CUMULOCITY IOT FRONTRUNNER MANAGE IOT ANALYTICS

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1 CUMULOCITY IOT FRONTRUNNER MANAGE IOT ANALYTICS ALIM YIGITER SR. PM CUMULOCITY IOT

2 YOUR DIGITAL BUSINESS PLATFORM IOT IS A SUBSET OF THE DIGITAL BUSINESS DIGITAL ENTERPRISE MODEL ANALYTICS & DECISIONS Streaming Analytics & Artificial Intelligence In-Memory Data powered by TERRACOTTA & APAMA Process Transformation & Management Governance, Risk & Compliance Portfolio Management Enterprise Architecture Management powered by ARIS & ALFABET PROCESS & APPLICATIONS Dynamic Process Automation Low-Code Applications INTEGRATION & API Hybrid Integration API Management DEVICES Device Connectivity Device Management powered by WEBMETHODS powered by WEBMETHODS powered by CUMULOCITY INTERNET OF THINGS CLOUD + HYBRID ON PREMISE 2

3 Flexibility & Sophistication DIFFERENT DELIVERY MODELS FOR DIFFERENT CUSTOMER NEEDS IoT SaaS Fast Entry Self-service, out-of-the-box Pre-defined solution accelerators IoT PaaS Fan Out (Departmental) High productivity, fast go-to-market Smart rules Focus on business users IoT Framework Scale Out (Enterprise Level) Cross divisional end-to-end company processes Coding, professional developers Existing and new IoT applications fully interwoven Cumulocity IoT Growing Maturity Level over Time Software AG. All rights reserved.

4 CUMULOCITY IoT DEVICE CONNECTIVITY Plug & Play with existing integrations 100+ devices and gateways 300+ protocols (BACnet, KNX, Siemens..) Cloud Fieldbus Central, web based end-to-end integration Integrate new device types Protocols supported: MQTT, REST, LWM2M, Tracker, SNMP SmartREST payload compression Device SDK s for: SE & ME LPWAN Agents NB-IoT Connect over any IP network without VPN DEVICES Use any environment with: Model-less integration Use 1000 s of device types/versions Device originated data model extension all devices, all networks, all verticals, all use cases Software AG. All rights reserved.

5 CUMULOCITY IoT ANALYTICS & DATA Streaming & Predictive Analytics Apama s patented, in-memory streaming analytics enables: Filtering, correlation, aggregation and pattern detection with time and location constraints Enrichment of streaming data with context data for deeper, richer analytics Performs analytics on both discrete events and event streams Designed for high throughput & low latency, with small HW footprint Predictive analytics with R and Python Operationalization of predictive models DATA & ANALYTICS DEVICES Visualization & Data Exploration Interactive business-focused mashup dashboards with responsive design Real-time with historic data blending Exploratory ad-hoc & time series analysis Supports rich set of data sources IIoT Cockpit & Digital Twins Data Management Elastically scalable data store MongoDB Complemented by Terracotta DB as in-memory data platform Pre-built integration with data lakes Built-in IoT/IIoT domain data models all devices, all networks, all verticals, all use cases Software AG. All rights reserved.

6 CUMULOCITY IOT FRONTRUNNER APAMA OVERVIEW Rob Jones Apama Product Manager

7 STREAMING ANALYTICS APAMA ELEVATOR PITCH What is Apama Streaming Analytics? Apama can apply analytics to huge volumes of fast-moving data with very low latency Where can it be deployed? Cumulocity IoT Cloud and Cumulocity IoT Edge Standalone - Enterprise hardware: x86 compatible hardware on Windows, & Linux Standalone - Other hardware: ARM embedded devices, Edge Servers Who is it for? Organizations that wish to analyze data-in-motion and drive fast decisions How does it help? Processes large numbers of data events every second and provides sub-millisecond decisioning Supports vast scalability, open analytics standards, very efficient use of hardware and exhibits extreme high reliability 7

8 STREAMING ANALYTICS THE DATA DIVIDE BIG DATA CHASM Global datasphere is estimated to grow from 16.1 ZB in 2016 to 163 ZB in % will contain valuable information 3% prepared for analysis 0.5% being analyzed <0.5% being operationalized Sources: IDC, The Digital Universe of Opportunities: Rich Data and the Increasing Value of the Internet of Things and "Data Age The Evolution of Data to Life-Critical, 1ZB (Zettabyte) = 1T GB 8

9 STREAMING ANALYTICS PERISHABLE INSIGHTS VALUE FALLS RAPIDLY Business Event Business Value Response Response Window Forrester defines perishable insights as urgent business situations (risks and opportunities) that firms can only detect and act on at a moment s notice. Forrester Research, Q Time 9

10 STREAMING ANALYTICS DETECT PATTERNS AND ACT ON REAL-TIME INSIGHTS Software that can filter, aggregate, enrich, and analyze a high throughput of data from multiple, disparate live data sources and in any data format to identify simple and complex patterns to provide applications with context to detect opportune situations, automate immediate actions, and dynamically adapt. Forrester Research, March 2016 Data feeds Streaming Analytics Application Logic Predictive Analytics, Business Rules, Visual Alerts & Analysis Business Processes 10

11 APAMA BATCH PROCESSING COMPARED & STREAMING ANALYTICS Batch Processing: What was the average temperature of the machine yesterday? Data at rest traditional approach Store the data first Then analyze it (run queries) Event Streams Event Processing Time Streaming Analytics Processing: When more than 3 temperature events are received above a threshold, alert. 11

12 APAMA IN CUMULOCITY IOT STREAMING ANALYTICS USE CASES Notifications: Send me an if there's a power outage in one of my machines Remote control: Turn a device off if its temperature goes over 40 degrees Validation: Discard negative meter readings or meter readings that are lower than the previous value Derived data: Calculate the volume of sales transactions per vending machine per day Aggregation: Sum up the sales of vending machines for an organization per day Compression: Store location updates of all cars only once every five minutes (but still send real-time data for the car that I am looking at to the user interface) 12

13 APAMA IN CUMULOCITY IOT SMART RULES Smart Rules allow you to select pre-existing rules and use a friendly UI to configure them A number of Smart Rules are provided with Cumulocity E.g. On geofence create alarm Apama is used behind the scenes to execute the rules 13

14 APAMA IN CUMULOCITY CUSTOM CEP RULES Custom CEP rules allow you to run specific Apama code in real-time on the data streaming through Cumulocity E.g. Create alarm if temperature too low for 15 mins Apama is used behind the scenes to execute the rules 14

15 APAMA BENEFITS FIRST CLASS DEVELOPER TOOLING Apama has a full development environment Code autocompletion Syntax highlighting Interactive debugger with breakpoints, stepping etc. Connectivity with Cumulocity for live execution and debugging 15

16 APAMA BENEFITS FIRST CLASS DEVELOPER TOOLING Apama has extensive tooling for use with the development environment Code-coverage utility Discover how test cases cover application code Identify gaps in testing Memory profiler Track how and where memory is used CPU profiler Highlight processing-intensive parts of your application Data replay Record and replay data for simulation and testing 16

17 APAMA BENEFITS APAMA EPL IS JAVA-LIKE Apama s programming language EPL is recognized as Java-like Straightforward for Java developers to get started Apama EPL: monitor ForwardMeasurements { action onload() { on all Measurement(type = "c8y_temperaturemeasurement") as m { send Alarm( "", "c8y_temperaturealarm", m.source, m.time, "Temperature measurement was created", "ACTIVE", "CRITICAL", 1, new dictionary<string,any> ) to Event.CHANNEL; } } } 17

18 APAMA BENEFITS CLASS-LEADING PERFORMANCE Applications run faster in Apama and require less memory Apama s server is natively built and optimized for performance on each platform: Does not require the performance overhead of working through a JVM No unpredictable slow performance spikes due to Java garbage collection CPU profiler tool highlights application performance bottlenecks Use profiler to optimize your applications 18

19 Flexibility & Sophistication APAMA BENEFITS APAMA IN ALL IOT DELIVERY MODELS IoT Framework Scale Out High flexibility & control Focus on IT & developers IoT SaaS Fast Entry Cloud, self-service Pre-defined solution accelerators IoT PaaS Fan Out High productivity, fast go-to-market Focus on business users IoT Platform Growing Maturity Level over Time 19

20 APAMA BENEFITS SINGLE APPLICATION WORKS IN ALL ENVIRONMENTS Same Apama application can be deployed across all Cumulocity IoT environments and in standalone Apama installations (optional) Global Platform (Cloud / On-Premise) Regional Platform (Cloud / On-Premise) Thick Edge (On-Site Server) Thin Edge (IoT Gateway) Device Knowledge & Analytics Horizon TCO per Device Broad High Deep Low Broad High Deep Low Broad High Deep Low Broad High Deep Low Broad High Deep Low 20 Fully-fledged Cumulocity IoT Platform with embedded Apama Apama as part of IoT customer frameworks Lightweight Cumulocity IoT Platform with Apama Apama embedded in 3 rd party edge platforms Apama incorporating Cumulocity IoT device-side agent Apama standalone Apama incorporating Cumulocity IoT deviceside agent Apama standalone

21 APAMA IN CUMULOCITY IOT V9 (AND LATER) SOFTWARE AG STRATEGY FOR CUMULOCITY IOT Apama is the streaming analytics platform for Cumulocity IoT Apama is fully supported within Cumulocity IoT Apama and Cumulocity IoT are both Software AG products Direct support from the same Software AG global support team Integration between Apama and Cumulocity IoT provide several benefits, which will increase over time Apama s streaming analytics capabilities and tooling will broaden to enhance what is possible today Apama s roadmap is aligned with Cumulocity IoT 21

22 APAMA IN CUMULOCITY IOT ROADMAP - ANALYTICS BUILDER New Analytics Builder available as a Cumulocity IoT web-app Graphical UI for non-coders wanting to take advantage of streaming analytics Quickly build and deploy analytical models Library of pre-built analytic blocks Drag and drop, web-based editor Manage deployment and simulation First release planned for Cumulocity IoT Edge later in

23 APAMA IN CUMULOCITY IOT ROADMAP - ANALYTICS BUILDER Example network of four analytics Computed range Breach Parameters A set of parameters (specific to each type of Analytic) Filter Spike Value Sum Incoming Events Computed Events Drift Baseline Computed range Encapsulated logic Value Breach 23

24 APAMA IN CUMULOCITY IOT ROADMAP ANALYTICS BUILDER NEW WEB UI Current prototype from Apama R&D showing how a customer model could be represented in a free-flow UI style 24

25 APAMA IN CUMULOCITY IOT ROADMAP ANALYTICS BUILDER MODEL MANAGER Cumulocity Model Manager Single click activation of models Manages whether models are running with simulated or live data 25

26 APAMA ANALYTICS BUILDER ANALYTIC BLOCKS Gate Blocks the input from going to output unless the gate is open and enabled Direction Detects change in direction of the inputs. Generates direction and last inflection point, ignoring minor variations? Threshold And Or Compares input value against a threshold and detects above/below or crossing the threshold Performs a logical 'and' on the inputs Performs a logical 'or' on the inputs Measurements & Event Input Takes Measurement events from Cumulocity IoT and re-orders them based on timestamp Measurement Output Outputs a Cumulocity IoT measurement Operation Output Creates operations for a specified device with pre-configured operation name and parameters Delta Calculates the difference between successive values on a wire Time Delay Delays the input by the specified amount of time Difference Calculates the absolute difference between the connected inputs Latch Latches the latest input value received while enabled and only generates an output if the input value changes Missing Data Generates an output if the input has not occurred for a set amount of time Expression Addition, subtraction, compare etc. Mean Mean (arithmetic average) Integrate Calculates the integral of the value over time. Integral is defined as input value multiplied by the amount of time it maintains that value Toggle Converts two pulse inputs to a boolean output based on set and reset signals - with optional delays 26

27 APAMA STANDALONE WHAT CAN I DO WITH STANDALONE APAMA? Apama can also be licensed for external, standalone use with Cumulocity IoT Additional standalone capabilities of Apama: Predictive Analytics (Zementis, R) Direct connectivity (JMS, Kafka, MQTT, HTTP, Universal Messaging etc.) Apama queries Custom connectivity and integration plug-ins (C++, Java) Command Central for deployment, monitoring Command line DevOps tools Client APIs for custom integration Correlator persistence Dashboards Deployment scripts External in-memory stores (Terracotta) Database integration File system integration Web Services (SOAP) Log file access Monitoring using REST services 27

28 APAMA STANDALONE EXAMPLE USE CASE: TEST TIME OPTIMIZATION As-Is: Today testing equipment validates the quality of each product at the end of assembly leading to high efforts and costs To-Be: Operationalize models & algorithms to reliably predict the test result for each product based on the correlation of different assembly data in real-time Real-time Pattern Detection & Operationalization of Predictive Models Universal Messaging Visualization Alarms & Actions Collaboration with I4.0 28

29 SERVICE GOVERNANCE MANAGED FILE TRANSFER APAMA STANDALONE PREDICTIVE ANALYTICS DATA SCIENTISTS ENVIRONMENT STREAMING ANALYTICS DASHBOARD PRE-PROCESSING CLUSTER SCORING CLUSTER POST-PROCESSING CLUSTER PMML Models for Scoring EVENT PROCESSING LANGUAGE (EPL) PMML EXECUTION PLUGIN IN-MEMORY DATA FABRIC SERVER ARRAY R Scripts & models for Post-Processing UNIVERSAL MESSAGING INTEGRATION AND SERVICES Sensor Data 29

30 APAMA THIN EDGE SMALL FOOTPRINT Apama is a native C++ application FAST speed LOW footprint Requires no JVM overhead Executes within 32MB memory Requires just 88MB disk space on ARM Perfectly suited for lightweight Edge devices 30

31 APAMA BENEFITS LEADER IN FORRESTER STREAMING ANALYTICS WAVE Software AG s Apama continues to be a broadly applicable and perennially capable streaming analytics platform. With its recent acquisition of Cumulocity, Apama deeply extends its reach deeper into industrial IoT use cases by providing device management, digital twin, and other connectivity-oriented services. There is no stopping Apama to become the real-time engine for digital transformation that extends all the way from the factory floor to direct customer interactions. Source: The Forrester Wave : Streaming Analytics, Q3 2017, Forrester Research, Inc., September 7, 2017 The Forrester Wave is copyrighted by Forrester Research, Inc. Forrester and Forrester Wave are trademarks of Forrester Research, Inc. The Forrester Wave is a graphical representation of Forrester's call on a market and is plotted using a detailed spreadsheet with exposed scores, weightings, and comments. Forrester does not endorse any vendor, product, or service depicted in the Forrester Wave. Information is based on best available resources. Opinions reflect judgment at the time and are subject to change. 31

32 APAMA STREAMING ANALYTICS SUMMARY Market-leading streaming analytics for fast-moving data The most complete Streaming Analytics platform event processing, messaging, in-memory data management and visualization combined Fully integrated with Cumulocity IoT Supports extreme scale and performance even with applications requiring complex, temporal and stateful analysis Business user and business analyst interfaces for development and operational control Highest analyst rated platform in its category 32

33 FREE TRIAL CUMULOCITY IoT cumulocity.softwareag.com Software AG. All rights reserved.

34 Q&A PLEASE USE THE Q&A PANEL TO SUBMIT YOUR QUESTIONS Software AG. All rights reserved. For internal use only 2017 Software AG. All rights reserved. For internal use only

35 Questions? Contact Us UPCOMING LIVE WEBINARS June 21, MANAGE: IoT Analytics June 28, EXTEND: IoT Enterprise Integration Software AG. All rights reserved. For internal use only