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Some folks swear a microservices architecture is always a good choice and that a monolith architecture is always a bad choice. Come to think of it – what architecture is a good choice for you and your product? Not all software architectures are equal. The post AgileArchitectures first appeared on Agile Alliance.
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. Optimize data flows for agility.
Developing a robust technical architecture for digital twins necessitates a comprehensive understanding of several foundational components and integration of advanced technologies. This architecture allows for better decision-making, predictive maintenance and enhanced operational efficiency. Digital model.
A company that adopts agentic AI will gain competitive advantages in innovation, efficiency and responsiveness and may become more agile in operations. There are many reasons to build your own. Investments in AI agent projects are expected to yield orders of magnitude in ROI and business value if companies select high-impact use cases.
Speaker: Jeremiah Morrow, Nicolò Bidotti, and Achille Barbieri
In this webinar, learn how Enel Group worked with Agile Lab to implement Dremio as a data mesh solution for providing broad access to a unified view of their data, and how they use that architecture to enable a multitude of use cases. Leveraging Dremio for data governance and multi-cloud with Arrow Flight.
Stephen and his team embraced zero trust not as a buzzword, but as a practical architecture to simplify and scale security across this diverse environment. When AI is added to the mix, it becomes possible to detect anomalies and enforce policies in real time, making enterprises far more agile against threats.
CIOs often have a love-hate relationship with enterprise architecture. In the State of Enterprise Architecture 2023 , only 26% of respondents fully agreed that their enterprise architecture practice delivered strategic benefits, including improved agility, innovation opportunities, improved customer experiences, and faster time to market.
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).
Their journey offers valuable lessons for IT leaders seeking scalable and efficient architecture solutions. This story may sound familiar to many IT leaders: the business grows, but legacy IT architecture cant keep up limiting innovation and speed. Domain-Driven Design gurus could see good old bounded contexts here.
Speaker: Scott Middleton CEO & Founder, Terem Technologies & Anthony Murphy, Product & Agility Lead, UST Global
Agilearchitecture is a lever for unleashing autonomy and enabling agility in product teams. Watch this session with Anthony and Scott to go in depth on everything you need to know about agilearchitecture, and how to implement it.
In this model, organizations are investing in creating architectures for intelligent choices and using technology to augment people, not automate tasks, transforming the entire value chain, he says. CIOs should consider how agentic AI and other emerging AI capabilities enable the creation of intelligent organizations.
Decisions made in isolation lead to inefficiencies, slower responses to market changes, and a lack of agility that stifles innovation. Architects help organizations remain agile, innovative, and aligned by bridging gaps between strategy and technology. The future of leadership is agile, adaptable and architecturally driven.
Adopting agile methodologies for flexibility and adaptation The Greek philosopher Heraclitus famously stated, “Change is the only constant.” In today’s business environment, agile methodologies have become indispensable for maintaining alignment between IT and business strategies.
The latter option had emerged as a compelling solution, offering the promise of enhanced agility, reduced operational costs, and seamless scalability. Financial services unique challenges However, it is important to understand that serverless architecture is not a silver bullet. Architecture complexity. Legacy infrastructure.
To address this, a next-gen cloud data lake architecture has emerged that brings together the best attributes of the data warehouse and the data lake. This new open data architecture is built to maximize data access with minimal data movement and no data copies.
I believe that the fundamental design principles behind these systems, being siloed, batch-focused, schema-rigid and often proprietary, are inherently misaligned with the demands of our modern, agile, data-centric and AI-enabled insurance industry. This is where Delta Lakehouse architecture truly shines.
At a time when technology innovation cycles are getting shorter, we will struggle to keep pace if we have to navigate around legacy systems that act as barriers to speed and agility. Over time the speed and agility barriers associated with the ERP spread to other systems as they, in turn, formed an expanding wave of technical debt.
What companies need to do in order to cope with future challenges is adapt quickly: slim down and become more agile, be more innovative, become more cost-effective, yet be secure in IT terms. Generally speaking, a healthy application and data architecture is at the heart of successful modernisation.
Enterprise architecture definition Enterprise architecture (EA) is the practice of analyzing, designing, planning, and implementing enterprise analysis to successfully execute on business strategies. Another main priority with EA is agility and ensuring that your EA strategy has a strong focus on agility and agile adoption.
Particularly well-suited for microservice-oriented architectures and agile workflows, containers help organizations improve developer efficiency, feature velocity, and optimization of resources. Containers power many of the applications we use every day.
In todays digital-first economy, enterprise architecture must also evolve from a control function to an enablement platform. This transformation requires a fundamental shift in how we approach technology delivery moving from project-based thinking to product-oriented architecture. The stakes have never been higher.
Technology investments, such as in generative AI, are a priority in addressing the need to meet rising expectations while also driving operational agility and resilience. He advises beginning the new year by revisiting the organizations entire architecture and standards. Are they still fit for purpose?
However, as companies expand their operations and adopt multi-cloud architectures, they are faced with an invisible but powerful challenge: Data gravity. Instead of fighting against data gravity, organizations should design architectures that leverage their strengths while mitigating their risks.
According to research from NTT DATA , 90% of organisations acknowledge that outdated infrastructure severely curtails their capacity to integrate cutting-edge technologies, including GenAI, negatively impacts their business agility, and limits their ability to innovate. [1]
Speaker: Leo Zhadanovsky, Principal Solutions Architect, Amazon Web Services
Amazon's journey to its current modern architecture and processes provides insights for all software development leaders. To get there, Amazon focused on decomposing for agility, making critical cultural and operational changes, and creating tools for software delivery. The "two pizza" team culture. How Amazon thinks about metrics.
The evolution of agile development The agile manifesto was released in 2001 and, since then, the development philosophy has steadily gained over the previous waterfall style of software development. Agents can be more loosely coupled than services, making these architectures more flexible, resilient and smart.
More organizations than ever have adopted some sort of enterprise architecture framework, which provides important rules and structure that connect technology and the business. The results of this company’s enterprise architecture journey are detailed in IDC PeerScape: Practices for Enterprise Architecture Frameworks (September 2024).
As enterprises scale their digital transformation journeys, they face the dual challenge of managing vast, complex datasets while maintaining agility and security. These capabilities rely on distributed architectures designed to handle diverse data streams efficiently.
Suboptimal integration strategies are partly to blame, and on top of this, companies often don’t have security architecture that can handle both people and AI agents working on IT systems. Most importantly, position technical debt management not as a cost center, but as an investment in business agility and competitive advantage.
The result was a compromised availability architecture. The role of enterprise architecture and transformational leadership in sustainability Enterprise architecture is a framework to drive the transformation necessary for organizations to remain agile and resilient amid rapid technological and environmental changes.
With digital operating models altering business processes and the IT landscape, enterprise architecture (EA) — a rigid stalwart of IT — has shown signs of evolving as well. An enterprise architecture tool is often sold as a prerequisite by consulting firms that often earn software commissions. says LeanXI’s Christ.
In todays fast-paced digital landscape, the cloud has emerged as a cornerstone of modern business infrastructure, offering unparalleled scalability, agility, and cost-efficiency. Technology modernization strategy : Evaluate the overall IT landscape through the lens of enterprise architecture and assess IT applications through a 7R framework.
Cloud architects are responsible for managing the cloud computing architecture in an organization, especially as cloud technologies grow increasingly complex. At organizations that have already completed their cloud adoption, cloud architects help maintain, oversee, troubleshoot, and optimize cloud architecture over time.
To keep up, IT must be able to rapidly design and deliver application architectures that not only meet the business needs of the company but also meet data recovery and compliance mandates. Few CIOs would have imagined how radically their infrastructures would change over the last 10 years — and the speed of change is only accelerating.
These include adopting Agile methods, modern engineering practices, DevOps, API design, microservices, and cloud architectures. The post Learning Over Delivery – How Companies Become Learning Organizations with Dojos first appeared on Agile Alliance.
What companies need to do in order to cope with future challenges is adapt quickly: slim down and become more agile, be more innovative, become more cost-effective, yet be secure in IT terms. Generally speaking, a healthy application and data architecture is at the heart of successful modernisation.
Contextual AI Integration for Agile Product Teams Imagine this scenario: An empowered product team implements an AI assistant to help with feature prioritization and customer insights. Despite everyone using the same AI tool, it doesnt understand how the product team actually works.
Since these technology solutions can’t scale without a modular, well-architected foundation of platform services, she’s set her sights on moving from a set of customized and packaged software to a more modern architecture. We need our architecture to help deliver on that intent.” My team is very proactive and customer-focused.
As a long-time partner with NVIDIA, NetApp has delivered certified NVIDIA DGX SuperPOD and NetApp ® AIPod ™ architectures and has seen rapid adoption of AI workflows on first-party cloud offerings at the hyperscalers. Planned innovations: Disaggregated storage architecture.
Data-driven decision making and AI integration will remain critical must-haves for IT leaders For IT leaders, leveragingtrusted, high-quality datais essential to drive smarter decisions, enhance organizational agility and embed a data-driven culture. IQ ensures preparedness; EQ enables agility.
Without the right cloud architecture, enterprises can be crushed under a mass of operational disruption that impedes their digital transformation. What’s getting in the way of transformation journeys for enterprises? This isn’t a matter of demonstrating greater organizational resilience or patience.
The idea was coined by legendary programmer Ward Cunningham, one of the authors of the Agile Manifesto, and he laid it out succinctly at the OOPSLA conference in 1992 : Shipping first-time code is like going into debt. Thats part of the Agile philosophy of continuous improvement.
When evaluating options, prioritize platforms that facilitate data democratization through low-code or no-code architectures. A robust data distillery should integrate governance, modeling, architecture, and warehousing capabilities while providing comprehensive oversight aligning with industry standards and regulations.
Now that systems are being replaced, it’s also about creating a new architecture without those types of connections. Paring down agile Another change the digital organization has gone through recently is to start backing away from a pure agile approach. But it’s extremely difficult to suddenly launch a successfully IT system.
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