Gartner defines AI-augmented software testing tools as enablers of continuous, self-optimizing and adaptive automated testing through the use of AI technologies. The capabilities run the gamut of the testing life cycle including test scenario and test case generation, test automation generation, test suite optimization and prioritization, test analysis and defect prediction as well as test effort estimation and decision making. These tools help software engineering teams to increase test coverage, test efficacy and robustness. They assist humans in their testing efforts and reduce the need for human intervention in the different phases of testing.
Active metadata management is a set of capabilities that enables continuous access and processing of metadata that support ongoing analysis over a different spectrum of maturity, use cases and vendor solutions. Active metadata outputs range from design recommendations based upon execution results and reports of runtime steps through, and indicators of, business outcomes achieved. The resulting recommendations from those analytics are issued as design inputs to humans or system-level instructions that are expected to have a response.
Analytics and business intelligence platforms — enabled by IT and augmented by AI — empower users to model, analyze and share data. Analytics and business intelligence (ABI) platforms enable organizations to understand their data. For example, what are the dimensions of their data — such as product, customer, time, and geography? People need to be able to ask questions about their data (e.g., which customers are likely to churn? Which salespeople are not reaching their quotas?). They need to be able to create measures from their data, such as on-time delivery, accidents in the workplace and customer or employee satisfaction. Organizations need to blend modeled and nonmodeled data to create new data pipelines that can be explored to find anomalies and other insights. ABI platforms make all of this possible.
The application delivery controller is a key component within enterprise and cloud data centers to improve availability, security and performance of applications. Application delivery controllers (ADCs) provide functions that optimize delivery of enterprise applications across the network. ADCs provide functionality for both user-to-application and application-to-application traffic, and effectively bridge the gap between the application and underlying protocols and traditional packet-based networks. This market evolved from the load-balancing systems that were developed in the latter half of the 1990s to ensure the availability and scalability of websites. Enterprises use ADCs today to improve the availability, scalability, end-user performance, data center resource utilization, security of their applications.
Reviews for 'Application Development, Integration and Management - Others'
Application platforms provide runtime environments for application logic. They manage the life cycle of an application or application component, and ensure the availability, reliability, scalability, security and monitoring of application logic. They typically support distributed application deployments across multiple nodes. Some also support cloud-style operations (elasticity, multitenancy and self-service).
Gartner defines the market for cloud database management systems (DBMSs) as the market for software products that store and manipulate data and that are primarily delivered as software as a service (SaaS) in the cloud. Cloud DBMSs may optionally be capable of running on-premises, or in hybrid, multicloud or intercloud configurations. They can be used for transactional work and/or analytical work. They may have features that enable them to participate in a wider data ecosystem. Must-have capabilities for this market include: Availability as SaaS on provider-managed public or private cloud systems; Management of data within cloud storage — that is, cloud DBMSs are not hosted in infrastructure as a service (IaaS), such as in a virtual machine or a container managed by the customer.
Continuous configuration automation (CCA) tools enable the description of configuration states, customization of settings, software binaries deployment, and configuration state reporting. These tools are a programmable framework on which configuration and provisioning tasks can be codified, versioned and managed like any other piece of application code — frequently known as 'infrastructure as code.' Many of the tools in the market provide a repository to store and manage configuration content but can be integrated with or use (code) revision control systems in use by application development teams. System administrators and application developers use CCA tools to programmatically manage the configurations of applications, servers, middleware, databases and other IT infrastructure for both on-premises and cloud data centre environments. Most CCA tools have both an open-source and commercial offering.
The data integration tools market comprises stand-alone software products that allow organizations to combine data from multiple sources, including performing tasks related to data access, transformation, enrichment and delivery. Data integration tools enable use cases such as data engineering, operational data integration, delivering modern data architectures, and enabling less-technical data integration. Data integration tools are procured by data and analytics (D&A) leaders and their teams for use by data engineers or less-technical users, such as business analysts or data scientists. These products are consumed as SaaS or deployed on-premises, in public or private cloud, or in hybrid configurations.
Gartner defines DevOps platforms as those that provide fully integrated capabilities to enable continuous delivery of software using Agile and DevOps practices. The capabilities span the development and delivery life cycle built around the continuous integration/continuous delivery (CI/CD) pipeline and include aspects such as versioning, testing, security, documentation and compliance. DevOps platforms support team collaboration, consistency, tool simplification and measurement of software delivery metrics. DevOps platforms simplify the creation, maintenance and management of the components required for the delivery of modern software applications. Platforms create common workflows and data models, simplify user access, and provide a consistent user experience (UX) to reduce cognitive load. They lead to improved visibility, auditability and traceability into the software development value stream. This end-to-end view encourages a systems-thinking mindset and accelerates feedback loops.
A digital experience platform (DXP) is an integrated set of technologies designed for the composition, management, delivery and optimization of personalized digital experiences across multiple channels in the customer journey. A DXP binds capabilities from multiple applications to allow the creation, orchestration and presentation of seamless experiences. It also forms part of a digital business ecosystem via API-based integrations with adjacent technologies. DXPs are applicable to business-to-consumer (B2C), business-to-business (B2B) and business-to-employee (B2E) use cases.
Infrastructure monitoring tools capture the health and resource utilization of IT infrastructure components, no matter where they reside (e.g., in a data center, at the edge, infrastructure as a service [IaaS] or platform as a service [PaaS] in the cloud). This enables I&O leaders to monitor and collate the availability and resource utilization data of physical and virtual entities — including servers, containers, network devices, database instances, hypervisors and storage. These tools collect data in real time and perform historical data analysis or trending of the elements they monitor.
Gartner defines Insight Engines as follows: Insight engines apply relevancy methods to discover, analyze, describe and organize content and data. They enable the interactive or proactive delivery or synthesis of information to people, and data to machines, in the context of their respective business moments. Insight engines should be viewed as platforms on which applications are provided, developed or augmented by applying the capabilities listed above to specific employee and customer experience use cases. Such applications are provided out of the box by vendors (e.g., intranet or site search), developed through technical partnerships (e.g., search within third-party applications), developed with customers in-house (e.g., expert finder), or developed through integration with third-party applications (e.g., extracting data from documents to support RPA).
Mobile app analytics tools collect and report on in-app data pertaining to the operation of the mobile app and the behavior of users within the app. These areas of app analytics are defined as follows: Operational analytics: Provides visibility into the availability and performance of mobile apps in relation to device, network, server and other technology factors. Operational analytics are essential to capture and fix unexpected app behavior (such as crashes, bugs, errors and latency) that can lead to user frustration and abandonment of the app. Such analytics should be applied at both the app testing phase and after release of the app into production. Behavioral analytics: Shows how app users interact with the app to gain actionable insights, drive app improvements and improve business outcomes. Behavioral data can be analyzed based on correlating clicks, swipes, views and other usage stats based on user profiles, segmentation/cohorts, retention, funnel/event tracking and A/B testing.
Gartner defines a mobile application management (MAM) tool as an on-premises or SaaS tool specifically designed for the license management, distribution, securing and life cycle management of apps for mobile device platforms. Thus, MAM tools provide integration with public app store payment and licensing mechanisms (such as Apple's Volume Purchase Program [VPP]), an enterprise app store, and the ability to set policies related to security, usage and ongoing management for apps or groups of apps. At minimum, a MAM product supports native and HTML 5 apps. Many also support a variety of popular hybrid app architectures, which may be highly desirable based on a particular client's needs.
An MXDP is an opinionated, integrated set of front-end development tools and “backend for frontend” (BFF) capabilities. It enables a distributed, scalable development approach (in terms of both teams and architecture) to build fit-for-purpose apps across digital touchpoints and interaction modalities. At minimum, an MXDP must support cross-platform development and building of both custom iOS and Android app binaries, responsive web apps, and at least one of the following: PWAs, chatbots, voice apps, wearables and Internet of Things (IoT) apps, and augmented-reality (AR) and mixed-reality (MR) apps.
Network detection and response (NDR) products detect abnormal system behaviors by applying behavioral analytics to network traffic data. They continuously analyze raw network packets or traffic metadata within internal networks (east-west) and between internal and external networks (north-south). NDR products include automated responses, such as host containment or traffic blocking, directly or through integration with other cybersecurity tools. NDR can be delivered as a combination of hardware and software appliances for sensors, some with IaaS support. Management and orchestration consoles can be software or SaaS.
Reviews for 'Office Productivity Solutions - Others'
Gartner defines WCM as the process of creating, managing and delivering content to one or more digital channels. This is achieved through the use of specific content management features based on a core repository. WCM tools are used to manage content to be delivered to websites and other digital channels. These tools are used by both IT and marketing/business. They may be procured as commercial products or open-source tools and are typically cloud-based. The functionality of WCM solutions goes beyond the publication of webpages. It also includes: - Content-creation functions, such as assembling content components, pages, websites, microsites and landing pages. - A content repository that organizes different content types and their metadata. - Library services, such as check-in and check-out, versioning and rollback. - Security and roles, and permissions management. - Management features such as layout and templates, menus and navigation, and workflows. - Content and application deployment functions. - Personalization capabilities. - The ability to integrate, via APIs, with adjacent technologies such as digital commerce platforms, CRM, and marketing automation platforms. - Hybrid and headless capabilities for API-driven multiexperience content delivery beyond websites and to other channels — such as mobile apps, progressive web apps (PWAs), single-page applications (SPAs), digital and voice assistants and smart devices.