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IT Strategy in the Application Economy: DevOps, Data Management, and APIs

  • February 2016
  • -
  • Mind Commerce Publishing
  • -
  • 432 pages

Overview:

DevOps is an approach to software development that relies upon effective communication, collaboration, integration, automation, and cooperation between software development and operations organizations. It represents a very important option for organizing teams in the evolving application economy. Awareness and understanding of DevOps, as well as possession of supporting skills, are critically important for IT leaders and their companies.

Data as a Service (DaaS) is defined as any service offered wherein users can access vendor provided databases or host their own databases on vendor managed systems. DaaS is expected to grow significantly in the near future due to a few dominant themes including cloud-based infrastructure/services, enterprise data syndication, and the consumer services trend towards Everything as a Service (XaaS). Telecom Network APIs capitalize on existing network infrastructure and platforms to facilitate many new business opportunities for global Communication Service Providers (CSP) to offer Business-to-Business (B2B) services in a DaaS basis. These three trends taken together represent a transformation in the data and applications economy that has caused CSPs and enterprise companies to rethink business processes, service offerings, and even their philosophy towards product and service realization and support.

This research assesses the future outlook for DevOps in terms of IT adoption and relationship to ICT software development, evaluates market opportunities and provides a market outlook and forecast from 2015 to 2020, and provides an in-depth analysis of the global Telecom Network API market, including business models, business case, best practices, value chain analysis, operator and vendor strategies, vision for the future of telecom data, and a quantitative assessment of the industry from 2015 to 2020. All purchases of Mind Commerce reports includes time with an expert analyst who will help you link key findings in the report to the business issues you're addressing. This needs to be used within three months of purchasing the report.

Target Audience:
API Aggregators
Investment Firms
Application Developers
Mobile Device Vendors
Mobile Network Carriers
Data services companies
Cloud services companies
Service Bureau Companies
Data infrastructure providers
Wireless Infrastructure Vendors
Telecom Managed Service Providers
Major enterprise and businesses of all types

Table Of Contents

IT Strategy in the Application Economy: DevOps, Data Management, and APIs
DevOps: Market Opportunities and Forecasts 2015 - 2020

1.0 INTRODUCTION
1.1 EXECUTIVE SUMMARY
1.2 RESEARCH OBJECTIVES
1.3 QUESTIONS ANSWERED
1.4 RESEARCH METHODOLOGY
1.5 TARGET AUDIENCE
1.6 COMPANIES MENTIONED
2.0 ENTERPRISE IT TRENDS AND DEVOPS
2.1 ENTERPRISE IT TREND
2.2 IT MODERNIZATION AND CLOUD NIGHTMARE
2.3 DEMAND LED IT DELIVERY APPROACH
2.4 CHANGING PATTERN OF STRATEGIC OBJECTIVES
2.5 ENTERPRISE IT CHALLENGES
2.6 AGILITY - STABILITY PARADOX
2.7 EMERGENCE OF DEVOPS
2.8 TRANSFORMING EXISTING IT METHODOLOGY TO DEVOPS APPRAOCH
3.0 DEVOPS ECOSYSTEM
3.1 WHAT IS DEVOPS?
3.2 FEATURES OF DEVOPS
3.2.1 COLLABORATIVE DEVELOPMENT
3.2.2 AUTOMATED TEST and CONFIGURATION
3.2.3 CONTINUOUS INTEGRATION
3.2.4 CONTINUOUS MONITORING AND FEEDBACK
3.3 BENEFITS OF DEVOPS
3.3.1 BUSINESS INNOVATION
3.3.2 IT DEPLOYMENT
3.4 DEVOPS LIFECYCLE
3.5 DEVOPS CHALLENGES
3.6 IT SERVICE MANAGEMENT (ITSM) AND DEVOPS
3.7 SDN AND DEVOPS
3.8 DATA VIRTUALIZATION AND DEVOPS
3.9 SERVICE VIRTUALIZATION AND DEVOPS
3.10 MANAGED SERVICE AND DEVOPS
3.11 APPLICATION MONITORING AND DEVOPS
3.12 MANAGED PRIVATE PAAS AND DEVOPS
3.13 SMAC TECHNOLOGIES AND DEVOPS
3.14 MOBILE DEVOPS
3.15 DEVOPS AND CLOUD, IOT, BIG DATA and SDS
3.16 MANAGEMENT LAYER AND DEVOPS REVENUE
3.17 DEVOPS LANDSCAPE BY LAYER
4.0 DEVOPS MARKET DRIVER
4.1 GROWTH DRIVERS
4.1.1 ENTERPRISE TRANSITION
4.1.2 REDUCTION IN IT SPENDING
4.1.3 SOFTWARE AND TELECOM
4.1.4 HYBRID CLOUD
4.1.5 DATA CENTER
4.1.6 EVERYTHING AS A SERVICE
4.2 TECHNOLOGY DRIVER
4.2.1 SONARQUBE
4.2.2 CONTINUOUS INTEGRATION (CI)
4.2.3 LEAN STARTUP
4.2.4 AGILE SOFTWARE DEVELOPMENT
4.2.5 AUTOMATION
4.2.6 CLOUD COMPUTING
4.2.7 SDN
4.2.8 VIRTUALIZATION
4.2.9 OPTIMIZATION
4.2.10 INFRASTRUCTURE AS CODE (IAC)
4.2.11 OPENSTACK
5.0 DEVOPS IN ENTERPRISE
5.1 DEVOPS ENVIRONMENT
5.2 ENTERPRISE RISK
5.3 BUILDING DEVOPS CULTURE
5.3.1 IT SKILL GAP
5.3.2 DEVOP BLUEPRINT
5.3.3 TECHNICAL INVESTMENT
5.3.4 CHANGE MANAGEMENT
5.3.5 AUTOMATION
5.3.6 TRADITIONAL BARRIERS
5.3.7 CUSTOMER FACING SYSTEM
5.3.8 LEGACY SYSTEM INTEGRATION
5.3.9 COLLABORATIVE INTEGRATION
5.4 REAL TIME DEVOPS
5.5 ENTERPRISE CHALLENGES
5.6 DEVOPS APPROACH AND STEPS
5.7 DEVOPS SECURITY
5.8 CYBER SECURITY
5.9 TELECOM DEVOPS CULTURE
5.10 ENTERPRISE IMPACT
5.10.1 AGILE DEVELOPMENT
5.10.2 IT OPERATION MANAGEMENT
5.10.3 DIGITAL AGILITY
5.11 DEVOPS IMPLEMENTATION
5.12 IT PERFORMANCE
5.13 IT PERFORMANCE METRICS
5.14 SIZE OF THE ENTERPRISE
5.15 DEVOPS AS CAREER
5.16 BENEFIT METRICS
6.0 DEVOPS IMPLEMENTATION CASE STUDIES
6.1 SPACEX
6.2 WEST VIRGINIA STATE
6.3 FOX SPORTS
6.4 IPROPERTY
6.5 GRAYLOG
6.6 RABOBANK
6.7 NATIONWIDE INSURANCE
7.0 DEVOPS MARKET FORECASTS 2015 - 2020
7.1 GLOBAL DEVOPS MARKET REVENUE 2015 - 2020
7.2 DEVOPS TOOLSETS PAAS REVENUE 2015 - 2020 57
7.3 DEVOPVS MARKET REVENUE BY REGION 2015 - 2020
7.4 OPENSTACK VENDOR REVENUE INCLUDING DEVOPS TOOLS 2015 - 2020
7.5 GLOBAL ENTERPRISE INVESTMENT 2015 - 2020
7.6 DEVOPS ENTERPRISE ADOPTION 2016 - 2020
7.7 DEVOPS BENEFIT METRICS
7.8 DEVOPS ROI METRICS FOR BUSINESS AND IT
8.0 DEVOPS VENDORS
8.1 IBM
8.2 CIGNITI TECHNOLOGIES
8.3 ANSIBLE
8.4 CLARIVE SOFTWARE
8.5 DOCKER
8.6 INEDO
8.7 SCRIPTROCK
8.8 AMAZON WEB SERVICES
8.9 COREOS
8.10 CHEF
8.11 PUPPET LAB
8.12 SALTSTACK
8.13 ATLASSIAN
8.14 TASKTOP
8.15 CODENVY
8.16 SMARTBEAR
8.17 CA TECHNOLOGIES
8.18 SERVICENOW
8.19 CF ENGINE
8.20 CISCO
8.21 COLLABNET
8.22 DBMAESTRO
8.23 HP
8.24 MICROSOFT
8.25 RACKSPACE
8.26 RALLY
8.27 REDHAT
8.28 SPIRENT
8.29 SPLUNK
8.30 VERSIONONE
8.31 VMWARE
8.32 XEBIALABS
8.33 MIDVISION
8.34 INAKA
8.35 CAKESOLUTIONS
8.36 GITHUB
9.0 CONCLUSIONS AND RECOMMENDATIONS
9.1 RECOMMENDATIONS FOR ENTERPRISE
9.2 RECOMMENDATIONS FOR TOOLSET VENDORS
9.3 RECOMMENDATIONS FOR INDEPENDENT PRACTITIONERS

Figures

Figure 1: DevOps Concept and Ecosystem
Figure 2: DevOps Features driven by Philosophy
Figure 3: DevOps Lifecycle Diagram
Figure 4: Data Virtualization Platform through Masking
Figure 5: DevOps Walls inside Enterprise
Figure 6: DevOps and SMAC Integration Diagram
Figure 7: DevOps Layer
Figure 8: DevOps Companies by Layer
Figure 9: DevOps Culture Components
Figure 10: Real Time DevOps Process and Benefits
Figure 11: Security at DevOps Process
Figure 12: DevOps Implementation Framework
Figure 13: DevOps Benefit Metrics
Figure 14: DevOps Adoption Trend of Global 2000 Organization
Figure 15: Cigniti DevOps QA Framework
Figure 16: Ansible Automation to Environment Framework
Figure 17: Clarive DevOps Solution Model
Figure 18: Docker DevOps Model
Figure 19: Chef Kung Fu Style DevOps Principles
Figure 20: SaltStack DevOps Integration Framework
Figure 21: SmartBear API Powered DevOps Diagram
Figure 22: CollabNet DevOps Framework
Figure 23: HP DevOps Framework
Figure 24: RedHat DevOps Approach

Tables

Table 1: DevOps Enterprise Challenges
Table 2: Benefits of Managed Services to DevOps Enterprise
Table 3: Application Monitoring Tools for DevOps
Table 4: Global DevOps Revenue by Toolsets and Consulting 2015 - 2020
Table 5: Global DevOps Toolsets Rev: Proprietary vs. OpenStack 2015 - 2020
Table 6: DevOps Market Revenue by NA, APAC, Europe, Others 2015 - 2020
Table 7: OpenStack Vendor Revenue by Category 2015 - 2020
Table 8: Global IT Investment by Category 2015 - 2020
Table 9: DevOps Benefit Metrics
Table 10: DevOps ROI Metrics for Business
Table 11: DevOps ROI Metrics for IT

Data as a Service (DaaS) Market and Forecasts 2015 - 2020

1 Introduction
1.1 Executive Summary
1.2 Topics Covered
1.3 Key Findings
1.4 Target Audience
2 DaaS Technologies
2.1 Cloud
2.2 Database Approaches and Solutions
2.2.1 Relational Database Management System (RDBS)
2.2.2 NoSQL
2.2.3 Hadoop
2.2.4 High Performance Computing Cluster (HPCC)
2.2.5 OpenStack
2.3 DaaS and the XaaS Ecosystem
2.4 Open Data Center Alliance
2.5 Market Sizing by Horizontal
3 DaaS Market
3.1 Market Overview
3.1.1 Data-as-a-Service: A movement
3.1.2 Data Structure
3.1.3 Specialization
3.1.4 Vendors
3.2 Vendor Analysis and Prospects
3.2.1 Large Vendors: BDaaS
3.2.2 Mid-sized Vendors
3.2.3 Small Vendors: DaaS and SaaS
3.2.4 Market Size: BDaaS vs. RDBMS
3.3 Market Drivers and Constraints
3.3.1 Drivers
3.3.1.1 Business Intelligence and DaaS Integration
3.3.1.2 The Cloud Enabler DaaS
3.3.1.3 XaaS Drives DaaS
3.3.2 Constraints
3.3.2.1 Issues Relating to Data-as-a-Service Integration
3.4 Barriers and Challenges to DaaS Adoption
3.4.1 Enterprises Reluctance to Change
3.4.2 Responsibility of Data Security Externalized
3.4.3 Security Concerns are Real
3.4.4 Cyber Attacks
3.4.5 Unclear Agreements
3.4.6 Complexity is a Deterrent
3.4.7 Lack of Cloud Interoperability
3.4.8 Service Provider Resistance to Audits
3.4.9 Viability of Third-party Providers
3.4.10 No Move of Systems and Data is without Cost
3.4.11 Lack of Integration Features in the Public Cloud results in Reduced Functionality
3.5 Market Share and Geographic Influence
3.6 Vendors
3.6.1 1010data
3.6.2 Amazon
3.6.3 Clickfox
3.6.4 Datameer
3.6.5 Google
3.6.6 Hewlett-Packard
3.6.7 IBM
3.6.8 Infosys
3.6.9 Microsoft
3.6.10 Oracle
3.6.11 Rackspace
3.6.12 Salesforce
3.6.13 Splunk
3.6.14 Teradata
3.6.15 Tresata
4 DaaS Strategies
4.1 General Strategies
4.1.1 Tiered Data Focus
4.1.2 Value-based Pricing
4.1.3 Open Development Environment
4.2 Specific Strategies
4.2.1 Service Ecosystem and Platforms
4.2.2 Bringing to Together Multiple Sources for Mash-ups
4.2.3 Developing Value-added Services (VAS) as Proof Points
4.2.4 Open Access to all Entities including Competitors
4.2.5 Prepare for Big Opportunities with the Internet of Things (IoT)
4.3 Service Provider Strategies
4.3.1 Telecom Network Operators
4.3.2 Data Center Providers
4.3.3 Managed Service Providers
4.4 Infrastructure Provider Strategies
4.4.1 Enable New Business Models
4.5 Application Developer Strategies
5 DaaS based Applications
5.1 Business Intelligence
5.2 Development Environments
5.3 Verification and Authorization
5.4 Reporting and Analytics
5.5 DaaS in Healthcare
5.6 DaaS and Wearable technology
5.7 DaaS in the Government Sector
5.8 DaaS for Media and Entertainment
5.9 DaaS for Telecoms
5.10 DaaS for Insurance
5.11 DaaS for Utilities and Energy Sector
5.12 DaaS for Pharmaceuticals
5.13 DaaS for Financial Services
6 Market Outlook and Future of DaaS
6.1 Recent Security Concerns
6.2 Cloud Trends
6.2.1 Hybrid Computing
6.2.2 Multi-Cloud
6.2.3 Cloud Bursting
6.3 General Data Trends
6.4 Enterprise Leverages own Data and Telecom
6.4.1 Web APIs
6.4.2 SOA and Enterprise APIs
6.4.3 Cloud APIs
6.4.4 Telecom APIs
6.5 Data Federation Emerges for DaaS
7 Conclusions
8 Appendix
8.1 Structured vs. Unstructured Data
8.1.1 Structured Database Services in Telecom
8.1.2 Unstructured Database Services in Telecom and Enterprise
8.1.3 Emerging Hybrid (Structured/Unstructured) Database Services
8.2 Data Architecture and Functionality
8.2.1 Data Architecture
8.2.1.1 Data Models and Modelling
8.2.1.2 DaaS Architecture
8.2.2 Data Mart vs. Data Warehouse
8.2.3 Data Gateway
8.2.4 Data Mediation
8.3 Master Data Management (MDM)
8.3.1 Understanding MDM
8.3.1.1 Transactional vs. Non-transactional Data
8.3.1.2 Reference vs. Analytics Data
8.3.2 MDM and DaaS
8.3.2.1 Data Acquisition and Provisioning
8.3.2.2 Data Warehousing and Business Intelligence
8.3.2.3 Analytics and Virtualization
8.3.2.4 Data Governance
8.4 Data Mining
8.4.1 Data Capture
8.4.1.1 Event Detection
8.4.1.2 Capture Methods
8.4.2 Data Mining Tools

Figures

Figure 1: Cloud Computing Service Model Stack and Principle Consumers
Figure 2: DaaS across Horizontal and Vertical Segments
Figure 3: Different Data Types and Functions in DaaS
Figure 4: Ecosystem and Platform Model
Figure 5: Ecosystem and Platform Model
Figure 6: DaaS and IoT Mediation for Smartgrid
Figure 7: Internet of Things (IoT) and DaaS
Figure 8: Telecom API Value Chain for DaaS
Figure 9: DaaS, Verification and Authorization
Figure 10: Web APIs
Figure 11: Services Oriented Architecture
Figure 12: Cloud Services, DaaS, and APIs
Figure 13: Telecom APIs
Figure 14: Federated Data vs. Non-Federated Models
Figure 15: Federated Data at Functional Level
Figure 16: Federated Data at City Level
Figure 17: Federated Data at Global Level
Figure 18: Federation Requires Mediation Data
Figure 19: Mediation Data Synchronization
Figure 20: Hybrid Data in Next Generation Applications
Figure 21: Traditional Data Architecture
Figure 22: Data Architecture Modeling
Figure 23: DaaS Data Architecture
Figure 24: Location Data Mediation
Figure 25: Data Mediation in IoT
Figure 26: Data Mediation for Smartgrids
Figure 27: Enterprise Data Types
Figure 28: Data Governance
Figure 29: Data Flow
Figure 30: Processing Streaming Data

Telecom Network API Marketplace: Strategy, Ecosystem, Players and Forecasts 2015 - 2020

1 Introduction 11
1.1 Executive Summary 11
1.2 Topics Covered 12
1.3 Key Findings 14
1.4 Target Audience 15
1.5 Companies Mentioned 16
2 Telecom Network API Overview 18
2.1 Defining Network APIs 18
2.2 Why Carriers are Adopting Telecom Network APIs 19
2.2.1 Need for New Revenue Sources 20
2.2.2 B2B Services and Asymmetric Business Models 21
2.3 Telecom Network API Categories 22
2.3.1 Web Real-time Communications (WebRTC) 22
2.3.2 SMS and RCS-E 24
2.3.3 Presence 24
2.3.4 MMS 24
2.3.5 Location 24
2.3.6 Payments 25
2.3.7 Voice/Speech 25
2.3.8 Voice Control 25
2.3.9 Multimedia Voice Control 25
2.3.10 M2M 25
2.3.11 SDM/Identity Management 25
2.3.12 Subscriber Profile 26
2.3.13 QoS 26
2.3.14 ID/SSO 26
2.3.15 Content Delivery 26
2.3.16 Hosted UC 26
2.3.17 Directory 26
2.3.18 Number Provisioning 26
2.3.19 USSD 27
2.3.20 Billing of Non-Digital Goods 27
2.3.21 Advertising 27
2.3.22 Collaboration 27
2.3.23 IVR/Voice Store 27
2.4 Telecom Network API Business Models 28
2.4.1 Two-Sided Business Model 28
2.4.2 Exposing APIs to Developers 28
2.4.3 Web Mash-ups 29
2.5 Segmentation 29
2.5.1 Users by Segment 29
2.5.2 Workforce Management 29
2.6 Competitive Issues 30
2.6.1 Reduced TCO 30
2.6.2 Open APIs 30
2.6.3 Configurability 30
2.7 Percentage of Applications that use APIs 31
2.8 Telecom API Revenue Potential 32
2.8.1 Standalone API Revenue vs. Finished Goods Revenue 33
2.8.2 Telecom API-enabled Mobile VAS Applications 35
2.8.3 Carrier Focus on Telecom API's for the Enterprise 38
2.9 Telecom Network API Usage by Industry Segment 44
2.10 Telecom Network API Value Chain 44
2.10.1 Telecom API Value Chain 44
2.10.2 How the Value Chain Evolve 46
2.10.3 API Transaction Value Split among Players 46
2.11 Cost for Different API Transactions 48
2.12 Volume of API Transactions 48
3 API Aggregation 50
3.1 The Role of API Aggregators 50
3.2 Total Cost Usage for APIs with Aggregators 50
3.2.1 Start-up Costs 51
3.2.2 Transaction Costs 51
3.2.3 Ongoing Maintenance/Support 51
3.2.4 Professional Services by Intermediaries 51
3.3 Aggregator API Usage by Category 52
3.3.1 An LBS Case Study: LOC-AID 52
3.3.2 Aggregation: Intersection of Two Big Needs 52
3.3.3 The Case for Other API Categories 53
3.3.4 Moving Towards New Business Models 54
4 Enterprise and Telecom API Marketplace 55
4.1 Data as a Service (DaaS) 55
4.1.1 Carrier Structured and Unstructured Data 58
4.1.2 Carrier Data Management in DaaS 62
4.1.3 Data Federation in the DaaS Ecosystem 62
4.2 API Market Makers 64
4.2.1 mashape 64
4.2.2 Mulesoft 65
4.3 Need for a New Type of Application Marketplace: CAM 66
4.3.1 Communications-enabled App Marketplace (CAM) 66
4.3.2 CAM Market Opportunities and Challenges 67
5 Telecom API Enabled App Use Cases 69
5.1 Monetization of Communications-enabled Apps 69
5.1.1 Direct API Revenue 69
5.1.2 Data Monetization 70
5.1.3 Cost Savings 70
5.1.4 Higher Usage 70
5.1.5 Churn Reduction 70
5.2 Use Case Issues 71
5.2.1 Security 71
5.2.2 Interoperability 71
6 Non-Telecom Network APIs and Mash-ups 73
6.1 Non-Telecom Network APIs 73
6.1.1 Twitter 73
6.1.2 Netflix API 74
6.1.3 Google Maps 74
6.1.4 Facebook 75
6.1.5 YouTube 75
6.1.6 Flickr 76
6.1.7 eBay 76
6.1.8 Last.fm 77
6.1.9 Amazon Web Services 77
6.1.10 Bing Maps 78
6.1.11 Yahoo Web Search API 78
6.1.12 Shopping.com 79
6.1.13 Salesforce.com 80
6.2 Mash-ups 81
6.2.1 BBC News on Mobile 81
6.2.2 GenSMS emailSMS 81
6.2.3 Foursquare 82
6.2.4 Amazon SNS and Nexmo 82
6.2.5 Triage.me 83
6.2.6 MappyHealth 83
6.2.7 Lunchflock 84
6.2.8 Mobile Time Tracking 84
6.2.9 Fitsquare 84
6.2.10 GeoSMS 84
6.2.11 FONFinder 85
6.2.12 Pound Docs 85
6.2.13 140Call 85
6.2.14 Salesforce SMS 85
7 Carrier Strategies 86
7.1 Carrier Market Strategy and Positioning 86
7.1.1 Increasing API Investments 86
7.1.2 The Rise of SDM 86
7.1.3 Telecom API Standardization 87
7.1.4 Carrier Attitudes towards APIs: U.S vs. Asia Pacific and Western Europe 89
7.2 Carrier API Programs Worldwide 89
7.2.1 ATandT Mobility 89
7.2.2 Verizon Wireless 93
7.2.3 Vodafone 95
7.2.4 France Telecom 95
7.2.5 Telefonica 97
7.3 Carriers and Internal Telecom API Usage 99
7.3.1 The Case for Internal Usage 99
7.3.2 Internal Telecom API Use Cases 100
7.4 Carriers and OTT Service Providers 101
7.4.1 Allowing OTT Providers to Manage Applications 101
7.4.2 Carriers Lack the Innovative Skills to Capitalize on APIs Alone 101
7.5 Carriers and Value-added Services (VAS) 102
7.5.1 The Role and Importance of VAS 102
7.5.2 The Case for Carrier Communication-enabled VAS 103
7.5.3 Challenges and Opportunities for Carriers in VAS 104
8 API enabled App Developer Strategies 106
8.1 A Critical Asset to Developers 106
8.2 Stimulating the Growth of API Releases 106
8.3 Working alongside Carrier Programs 106
8.4 Developer Preferences: Google vs Carriers 107
9 Telecom API Vendor Strategies 108
9.1 Positioning as Enablers in the Value Chain 108
9.2 Moving Away from a Box/Product Supplier Strategy 108
9.3 Telecom API Companies and Solutions 109
9.3.1 Alcatel Lucent 109
9.3.2 UnboundID 110
9.3.3 Twilio 112
9.3.4 LOC-AID 113
9.3.5 Placecast 114
9.3.6 Samsung 117
9.3.7 ATandT Mobility 118
9.3.8 Apigee 118
9.3.9 2600 Hz 120
9.3.10 Callfire 120
9.3.11 Plivo 121
9.3.12 Tropo (now part of Cisco) 122
9.3.13 Urban Airship 122
9.3.14 Voxeo (now Aspect Software) 123
9.3.15 TeleStax 123
9.3.16 Intel 124
9.3.17 Competitive Differentiation 126
10 Market Analysis and Forecasts 127
10.1 Telecom Network API Revenue 2015 - 2020 127
10.2 Telecom Network APIs Revenue by API Category 2015 - 2020 128
10.2.1 Messaging API Revenues 129
10.2.2 LBS API Revenues 130
10.2.3 SDM API Revenues 131
10.2.4 Payment API Revenues 132
10.2.5 Internet of Things (IoT) API Revenues 133
10.2.6 Other API Revenues 134
10.3 Telecom API Revenue by Region 2015 - 2020 135
10.3.1 Asia Pacific 136
10.3.2 Eastern Europe 137
10.3.3 Latin and Central America 138
10.3.4 Middle East and Africa 139
10.3.5 North America 140
10.3.6 Western Europe 141
11 Technology and Market Drivers for Future API Market Growth 142
11.1 Service Oriented Architecture (SOA) 142
11.2 Software Defined Networks (SDN) 145
11.3 Virtualization 146
11.3.1 Network Function Virtualization (NFV) 148
11.3.2 Virtualization beyond Network Functions 151
11.4 The Internet of Things (IoT) 152
11.4.1 IoT Definition 152
11.4.2 IoT Technologies 155
11.4.3 IoT Applications 171
11.4.4 IoT Solutions 172
11.4.5 IoT, DaaS, and APIs (Telecom and Enterprise) 172
12 Expert Opinion: TeleStax 178
13 Expert Opinion: Twilio 183
14 Expert Opinion: Point.io 189
15 Expert Opinion: Nexmo 192
16 Appendix 195
16.1 Research Methodology 195
16.2 Telecom API Definitions 197
16.3 More on Telecom APIs and DaaS 201
16.3.1 Tiered Data Focus 202
16.3.2 Value-based Pricing 204
16.3.3 Open Development Environment 205
16.3.4 Specific Strategies 206
16.3.4.1 Service Ecosystem and Platforms 206
16.3.4.2 Bringing to Together Multiple Sources for Mash-ups 207
16.3.4.3 Developing Value-added Services (VAS) as Proof Points 208
16.3.4.4 Open Access to all Entities including Competitors 208
16.3.4.5 Prepare for Big Opportunities with the Internet of Things (IoT) 209

Figures

Figure 1: Wireless Carrier Assets 19
Figure 2: Telecom API: Standalone vs. Finished Services 33
Figure 3: RCS and Telecom API Integration 36
Figure 4: RCS Revenue Forecast 37
Figure 5: Business vs. Consumer Telecom API Focus 40
Figure 6: Enterprise Dashboard 41
Figure 7: Enterprise Dashboard App Example 42
Figure 8: Telecom Network API Value Chain 45
Figure 9: Value Split among Aggregators, Carriers and Enterprise for API Transactions: 2012 - 2019 47
Figure 10: API Transaction Costs (US Cents) 2012 - 2019 48
Figure 11: Volume of API Transactions for a Tier 1 Carrier (Billions per Month): 2015 - 2020 49
Figure 12: Cloud Services and APIs 58
Figure 13: GSMA OneAPI: Benefits to Stakeholders 88
Figure 14: ATandT Wireless API Catalog 90
Figure 15: Verizon Wireless API Program 93
Figure 16: France Telecom (Orange) APIs 96
Figure 17: Telefonica APIs 98
Figure 18: Carrier Internal Use of Telecom APIs 100
Figure 19: UnboundID's Portfolio of Services 111
Figure 20: Twilio's Portfolio of Services 112
Figure 21: LOC-AID Exchange Server Architecture 113
Figure 22: Placecast's ShopAlerts Solution 115
Figure 23: Apigee Portfolio of Services 119
Figure 24: Telecom API Revenue (USD Billions) 2015 - 2020 127
Figure 25: Telecom API Revenue (USD Billions) by API Category 2015 - 2020 128
Figure 26: Messaging APIs Revenue (USD Billions) 2015 - 2020 129
Figure 27: LBS APIs Revenue (USD Billions) 2015 - 2020 130
Figure 28: SDM APIs Revenue (USD Billions) 2015 - 2020 131
Figure 29: Payment APIs Revenue (USD Billions) 2015 - 2020 132
Figure 30: IoT API Revenue (USD Billions) 2015 - 2020 133
Figure 31: APIs Revenue for Other Categories (USD Billions) 2015 - 2020 134
Figure 32: Telecom API Revenue (USD Billions) by Region 2015 - 2020 135
Figure 33: Telecom API Revenue (USD Billions) Asia Pacific 2015 - 2020 136
Figure 34: Telecom API Revenue (USD Billions) Eastern Europe 2015 - 2020 137
Figure 35: Telecom API Revenue (USD Billions) Latin and Central America 2015 - 2020 138
Figure 36: Telecom API Revenue (USD Billions) Middle East and Africa 2015 - 2020 139
Figure 37: Telecom API Revenue (USD Billions) North America 2015 - 2020 140
Figure 38: Telecom API Revenue (USD Billions) Western Europe 2015 - 2020 141
Figure 39: Services Oriented Architecture 143
Figure 40: Growth of Connected Devices 159
Figure 41: IoT and Telecom API Topology 176
Figure 42: Telestax App Store Funnel 180
Figure 43: On-Premise vs. Twilio 188
Figure 44: Point.io and API Ecosystem 189
Figure 45: Different Data Types and Functions in DaaS 203
Figure 46: Ecosystem and Platform Model 206
Figure 47: Telecom API and Internet of Things Mediation 210
Figure 48: DaaS and IoT Mediation for Smartgrid 212

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Cloud Computing Industry in China - Forecast

  • March 2017
    16 pages
  • Cloud Computing  

  • China  

    United States  

    Asia  

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Cloud Computing Industry in Europe

  • March 2017
    34 pages
  • Cloud Computing  

  • Europe  

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Cloud Computing Market in the US

  • March 2017
    2 pages
  • Cloud Computing  

  • United States  

View report >

Related Market Segments :

Cloud Computing

ref:plp2016

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