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The chipmaker has released a series of what it calls Enterprise Reference Architectures (Enterprise RA), which are blueprints to simplify the building of AI-oriented data centers. A reference architecture provides the full-stack hardware and software recommendations. However, there is another advantage, and that has to do with scale.
Data architecture definition Data architecture describes the structure of an organizations logical and physical data assets, and data management resources, according to The Open Group Architecture Framework (TOGAF). An organizations data architecture is the purview of data architects. Ensure security and access controls.
To fully benefit from AI, organizations must take bold steps to accelerate the time to value for these applications. Just as DevOps has become an effective model for organizing application teams, a similar approach can be applied here through machine learning operations, or “MLOps,” which automates machine learning workflows and deployments.
In a global economy where innovators increasingly win big, too many enterprises are stymied by legacy application systems. Modernising with GenAI Modernising the application stack is therefore critical and, increasingly, businesses see GenAI as the key to success. The solutionGenAIis also the beneficiary.
Embedding analytics in your application doesn’t have to be a one-step undertaking. In fact, rolling out features gradually is beneficial because it allows you to progressively improve your application. Application Design: Depending on your capabilities, you can choose either a VM or a container-based approach.
Microsoft is describing AI agents as the new applications for an AI-powered world. This data would be utilized for different types of application testing. The output of the system should be able to stress the end user application by producing different-sized test files.
New research from IBM finds that enterprises are further along in deploying AI applications on the big iron than might be expected: 78% of IT executives surveyed said their organizations are either piloting projects or operationalizing initiatives that incorporate AI technology.
Enterprise architecture (EA) has evolved beyond governance and documentation. Establish clear roles and responsibilities for an integrated team of business, application, data and technology architects. Ensure architecture insights drive business strategy. Accelerate transformation by enabling rapid decision-making. The result?
After all, a low-risk annoyance in a key application can become a sizable boulder when the app requires modernization to support a digital transformation initiative. Accenture reports that the top three sources of technical debt are enterprise applications, AI, and enterprise architecture.
In his best-selling book Patterns of Enterprise ApplicationArchitecture, Martin Fowler famously coined the first law of distributed computing—"Don’t distribute your objects"—implying that working with this style of architecture can be challenging.
For starters, generative AI capabilities will improve how enterprise IT teams deploy and manage their SD-WAN architecture. With AI-driven network management and optimization capabilities, enterprises will be able to prioritize traffic and application performance based on user needs and business requirements, according to IDC.
Zero Trust architecture was created to solve the limitations of legacy security architectures. It’s the opposite of a firewall and VPN architecture, where once on the corporate network everyone and everything is trusted. In today’s digital age, cybersecurity is no longer an option but a necessity.
VMware by Broadcom has unveiled a new networking architecture that it says will improve the performance and security of distributed artificial intelligence (AI) — using AI and machine learning (ML) to do so. The latest stage — the intelligent edge — is on the brink of rapid adoption.
Project Salus is a responsible AI toolkit, while Essedum is an AI framework for networking applications. Top AI applications : Network automation leads at 57%, followed by security at 50% and predictive maintenance at 41%. LF Networking also announced the CAMARA Spring25 Meta-Release advancing the open-source telecom-focused platform.
Every data-driven project calls for a review of your data architecture—and that includes embedded analytics. Before you add new dashboards and reports to your application, you need to evaluate your data architecture with analytics in mind. 9 questions to ask yourself when planning your ideal architecture.
Jenga builder: Enterprise architects piece together both reusable and replaceable components and solutions enabling responsive (adaptable, resilient) architectures that accelerate time-to-market without disrupting other components or the architecture overall (e.g. compromising quality, structure, integrity, goals).
AI factories are specified data centers emphasizing AI applications as opposed to traditional line of business applications like databases and ERP. The architecture aims to optimize deployment speed, performance, resiliency, cost, energy efficiency and scalability for current- and future-generation data centers.
The built-in elasticity in serverless computing architecture makes it particularly appealing for unpredictable workloads and amplifies developers productivity by letting developers focus on writing code and optimizing application design industry benchmarks , providing additional justification for this hypothesis. Vendor lock-in.
Modern Application Development Services Defined Clients want more autonomy to better control their own innovation and development capabilities to build modern and up-to-date custom applications.
Of course, the key as a senior leader is to understand what your organization needs, your application requirements, and to make choices that leverage the benefits of the right approach that fits the situation. How to make the right architectural choices given particular application patterns and risks.
Its no secret that more modern approaches to remote access have been usurping VPNs as organizations adapt to the realities of a more distributed workforce, increasingly cloud-based applications, and heightened security threats. Its really access to an individual resource or application instead of a whole network segment.
As 2025 kicked off, I wrote a column about the network vendor landscape specifically, which networking players will step up and put their efforts into finding new applications with solid business benefits that could enable a network transformation. Its not an application, but an applicationarchitecture or model.
The Supermicro JBOF replaces the traditional storage CPU and memory subsystem with the BlueField-3 DPU and runs the storage application on the DPU’s 16 Arm cores. BlueField-3 accelerates networking traffic through hardware support for RoCE (RDMA over converged Ethernet), GPU direct storage and GPU initiated storage.
Zscaler eliminates this risk and the attack surface by keeping applications and services invisible to the internet. This approach stops encrypted threats from reaching critical applications and systems, providing proactive protection that doesnt rely on shared network access.
Two things play an essential role in a firm’s ability to adapt successfully: its data and its applications. Which is why modernising applications is so important, especially for traditional businesses – they need to keep pace with the challenges facing trade and commerce nowadays. That’s why the issue is so important today.
To keep up, IT must be able to rapidly design and deliver applicationarchitectures that not only meet the business needs of the company but also meet data recovery and compliance mandates. It’s a tall order, because as technologies, business needs, and applications change, so must the environments where they are deployed.
The FortiDLP platform provides automated data movement tracking, cloud application monitoring and endpoint protection mechanisms that work both online and offline. FortiDLP expands Fortinet’s data protection efforts FortiDLP’s architecture includes several key technical components.
Applications and software: Manage applications software, understand the components of operating systems, and explain the purpose of methods of applicationarchitecture. Database fundamentals: Explain database concepts, structures, and purpose and understand methods used to interface with databases.
Speaker: Ahmad Jubran, Cloud Product Innovation Consultant
Many do this by simply replicating their current architectures in the cloud. Those previous architectures, which were optimized for transactional systems, aren't well-suited for the new age of AI. In this webinar, you will learn how to: Take advantage of serverless applicationarchitecture.
It prevents vendor lock-in, gives a lever for strong negotiation, enables business flexibility in strategy execution owing to complicated architecture or regional limitations in terms of security and legal compliance if and when they rise and promotes portability from an applicationarchitecture perspective.
Later, as an enterprise architect in consumer-packaged goods, I could no longer realistically contemplate a world where IT could execute mass application portfolio migrations from data centers to cloud and SaaS-based applications and survive the cost, risk and time-to-market implications.
They are using the considerable power of this fast-evolving technology to tackle the common challenges of cloud modernization, particularly in projects that involve the migration and modernization of legacy applications a key enabler of digital and business transformation. In this context, GenAI can be used to speed up release times.
VMware Tanzu for MySQL: “The classic web application backend that optimizes transactional data handling for cloud native environments.” VMware Tanzu RabbitMQ: “Secure, real-time message queuing, routing, and streaming for distributed systems, supporting microservices and event-driven architectures.” Not at all.”
Containers power many of the applications we use every day. Particularly well-suited for microservice-oriented architectures and agile workflows, containers help organizations improve developer efficiency, feature velocity, and optimization of resources.
Just as ancient trade routes determined how and where commerce flowed, applications and computing resources today gravitate towards massive datasets. However, as companies expand their operations and adopt multi-cloud architectures, they are faced with an invisible but powerful challenge: Data gravity.
Why IT/OT convergence is happening Companies want flexibility in how end users and business applications access and interact with OT systems. For example, manufacturers can pull real-time data from their assembly lines so that specialized analytics applications can identify opportunities for efficiency and predict disruptions to production.
The goal of the Kyndryl/Google Cloud service is to make it easier for organizations to utilize AI assistance to access and integrate mainframe-based data with cloud-based resources and combine that data with other information to build new applications, the companies stated.
Cisco is boosting network density support for its data center switch and router portfolio as it works to deliver the network infrastructure its customers need for cloud architecture, AI workloads and high-performance computing. This is accomplished with a common operating system, P4 programmable forwarding code, and an SDK.
Speaker: Daniel "spoons" Spoonhower, CTO and Co-Founder at Lightstep
Many engineering organizations have now adopted microservices or other loosely coupled architectures, often alongside DevOps practices. However, this increased velocity often comes at the cost of overall application performance or reliability.
In 2008, SAP developed the SAP HANA architecture in collaboration with the Hasso Plattner Institute and Stanford University with the goal of analyzing large amounts of data in real-time. The entire architecture of S/4HANA is tightly integrated and coordinated from a software perspective. In 2010, SAP introduced the HANA database.
Legacy platforms meaning IT applications and platforms that businesses implemented decades ago, and which still power production workloads are what you might call the third rail of IT estates. Compatibility issues : Migrating to a newer platform could break compatibility between legacy technologies and other applications or services.
In that report, we analyzed how the cloud-native ecosystem, driven by open-source software (OSS), has been powering architecture modernization across infrastructure and application development, enabling platform-driven innovation in the meantime across a spectrum of technology domains such as data […]
5 key findings: AI usage and threat trends The ThreatLabz research team analyzed activity from over 800 known AI/ML applications between February and December 2024. The surge was fueled by ChatGPT, Microsoft Copilot, Grammarly, and other generative AI tools, which accounted for the majority of AI-related traffic from known applications.
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