” computer that played
Jeopardy! TV show is an example
Vision processing is part of Machine
Learning, but is big enough to
warrant its own branch
(AI)
Machine learning
Planning, Scheduling,
and Optimization
Robotics
Vision
Natural Language
Processing (NLP)
Speech
Expert Systems
Scheduling everything from
airplanes to football games

Training and Using AI Models
Ingest Prep Train Infer
Pantry, Refrigerator, Freezer
Identify suppliers,
Gather ingredients
Ingredients
Wash and Chop
Vegetables
Recipe
Kitchen
Appliances
and Utensils
Prepared
Food item
Create and
Improve
Data Lake
Identify sources,
Gather inputs
Input data Feature engineering,
Labeling data
AI
Model
ML/DL
Libraries
Classification
Decision
Detection
Prediction
Train, Test, Validate,
Performance, Monitor, Feedback

Machine Learning
Deep Learning
Many-layer neural
networks
Advanced
Analytics
Human Intelligence Exhibited by Machines
Cognitive / AI
Learning without explicit
programming
AI is fueled by machine learning and deep learning techniques

Machine Learning (ML) and Deep Learning (DL)
Ingredients
Soups
Salads
Cocktails
Input data
Ingredients
Ingredients
Ingredients
Input data
Input data
Input data
Recipes
ML
Models
Ingredients
Ingredients
Ingredients
Ingredients
Topping
Filling
Crust
Pie
Pie Recipe
Inputs
Inputs
Inputs
inputs
DL Model
Machine Learning Deep Learning
Classification
Decision
Detection
Prediction
Classification
Decision
Detection
Prediction

What does IBM call these?
Anaconda
Spark
Python
Scala
R
For x86, Power and Cloud:
• IBM Data Science Experience (DSX)
• IBM Watson Studio Desktop
• IBM Watson Studio Local (WSL)
• IBM Watson OpenScale
• IBM PowerAI and PowerAI Vision
• IBM Cloud Pak for Data
• IBM Watson ML Community Edition (WML CE)
• IBM Watson ML Accelerator (WMLA)
• IBM Snap ML
For IBM Z and LinuxONE:
• IBM Open Data Analytics for z/OS (IzODA)
• IBM Watson ML for z/OS (WMLz)
• IBM Watson Studio Local (WSL) for Linux on Z

IBM Watson Machine Learning Community Edition
TensorFlow
TensorFlow Probability
TensorBoard
TensorFlow-Keras
BVLC Caffe
IBM Enhanced Caffe
Caffe2
OpenBLAS
HDF5
Curated, tested and pre-compiled binary
software distribution that enables
enterprises to quickly and easily deploy deep
learning for their data science and analytics
development
Including all of the following frameworks:
Nvidia RAPIDS

Training and Inference Data and Compute: Considerations
Training
• Data intensive: historical data sets
• Compute intensive: 100% accelerated
• Develop model for use on edge as inference
• Iterative to improve accuracy
Inference
• Enables the computer to act in real time
• Very fast response
• Low Power
• Out at the edge
• Deploy updates
20

ANALYZE - Scale insights with AI everywhere
Data of every type,
regardless of where it
lives
MODERNIZE
your data estate for an AI
and Multicloud World
AI
The AI Ladder
INFUSE – Operationalize AI with trust and transparency
ORGANIZE - Create a trusted analytics foundation
COLLECT - Make data simple and accessible

Agenda
Big Data Analytics
Containers and
Orchestration
Blockchain
Hybrid Multicloud

Solving all our problems

The What and Why of Containers?
Advantages of Containers
• Lightweight footprint & minimal
overhead
• Portability across machines
• Simplify DevOps practices
• Speed up Continuous Integration
• Enable microservice
architectures
• Isolation
Containers are an abstraction at the
app layer that packages code and
dependencies together

What is Kubernetes (K8s)?
Container-based virtualization Container orchestration
To satisfy common needs in production
+
Replicating application instances
Naming and discovery
Load balancing
Horizontal auto-scaling
Co-locating helper processes
Mounting storage systems
Distributing secrets
Application health checking
Rolling updates
Resource monitoring
Log access and ingestion

Agenda
Big Data Analytics
Containers and
Orchestration
Blockchain
Hybrid Multicloud

Transactions are
digitally signed and
protected through
strong cryptography
All organizations in the
blockchain network
have a replica
of the ledger
Party A
Bank
Auditor
Party B
Traditional
Clearing
House
…inefficient, expensive, vulnerable …provenance, immutability, finality
Privacy
Shared
ledger
Smart
contract Consensus
Party
A’s
records
Auditor’s
records
Bank’s
records
Party
B’s
records
With blockchain
Blockchain will fundamentally change business processes

 Blockchain is a new type of business network using a shared
replicated ledger that is continuously updated with digital
records of transactions.
 Rather than having a central administrator like a traditional
database, this ledger has a network of replicated databases,
synchronized via the internet and visible to authorized actors
within the network
Blockchain networks can be:
- publicly accessible to any person in the world
- e.g., Bitcoin is an implementation using a public Blockchain
- private with restricted membership similar to an intranet
- Hyperledger offers this type of implementation
What is blockchain?

Hyperledger Fabric
An implementation of blockchain technology that is a
foundation for developing blockchain applications
Emphasis on ledger, smart contracts, consensus,
confidentiality, resiliency and scalability
V1.4.2 released July 2019
• V1.4 Long Term Service release with emphasis on
production operational and serviceability
enhancements; new programming model abstractions
for ease of development
• V1.4.2 adds migration to RAFT consensus, channel
rollback and other features and fixes
IBM is one of the many contributing organizations

Agenda
Big Data Analytics
Containers and
Orchestration
Blockchain
Hybrid Multicloud

The Cloud

The Technology and the Business Side of Cloud
Cloud computing is a model for
enabling convenient,
on-demand network access to a
shared pool of configurable
computing resources (e.g.,
networks, servers, storage,
applications, and services) that can
be rapidly provisioned and
released with minimal
management effort or service
provider interaction.*
* Source: U.S. National Institute of Standards and Technology (nist.gov)
Technology Side… … Business Side
Cloud is a capability, not a place

Clients are Deploying Clouds for Speed and Scalability
Infrastructure
Dedicated
(Private)
Public
Local
(Private)
On-premises
Off-premises
Cost
Innovation,
Speed,
Scalability
Business
Value
TransformationCost
Effectiveness
Essential
Integration
PaaS-centric
DevOps tooling
Web/Mobile
apps
Basic analytics
Hybrid
integration
High value
solutions
Cognitive apps
Advanced analytics
Internet of Things
IaaS-centric
Virtual
compute
Low cost
storage
Traditional app
hosting
160+ IBM services
9.5 billion+ service
API calls/month

Shared
Off-Premise
Cloud
Local
On-Premise
Cloud
Traditional
IT
Dedicated
Off-Premise
Cloud
Choose the right mix for your business
Enterprise
Applications
Cloud Enabled
Cloud Native Apps/Services
Hybrid Cloud
• Existing enterprise IT applications can be “cloud-enabled” to
run in on-premise or off-premise cloud deployments
• Cloud apps or services built natively for public clouds can be
ported to on-premise or off-premise private clouds
Hybrid Cloud – Application Portability

Lift, Standardize, Consolidate,
Automate, Shift
Contain, Expose, Extend
Refactor, Create as Cloud-Native,
Microservices
Data Classification, Movement &
Governance
on-premises | off-premises
Evolution to cloud-based
applications
Customer
Information
Payment
Systems
Business
Process
New
Applications
Application portfolio
Hybrid DevOps
Hybrid Runtimes
Cloud Native
Architectures
Hybrid Cloud transformation patterns

What is hybrid multicloud?
IBM Systems Technical University © Copyright IBM Corporation 2019
Hybrid Cloud
A hybrid cloud is technological approach that allows applications and data to be shared in
a computing environment that combines two more of the following: traditional IT,
on-premises local private cloud, off-premises dedicated private cloud, and public cloud.
Multicloud
Multicloud is a business approach that decides not be limited to a single cloud platform or
service provider, allowing application designers, architects and owners to choose the best
fit from more than one cloud service, from more than one cloud vendor—public or private.
Hybrid Multicloud = Hybrid Cloud + Multicloud
A hybrid multicloud combines these technological and business approaches, with
on-premises IT resources connected to more than one cloud service provider, as needed.
36

IBM + Red Hat deliver the industry’s only true hybrid multicloud platform
Traditional workloads
AWS Microsoft GoogleIBM + Red Hat
Limited
feature
support
Azure Stack
Google
Anthos
Limited
feature
support
Public
Cloud
Private
Cloud
Traditional
on-premises
Limited
connectivity in
storage/data
movement
Connectivity
confined to
Microsoft
products
No
connectivity 𝙓
Extensive
multicloud
governance/mgmt.
↻
IBM
Private
Cloud
OpenShiftOpenShiftAWS Azure OpenShift
Google
Cloud
OpenShift AWS Outposts
IBM Public Cloud
OpenShift optimized

Making IBM’s key software products cloud native or all clouds
Reduce dev time
up to 84%*
Make data ready
for AI in hours vs.
days
Eliminate 33%
of integration
cost*
Reduce manual
processes up to
80%*
Reduce IT op expense
by up to 75%*
Cloud Pak for
Applications
Build, deploy and
run applications
IBM containerized
software
Cloud Pak for
Data
Collect, organize
and analyze data
Cloud Pak for
Integration
Integrate applications,
data, cloud services
and APIs
Cloud Pak for
Automation
Transform business
processes, decisions
and content
Cloud Pak for
Multicloud
Management
Multicloud visibility,
governance and
automation
IBM containerized
software
IBM containerized
software
IBM containerized
software
IBM containerized
software

Final Thoughts
These trends are
complementary, and
can be combined
together
Do not let Fear,
Uncertainty or Doubt
prevent you from
exploring their value
IBM is a leader in
these trends and can
help you in your
journey!

Thank you!
Tony Pearson
tpearson@us.ibm.com
+1-520-799-4309
Please complete the Session
Evaluation!

Special Thanks
I would like to thank the following colleagues
who contributed charts, insights, and review
comments for these presentation materials
— Thomas Chandler
— Rob Dyson
— Frank Van der Wal
— Stephane Faure
— Nin Lei
— Clarisse Taaffe-Hedglin
— Lloyd Dean
— Brian Sherman
— Brett Webb
— Theresa Tai
— Anna Shugol
— Joe Cropper
— Andrew Hicks

About the Speaker
42
Tony Pearson is a Master Inventor, Senior IT Management Consultant, and Content Manager for the
IBM Systems Technical University events. Tony joined IBM Corporation in 1986 in Tucson, Arizona,
USA, and has lived there ever since. Tony presents briefings on storage topics covering the entire IBM
Storage product line, IBM Spectrum Storage software products, and topics related to Cloud Computing,
Analytics and Cognitive Solutions. He interacts with clients, speaks at conferences and events, and
leads client workshops to help clients with strategic planning for IBM’s integrated set of storage
management software, hardware, and virtualization solutions.
Tony writes the “Inside System Storage” blog, which is read by thousands of clients, IBM sales reps and
IBM Business Partners every week. This blog was rated one of the top 10 blogs for the IT storage
industry by “Networking World” magazine, and #1 most read IBM blog on IBM’s developerWorks. The
blog has been published in series of books, Inside System Storage: Volume I through V.
Over the past years, Tony has worked in development, marketing and consulting for various IBM
Systems hardware and software products. Tony has a Bachelor of Science degree in Software
Engineering, and a Master of Science degree in Electrical Engineering, both from the University of
Arizona. Tony is an inventor or co-inventor of 19 patents in the field of IBM Systems and electronic data
storage.
9000 S. Rita Road
Bldg 9032 Floor 1
Tucson, AZ 85744
+1 520-799-4309 (Office)
tpearson@us.ibm.com
Tony Pearson
Master Inventor
Senior Management
Consultant, IBM Systems
La Services
IBM Storage
IBM Systems Technical University © Copyright IBM Corporation 2019

My Social Media Presence
Blog*:
ibm.co/Pearson
LinkedIn:
https://www.linkedin.com/in/az990tony
Books:
www.lulu.com/spotlight/990_tony
IBM Expert Network on Slideshare:
www.slideshare.net/az990tony
Twitter:
twitter.com/az990tony
Facebook:
www.facebook.com/tony.pearson.16121
Instagram:
www.instagram.com/az990tony/
Email:
tpearson@us.ibm.com
* Not a typo. This is short URL for https://www.ibm.com/developerworks/mydeveloperworks/blogs/InsideSystemStorage/

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