The IBM Watson Presentation Template

Hazelcast In-Memory Platform

Faster, Smarter Applications Secure, Resilient, Always-On Run Anywhere – Edge, to Hybrid Cloud to Z Platform

1 The Digital Enterprise

❑Always-On & Always Accessible ❑Touchless & Invisible ❑Self-Service & Autonomous ❑Boundaryless & Secure

●Hazelcast certified on Red Hat OpenShift & Cloud Paks ~3 years of integration engineering with IBM ●Global OEM for Cloud Pak Executed (May 15th, 2020) ●Edge Ecosystem ISV Hybrid multicloud is the reality, but you need a sound strategy Only From 27% From 22% to 34% to 39% 20% of enterprise workloads

Private Public Clouds Dedicated have moved to the cloud Clouds and SaaS Clouds Between 2019 and 2021, clients are migrating more - but inconsistently Traditional Enterprise IT From 39% to 16% 4 Source: McKinsey, IT as a service: From build to#FastStart2020 consume “2019 State of the cloud report.” RightScale. 2019. IBM Cloud / © 2020 IBM Corporation 4 © HAZELCAST | 4 Sources of value

Business A hybrid strategy acceleration Architecture unleashes the full development method productivity potential of the cloud. Infrastructure cost efficiency more value than a public-only strategy. Regulatory 2.5X and risk Strategic optionality

In-Memory Operational Computing Platform that is simple to deploy | operate | scale | maintain

Accelerate Performance Simple to Scale Always On x dd Up to 3X faster throughput Scale Elastically and Automatically Automated Multi-Cluster Disaster Recovery

6 IBM Cloud Pak for Applications

Client and Partner Applications In-Memory Computing Platform

Unified User Experience

Accelerators and Governance

Integration Self Service and Portal Develope Modernization Enterprise Management Runtimes DevOps r Toolkits Ready Extensions Tools

Secure Engineering

IBM containerized software

Container platform and operational services

IBM AWS Microsoft Google Private IBM Z Endpoints public cloud Azure Cloud IBM LinuxOne IBM Cloud Pak for Applications / © 2020 IBM Corporation IBM Power Systems IBM Storage 7 Watson AIOps Watson AIOps Intelligence Layer High level architecture Slack Microsoft Teams Client IT Ops / SRE teams MatterMost Others Deliver Analytics via ChatOps Client Operational Data

IBM & Strategic Partners:

IBM Netcool IBM Monitoring Watson AIOps Intelligence Layer

Incident Resolution (reactive) Incident Analysis (predictive) Incident avoidance (proactive)

• Intelligent alerting & alert • Anomaly detection • Change & version management grouping • Root cause analysis • Automated runbooks for next best … and more • Triaging • Next best action action recommendations Other Integrations: • Incident similarity recommendations • Code vulnerability analysis • Topology & blast status • Explanation fort trust

Prometheus Red Hat Open Shift Cloud Pak for Data Container Platform

IBM Cloud Google Cloud

Traditional Stack Modernized Stack BENEFITS OUTCOMES

High-Throughput, Increase Revenue: Legacy Apps Legacy Apps New Apps New Apps Fast customer response Low-Latency times & accelerated insights for decision making. Integrated Batch and Stream Processing with Decrease Risk: In-Memory Database In-Memory Storage Continuous intelligence Computing Platform for better decisions.

Simplified, Database Run-anywhere Deployments Reduce Operating Virtualization (Hypervisor) Containers / Costs: Cloud- Increase performance OpenShift Native, Multi- capacity of existing Operating System Operating Cloud infrastructure System Serverless

Runs Anywhere

88% will lose

Lost revenue Regulatory penalties Damaged reputations 88% of businesses lose Government regulation, Customers expect 24x7 $300,000 per hour & 40% monitoring and inspection availability. If a digital lose USD 1.5 million or add pressure to deliver service is unavailable, the more.¹ continuous availability. backlash can be swift.

Source: Forrester and IBM report: The Real Costs Of Planned And Unplanned Downtime North-to-South Hazelcast Fast Data & Compute Processing High throughput with Latencies in Reference Architecture Request/Reply Transactions / microseconds to Human milliseconds Interactions

Microservices

MQ MQ

Kafka Hazelcast In-Memory Computing Platform Kafka

IoT Alerts Fast Ingest & Analytics Analyze Custom Connector Enterprise Applications Enterprise Collect Interactive Applications Infuse AI Analytics Hazelcast IMDG Hazelcast Continuous ML Inference Ingest Transform Combine Stream Python, Java, Publish Fast Data Store IMDG Business C++ Events Actionable File Watcher Pipeline Context Databases Socket Fast Operational Data Layer ML Models HDFS, Database & Insights S3, Events NoSQL Organize File Sources Remote Fault-tolerant, ML Model Sinks Real-time & Fast Batch © HAZELCAST | 11 Data Pipelines Databases & Systems of Record IBM Cloud Pak for Data Top Use Cases

1. Maximize Multicloud Application Transaction Processing Performance Provide secure, reliable, elastically scalable, high-speed transaction processing with the ultra-low end-to-end latency for banks, payment processors, eCommerce and other firms, e.g.: ● >10,000 TPS with 99.999% uptime ● 3X faster than Redis ● Latencies remain predictably low and flat up to 5,000,000 TPS Example Use Cases: Real-time fraud detection, Payment processing, payment authorization, FX pricing exchanges

2. Modernize Multicloud-to-Mainframe Infrastructure While Increasing Performance Capacity ● Maximize mainframe and application performance - increase overall transaction throughput and lower latency. ● Future-proof application infrastructures by optimizing MF dependencies and performance. ● Simultaneously increase business agility, reduce application infrastructure costs, and increase the performance capacity of the existing infrastructure by 3X-10X.

Example Use Cases: Mainframe & microservices-based application modernization, mainframe cost reduction, PSD2/Open Banking initiatives

3. Provide Competitive Advantage in eCommerce & Omni-Channel Customer Experience Applications Deliver elastically-scalable, low-latency, customer-facing eCommerce & customer experience solutions to provide product visibility, speed purchases, increase upsell/cross-sell opportunities and maximize customer experience including during peak-customer demand. Example Use Cases: Real-time inventory visibility/Availability to Promise, real-time eCommerce Product Catalog, omni-channel customer experience

4. Deliver Instant Situationally Aware Insights with 5G, IoT/IIoT, Edge Computing, enabled with AIOps Provide a high-performance, low-latency processing backbone for Edge and IIoT applications to create value from situational-aware insights by placing intelligent compute power at the edge where data is generated and services are rendered.

Example Use Cases: Field equipment monitoring, Asset Performance Management (APM), manufacturing operations, smart vehicles, connected cities, telco (cloudification of networks, software-defined networks).

Hazelcast Hazelcast Hazelcast Open Liberty Client Client Client or Quarkus Nearcache Nearcache Nearcache

Cloud Region A Cloud Region B

Hazelcast Hazelcast Hazelcast Hazelcast IMDG IMDG IMDG IMDG Node Node Real-time Node Node Multi-Region Delta WAN Synch Fast Operational Data Layer Hazelcast Hazelcast Hazelcast Hazelcast Microsecond-Millisecond response IMDG IMDG IMDG IMDG Delivering 99.999% uptime Node Node Node Node On-Grid Low-Latency Compute

Asynch Write-through to Typically this architecture is replicated Persistent Store across multiple data centers or Cloud regions or in a hybrid Cloud model.

System of Record SQL, NoSQL, Mainframe

Hazelcast - Fast Data & Compute from Edge-to-Hybrid Cloud

Smart Smart Smart Smart Touchless Connected 5G Smart Vehicles Cities Factories Healthcare Energy Telemetry Retail Channels & APIs

Fast Data Ingest & Analytics Fast Data Ingest & Analytics Enrich Edge Ingest Analyz Act Publish ML e Fast Data Ingest & Analytics Enrich Ingest ML Act Publish Analyze

Fast Distributed Operational Data Enrich Layer Ingest ML Automate Publish Analyze Fast Distributed Operational Data Lightweight/Run-Anywhere

Fast Distributed Operational Hazelcast in Lightweight/Run-Anywhere Edge Data Layer

Hazelcast in Lightweight/Run-Anywhere IBM Edge Application Manager Public Cloud Deploy, Run & Manage Smart Hazelcast in Hazelcast Edge Applications Private Cloud Cognitive & Data Lakes (Data Center) Z & Power → Core Banking & Systems of Record Red Hat OpenShift, IBM CloudPak for Apps & Cloud Pak for Multi-Cloud Management Deploy, Run & Manage © HAZELCAST | 14 Hazelcast in Hybrid Cloud Real-time ML, Managed by Hazelcast Cluster

▪ Model gets created in Watson Studio ▪ Model deployed with the Job and managed by the Hazelcast ML Model cluster ▪ Scales Elastically with Resilient Execution ▪ Value in simplicity and performance ▪ Model deployment options: ML ML Model Model • Java • Python • C++ Hazelcast Cluster

Connecte Smart Smart Smart Smart Touchless 5G Smart d Cities Factories Healthcare Energy Telemetry Retail Vehicles IBM AIOps Fast Data Ingest & Analytics

Enrich Edge Ingest Act Publish Analyze ML Fast Data Ingest & Analytics Fast Data Ingest & Analytics

Enrich Fast Distributed Operational Data ML Act Publish Enrich Ingest Analyze Ingest ML Act Publish Layer Analyze

Lightweight/Run-Anywhere Applications Fast Distributed Operational Data Fast Distributed & APIs Operational Data Layer

Lightweight/Run-Anywhere

Lightweight/Run-Anywhere Hazelcast in Edge Hazelcast in IBM Edge Application Manager Public Cloud Data Lakes

Red Hat OpenShift, IBM CloudPak for Apps & Z-Platform Cloud Pak for Multi-Cloud Management Hazelcast running in Private Cloud,

Power OpenShift or Intel Hazelcast IMDG Hazelcast Jet

Z/OS Z/15 IBM MQ InfoSphere or JDBC Legend CICS (or IMS TM) Transactions

DB Changes DB2 IMS DB VSAM

TBs of data synched geographically 20K+ TPS low-latency compute APIs/Channels 99.999% uptime

Fast Ingest

Fast Event Driven Data Processing

Message Transform (ETL) Process Store Route

Dispatcher

Monitoring JMX JMX Data-Grid as Clustered Event Bus and Low-latency Data Store Security Microservices store result of each transaction in grid

Red Hat Open Shift Write-through to systems of & IBM Cloud Pak for record & reporting Multi-Cloud Management Systems of Record © HAZELCAST | 18 The Hazelcast Difference: Low Latency with Resilience Example: Credit Card Processing

Time-Based SLA

Network Transit

Swipe Card-Processing Infrastructure Tiny Window of Time For Accurate Processing Response Milliseconds Initial Processing: Microseconds

Business Opportunity: TIME Run multiple fraud lookups in Fraud Performance at Scale Detection gives time for the same round-trip approval Algorithm multiple algorithms SLA: reduce risk & loss

Trading Algos 1 Compliance Algos

Surveillance Pricing Circuit Breakers Market Risk Hedging Live Monitoring Other Risk Mitigation Credit Risk Execution Replay The ideal operating flow: Permitted 1. Compliance algorithms monitor trading in 3 Instruments real time. Revise If any of these get 2. If any compliance, risk, or regulatory rules 2 tripped, then… are broken, then the team is alerted. 3. The team then replays and evaluates the time period in question. 4. 2nd and 1st lines of defense discuss the Discuss 4 Evaluate situation and revise/test algos as required. 5. Inform the 3rd line of defense of actions taken. Inform Delays in these steps result 5 3rd Line of Defense in higher company risk. AUDITORS © HAZELCAST | CONFIDENTIAL | 20 Fast Risk Calculations with Cloud-scale

Market Feeds Fast Distributed Compute

Ingest Enrich Calculate Aggregate Report

Fast Operational Data Store

Portfolio Positions Prices VaR

Elastically Auto-Scale with Red Hat Open Shift Synchs with & IBM Cloud Pak for Multi-Cloud Management systems of record Systems of Record © HAZELCAST | 21 Hazelcast Fast Edge-to-Cloud Ingest & Edge Analytics

Connected Smart Smart Smart Smart Touchless 5G Smart Vehicles Cities Factories Healthcare Energy Telemetry Retail New ML Models Deployed to Edge

Fast Data Ingest & Analytics Data Lake Platform

Enrich & Fast Data Ingest & Analytics Ingest Edge ML Act Publish Analyze Enrich Ingest ML Act Publish Analyze

Fast Distributed Operational Data Layer Fast Distributed Operational Event Bus & Low-latency Store Data Layer

Lightweight/Run-Anywhere

Lightweight and Runs Anywhere

Sensor & Device Data

Touchless Tap & Go with Smart Online Channels Smart Signs Payments

Smart Mobile-Aware Brick & Mortar ML Models Deployed to Edge - Branch/ATM

Fast Data Ingest & Analytics

Enrich Enrich & Ingest ML Act Publish Ingest Edge ML Act Publish Analyze Analyze

Fast Distributed Operational Data Layer Fast Distributed Operational Data Layer

Event Bus & Low-latency Store Lightweight/Run-Anywhere

Payments, Deposits, Transfers, P2P Lightweight and Runs Anywhere

IBM Edge Application Manager Deploy & Manage Smart © HAZELCAST | 23 Hazelcast Edge Applications Digital Trade & Supply Chain Automation

APIs/Channels

Fast Ingest Fast Event Driven Data Processing

Message Transform (ETL) Process Store Route

Dispatcher

Monitoring JMX JMX Data-Grid as Clustered Event Bus and Low-latency Data Store Security Each Microservice caches the result of its task on the transaction

Write-through to systems of record & reporting Systems of Record © HAZELCAST | 24 Benefits - Zero-Downtime Banking Success

Cross-cluster replication across geographies Globally available transaction data with millisecond response Low-latency data-aware compute on elastic grid Elastic scalability to support peak loads during extreme spikes

Fast, Zero-Downtime Data Plane Low Latency Card Authorization Store 2TB of customer data and synch IMDG IMDG geographically 20K+ TPS distributed compute with low- IMDG IMDG IMDG IMDG latency 99.999% uptime architecture IMDG IMDG Instant Payments Hub

IMDG IMDG IMDG IMDG 20,000 TPS 99.999% up-time

• Low-latency data grid for fast access to market data, positions, etc. • Low latency, data-aware compute on elastic grid. • Distributed low-latency calculation of prices, risks, etc.

Trading FX Quotation Systems Applications • Sub-millisecond access, off heap data to eliminate garbage collection • Fast distributed calculations of prices, margins and quotations • Ensure zero-downtime SLA Financial Market Data Unified Data & Compute Grid • More predictable/accurate derived calculations with single source of market data • Stable and always-on gateway access – allowing more concurrent system users, more quickly IMDG IMDG Risk Calculation and Reporting • Data-aware, co-located Computation accelerates risk processing

IMDG IMDG IMDG IMDG • In-Memory Access to Operational and Market Data

Online Shopping

eCommerce App Servers Online Store - Phones Online Retailer • Time to report accurate • Removed performance order delivery date from bottleneck for Apache 30 mins to 7 secs Cassandra system of record – latency reduced IMDG IMDG • 1.2ms max application from 300ms to ~2ms latency • Exceeds SLA target of IMDG IMDG IMDG IMDG • Ensure zero-downtime 40ms and scales SLA for new iPhone elastically to meet Unified Digital Customer Data Layer introductions seasonal events like Black Friday, Cyber Monday • Cross-cluster replication across geographies • Globally available online store data with millisecond response • Elastic scalability to support peak loads during extreme spikes • De-couple online store from back-ends for maximum resilience © HAZELCAST | 27 Hazelcast and Intel Deliver Together

More Lower More Uptime Latency Data 2.5X faster restarts Ultrafast I/O & Encryption Big data sets—structured and Enables 99.999 Uptime & seamless can be achieved with Hazelcast unstructured—can be used with upgrades/deployments with Intel® solutions powered by Next-Gen Intel Hazelcast solutions powered by “Cascade Lake” Xeon® Platinum Xeon Scalable processors and NICs, Intel Xeon Scalable processors 8180 processor and Intel® that provide instant access to data. Intel® Optane™ DC persistent Optane™ DC persistent memory. memory modules, without a decrease in performance

▪ Unique: Joint & well integrated = Competitive advantage Modern & Innovative

▪ Enterprise grade & Resilient = Business Continuity ▪ Fast & Scalable & Secure = Lower TCO ▪ Agile & Easy to Manage = Faster Time-to-Market

Get Started https://www2.hazelcast.com/hazelcast-ibm-quick-start

Cheryl Parker Mark Santos John DesJardins Scott McMahon Hybrid Cloud Partner Offering Manager Sr. Director, Field CTO Technical Director [email protected] Worldwide Business Development [email protected] & Team Lead – North America +1.310.592.2647 [email protected] +1.770.833.9256 [email protected] +1.404.886.6263 +1.404.936.8005