Raising Abstractions for the Software Defined Business
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1 Smart Process is Smart Business Raising Abstractions for the Software Defined Business Presented to GoTo Chicago, May 12, 2015 Dave Duggal, Managing Director Bill Malyk, Chief System Architect EnterpriseWeb is a Registered Trademark of EnterpriseWeb LLC
2 The real-world is dynamic, distributed and diverse Traditional IT methods don t respond, scale or adapt fast enough
3 Recreating Silos in the Cloud Infrastructure is virtualized and horizontal, but apps are still 3-tier vertically integrated
4 As operations fragment management is lost Policies? Version Control? Governance? Security? Change? Analytics? Copyright 2013, EnterpriseWeb LLC
5 The Application Model is broken
6 but what we really need is flexibility
7 Rate of Change Reality Gap Time to cope with accelerating rate of change
8 varied perspectives
9 and increasing demands for interoperability
10 EnterpriseWeb has re-invented middleware enabling the real-time data-driven enterprise +1 (646) x444
11 A lightweight, scale-out architecture for responsive and highly-connected processes personalize user-experiences dynamically enforce compliance automate IT governance optimize Agile, DevOps, Cloud IoT and system pipelines integrate value-chains
12 Radically Simplifying Distributed Processes unified object model shared methods/common management middleware functions delivered as services immutable-shared memory, horizontal scale-out plug-in fabric
13 The Application Middleware Stack Event Processor Enterprise Service Bus Business Process Engine Business Rules Engine Relational Database NoSQL Analytics Engine Scheduler Service Catalog API Registry
14 From Vertical Specialization to Horizontal Generalization Event Processor Enterprise Service Bus Business Process Engine Business Rules Engine LESS CRUFT Relational Database NoSQL Analytics Engine Scheduler Service Catalog API Registry
15 From Mass Production of to Mass Customization Compute Cycles and IOPS More stuff Application Stack
16 Application middleware stacks are inadequate for distributed intelligent systems Stacks distribute a problem over a network of isolated components (cost, footprint, complexity, latency) Minimal state is passed in a linear chain of messages (no shared memory for transaction, constrains reasoning) Not conceived for dynamic data-driven interactions (tightly-coupled, brittle, siloed applications) Components don t all scale the same so applications cannot scale-out (increased activity = more middleware, not elastic) To support more complex applications you add more components (e.g. management, big data, IoT, etc. )
17 Example of small middleware stack implementation Enterprise Service Bus Middleware Persistence BPM/Workflow Components Analytics Components ESB ESB Load Balancer DB DB Load Balancer BPMN BPEL ETL Graph Analysis Machine Learning Statistics Packages Hypervisor K/ OpenStack Hypervisor K/ OpenStack Hypervisor K/ OpenStack Hypervisor K/ OpenStack Storage Network Storage Network Storage Network Storage Network Big Data Distributed Processing Big Data Distributed Processing Rules Engine Schedule r Big Data Node Big Data Node Big Data Node Big Data Node Big Data Node Rules Engine Hypervisor K/ OpenStack Hypervisor K/ OpenStack Hypervisor K/ OpenStack Storage Network Storage Network Storage Network Web Service Web Service Data Source Hypervisor K/ OpenStack Storage Network
18 Example of simple middleware stack transaction Event ESB ESB Load Balancer DB DB Load Balancer BPMN BPEL ETL Graph Analysis Machine Learning Statistics Packages Schedule Big Data Big Data r Node Node Big Data Big Data Big Data Node Node Node Rules Engine Web Web Data Service Service Source Service Call 1 Multiple Service Calls Service Call 2 Service Call 3
19 Example of Inter-process communications Application API Web-Service API
20 Example of standard EnterpriseWeb implementation EWeb EWeb Hypervisor Storage K/ OpenStack Network Web Service Web Service Data Source Hypervisor Storage K/ OpenStack Network
21 Example of simple EnterpriseWeb transaction Event EWeb Web Web Data Service Service Source Service Call 1 Multiple Service Calls Service Call 2 Service Call 3
22 Example of Inter-process communications in EnterpriseWeb Event EWeb Web Web Data Service Service Source Service Call 1 Multiple Service Calls Service Call 2 Service Call 3
23 The platform is based on an abstraction, every endpoint is a graph object Modeled as set of loosely-coupled relationships
24 Modeling the Application Graph Codebase Pointers to Repository Dependencies Application Resources Configuration Environment Variables Contract Pre-Conditions Contract Post-Conditions Logs Ordered, Time-Series Event Port Binding Connection Details Backing Service Databases, Systems, Machine/Devices
25 Objects can be composed to form higher-order functions, entities, data models, processes The abstraction harmonizes the representation of diverse and distributed resources, in order to simplify distributed computing
26 A Unified Object Model Index Multi-Model NoSQL Store Web-services REST-APIs Microservice Remote Objects In-Process Objects Business Entities Functions Policies Data Models Process Models Org Models Network Models UI Components Content
27 Logical Repository Data Metadata, Instance Data, Event Logs, Version History, Content, Models Index Web-services REST-APIs Microservice Remote Objects Code Code Repository, Service Catalog, API Registry, Application Resource Library In-Process Objects Business Entities Functions Policies Data Models Process Models Org Models Network Models UI Components Content Multi-Model NoSQL Store
28 Instrumented Infrastructure Index Multi-Model NoSQL Store In-Process Objects Web-services REST-APIs Microservice Remote Infrastructure Instantiate, Configure, Monitor, Balance, Stop, Tear-down Compute Virtual Machines Containers Bare Metal Storage HDFS Nodes SQL / NoSQL SAN Network SDN NFV Machines / Devices M2M iot
29 It presents an overlay application fabric, over diverse and distributed endpoints
30 Under Common Management Index System Security access, search, navigation Semantics Declarative Composition Modeling Environment Unified Object Model Platform Services Shared Immutable Memory Shared Libraries In-Process Objects Web-services REST-APIs Microservice Policy Management Remote Objects
31 At run-time events are handled by goal-oriented software agents The agents use interaction metadata to semantically interpret graph object
32 Anatomy of an Interaction Calls Agent EVENT Agent delivers custom payload including next-best-actions and updates repository, logs, indexes and tags Agent Interprets Model Isolated thread provides run-time container Agent connects, transforms Resources to advance processing Agent fetches representations of Resources and resolves queries to URIs Stateless Asynchronous ACID Transactions Distributable Threads
33 Request / Event Security / Identity Application Logic Cross Process Compliance Enterprise IT Governance Context-enhanced processing of functional and non-functional concerns System Controls Copyright 2014, EnterpriseWeb LLC
34 Process An asynchronous series of ACID transactions Copyright 2014, EnterpriseWeb LLC
35 Our high-level abstraction, takes virtualization to the application layer. We radically simplify distributed computing to enable the software defined business.
36 An award-winning platform Best Semantic Platform Best GRC Solution Most Innovative Solution The Software & Information Industry Association 2014 Award Winner - Healthcare Most Disruptive Solution
37 Use Cases: Expert Systems; DevOps Automation; Dynamic Pricing; Customer Experience Management; Supply Chain Optimization; Integrated Operations; Cross-Process Governance; Event-Monitoring; Predictive Maintenance; Internet-of-Things; Inflight Data Quality Management; Flexible Master Data Management; Adaptive Case Management; etc. Deploys on the Cloud or on-premise +1 (646) x444 Copyright 2014, EnterpriseWeb LLC
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