Mike Spicer is the lead architect for IBM Streams. In this presentation, Mike covers the key new features available in IBM Streams V4.2.

1. © 2016 IBM Corporation
What’s New in IBM Streams V4.2
Mike Spicer
Distinguished Engineer - Lead Architect, IBM Streams

2. © 2016 IBM Corporation2
Important Disclaimer
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3. © 2016 IBM Corporation3
IBM Streams V4.2 Overview
 Edge to Center analytics for IoT use cases
• Integration with Apache Edgent and Watson IoT Platform
 Development with Python & Jupyter Notebooks
• Python application API to develop Streams apps entirely in Python
• Support for Python operators
 Business Rules integration
• Business rules editor and associated SPL Type generation
• Business Rules compiler for optimized execution
 Performance & application deployment improvements
 Automatic fusion & dynamic threading
 Security, serviceability & administration improvements
 New and improved toolkits
• Speech to text

4. © 2016 IBM Corporation4
Edge to Center analytics for IoT use cases
 Apache Edgent for analytics at the edge
• Programming model and lightweight embeddable runtime
• Functional Flow API
• Connectors and Runtime (executable graph of oplets)
• Dynamic control (Change queue size, change out of band data limits)
• Metrics (Optional, rich set of metrics using open source package)
• Open Source Apache Incubation Project
• Developed in the open at Apache using github and JIRA
 Streams Integration for Center to Edge Analytics
• Streams pluggable “Device Hub” interface with IoT Platform implementation
• Manage Edgent apps by device type from Streams
• Control Edgent apps from Streams apps
• Streams console shows summary health of devices and Edgent apps
• Edgent app connects to Streams via IoTP (automatically configured)
IBM Confidential

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Streams, Edgent & Watson IoT Platform Integration
 Edgent for edge analytics – on device or gateway
• Lightweight embedded streaming analytics runtime
• Analyze events locally on the edge
• Reduce communication costs by only sending relevant events
 IBM Watson IoT Platform for optional device hub
• Device management
• Message broker (MQTT)
• Public device hub API supports custom device hub
• Includes message brokers like Kafka
 IBM Streams for streaming analytics
• High performance, full featured streaming analytics
• Build windows of state and correlate across devices
• Have access to data-of-record systems, e.g. medical history
• Control edge device based upon analytics
• Central job management/health summary
• Automatic application connectivity
IBM Watson IoT Platform
Device Hub
IBM Streams
Streaming Analytics
Edgent on Edge
Devices and Gateways
Cluster
Gateway
Edge
DeviceEdge
Device
Messaging
(MQTT, Kafka etc.)

6. © 2016 IBM Corporation6
Business Rules Integration
 Deep Integration of ODM Business Rules
 Tooling Integration
• Embedded Business Rules project in Streams Studio
• Business rules editor (ODM Rules Designer) in Streams Studio
• Generates SPL types from business rules
 Rules Compiler
• Business rules compiled to C++ operator(s)
• Can generate an Operator per rules package
 Dynamic update of rules for running applications
• Compiler generates new library for rules
• Ruleset Operator loads new library dynamically

7. © 2016 IBM Corporation7
Python Topology API
 Implement Streams applications entirely in Python
• Functional Flow API similar to Java Topology API
• Define topology with source, sink and operations
• Submit to standalone and distributed contexts
• Use existing Python modules
• Can use and invoke popular modules like SciKits
• Support for Python V3.5 with Anaconda
• Support for Python 2.7 planned
 Support for Jupyter notebooks
• Build and submit Python Streams application directly from notebook
• View stream data directly in python notebook
• Generate dynamically updating visualisations
 Support for Python functions as Streams operators

8. © 2016 IBM Corporation8
Python Topology API

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Performance and Application Deployment Improvements
 Parallel Region Improvements
• Nested parallel regions
• Parallel split to send tuples to all channels
 Consistent Region Improvements
• Asynchronous non-blocking checkpoints
• Increase concurrency of establishing and restoring consistent states
• Streams Hyperstate Accelerator support for checkpoints
 Scheduling Improvements
• Better utilization across different sized resources
• The ability to reserve application resources for a specific purpose
 Job Configuration Overlays
• Submission time Configuration & parameters in separate config file
• Same application can be run with different configurations with no code changes
 Secure Application Configuration
• A set of properties accessible to applications by name
• Update notifications through JMX
• Scoped at Streams Domain or Instance level

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Automatic Fusion and Dynamic Threading
 Pre V4.2 Behaviour
• Fusion determined at compile time
• Changes to fusion require a recompile
• Default 1 PE process per Operator
• Threads defined manually and statically
• Threaded ports
 New V4.2 Behaviour
• Fusion determined at submission time
• Default automatic fusion
• ~ 1 PE process per 4 Cores
• Based on resources available
• Optional directed fusion
• Specify number of PEs
• 1 to 1 Legacy behaviour
• Manual placement constraints take precedence
• Automatic threading determined at runtime
• Dynamically adjusts based on throughput
All fused
No fusing

11. © 2016 IBM Corporation11
Security, Serviceability and Administration Improvements
 Security Improvements
• Inter host communication encryption
• Management services and Inter PE connection using TLS/SSL
• Kerberos support
• Single Sign On (SSO) authentication
• Microsoft Active Directory Authentication through Kerberos Tokens
 Serviceability Improvements
• Improved defensive coding and error case handling
• Improved logging and troubleshooting
• Improved metrics and zookeeper monitoring
 Rolling Upgrades
• Domain can be upgraded to new version with instances and jobs running
• Each instance can be at a different version and upgraded independently
• Rolling upgrade of instance with jobs running planned for future release
 Console custom templates for hyperlink targets
 Streamtool Improvements
• Persistent command history in console mode
• Manage jobs by jobname

12. © 2016 IBM Corporation12
New and Improved Toolkits
 Speech to Text toolkit
• Converts audio input stream to text output
• Uses Watson Speech to text technology
 Open Source toolkits added to Product in V4.2
• Datetime Toolkit
• IoT Toolkit
• Connectivity with IoT platform
• JDBC toolkit
• JSON toolkit
• Network Toolkit
• Ingest, parse and process network packets
• Map ip addresses to locations, reassemble files from packets
 Geospatial toolkit enhancements
• Support for shared maps for matching points to a map (PointMapMatcher)
 Cybersecurity toolkit enhancements
• QRadar integration
• Improved algorithms
 Telecommunications Event Data Analytics (TEDA) toolkit enhancements
 DPS toolkit support for Streams Hyperstate accelerator

13. © 2016 IBM Corporation13
Streaming Analytics Service in Bluemix
 Provides the capabilities of Streams in the Bluemix Cloud
• Deploy any Streams application to run in the cloud
• The service has been generally available since October 2015
• Available in the US South, United Kingdom, and Sydney* Bluemix Regions
 Capabilities at the initial GA included:
• Integration with key Bluemix services such as Watson IoT, Message Hub, and Cloudant.
• Sample, demo and reference applications.
• Support for many Streams toolkits
 Users can create their Streams instance in seconds from the bluemix.net
web portal.
• Streams instances can be used interactively through the Streams web console or
programmatically via the Streaming Analytics REST API
• Instances are created initially with two dedicated application nodes, but users can
dynamically resize their instance
• Streams instances in Bluemix are highly available
 Streams apps must be developed locally before deploying to the cloud
[ * syndicated in Sydney catalog with deployment in London]

14. © 2016 IBM Corporation14
Bluemix Streams Analytics – What’s new since Streams 4.1?
 New features of the service
• Streaming Analytics Development Guide
• Enabled use of Streams product REST API in the cloud
• Subscription Price Plan
• Auto-stop of idle PayGo instances
• Real-time Hangout Detection (Geospatial Analytics Service)
 Integration with other Bluemix services
• HDFS and HBase (BigInsights on Cloud)
• Object Storage
• RabbitMQ
• DashDB and SQL Database
• Secure Gateway
• Message Connect (experimental)
 Additional demo and sample applications
• Twitter Smackdown Sample for Development Guide
• Water Conservation Starter Kit (IoT use case with Apache Edgent and IoT platform)
• Airport Sentiment Demo

15. © 2016 IBM Corporation15
Bluemix Streaming Analytics – Exploiting new Streams 4.2 features
 Most new Streams 4.2 features are relevant to and can be used with the
Streaming Analytics service in Bluemix:
• Edge to Center analytics for IoT use cases
• Development with Python & Jupyter Notebooks
• Compiled business rules
• Performance & application deployment improvements
• Automatic fusion & dynamic threading
• Inter host communication encryption
• Toolkit improvements
 Target for Streams 4.2 availability in Bluemix is October 19th.

16. © 2016 IBM Corporation16
Find out more and download V4.2 QSE at STREAMSDEV
https://developer.ibm.com/streamsdev/
Streaming Analytics Service in Bluemix
https://console.ng.bluemix.net/catalog/services/streaming-analytics
Get involved in the Apache Edgent Community
http://edgent.incubator.apache.org/
THANK YOU