This site uses cookies to improve your experience. To help us insure we adhere to various privacy regulations, please select your country/region of residence. If you do not select a country, we will assume you are from the United States. Select your Cookie Settings or view our Privacy Policy and Terms of Use.
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Used for the proper function of the website
Used for monitoring website traffic and interactions
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Strictly Necessary: Used for the proper function of the website
Performance/Analytics: Used for monitoring website traffic and interactions
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.
Technology leaders in the financial services sector constantly struggle with the daily challenges of balancing cost, performance, and security the constant demand for high availability means that even a minor system outage could lead to significant financial and reputational losses. Scalability. Architecture complexity.
To address this consideration and enhance your use of batch inference, we’ve developed a scalable solution using AWS Lambda and Amazon DynamoDB. Solution overview The solution presented in this post uses batch inference in Amazon Bedrock to process many requests efficiently using the following solution architecture.
Scalable data infrastructure As AI models become more complex, their computational requirements increase. Enterprises need infrastructure that can scale and provide the high performance required for intensive AI tasks, such as training and fine-tuning large language models. Planned innovations: Disaggregated storage architecture.
Apache Cassandra is an open-source distributed database that boasts an architecture that delivers high scalability, near 100% availability, and powerful read-and-write performance required for many data-heavy use cases. The topics covered include: Using Cassandra as if it were a Relational Database.
AI practitioners and industry leaders discussed these trends, shared best practices, and provided real-world use cases during EXLs recent virtual event, AI in Action: Driving the Shift to Scalable AI. Instead of performing line-by-line migrations, it analyzes and understands the business context of code, increasing efficiency.
Structured frameworks such as the Stakeholder Value Model provide a method for evaluating how IT projects impact different stakeholders, while tools like the Business Model Canvas help map out how technology investments enhance value propositions, streamline operations, and improve financial performance.
Alibaba has constructed a sophisticated microservices architecture to address the challenges of serving its vast user base and handling complex business operations.
This surge is driven by the rapid expansion of cloud computing and artificial intelligence, both of which are reshaping industries and enabling unprecedented scalability and innovation. The result was a compromised availability architecture. Global IT spending is expected to soar in 2025, gaining 9% according to recent estimates.
We will hear about specific use cases where organizations leveraged serverless refactoring, containerization or a combination of both solutions, that resulted in improved performance, availability, and scalability. How to make the right architectural choices given particular application patterns and risks.
But did you know you can take your performance even further? Vercel Fluid Compute is a game-changer, optimizing workloads for higher efficiency, lower costs, and enhanced scalability perfect for high-performance Sitecore deployments. What is Vercel Fluid Compute?
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.
Image: The Importance of Hybrid and Multi-Cloud Strategy Key benefits of a hybrid and multi-cloud approach include: Flexible Workload Deployment: The ability to place workloads in environments that best meet performance needs and regulatory requirements allows organizations to optimize operations while maintaining compliance.
To answer this, we need to look at the major shifts reshaping the workplace and the network architectures that support it. The Foundation of the Caf-Like Branch: Zero-Trust Architecture At the heart of the caf-like branch is a technological evolution thats been years in the makingzero-trust security architecture.
To achieve these goals, the AWS Well-Architected Framework provides comprehensive guidance for building and improving cloud architectures. The solution incorporates the following key features: Using a Retrieval Augmented Generation (RAG) architecture, the system generates a context-aware detailed assessment.
With this in mind, we embarked on a digital transformation that enables us to better meet customer needs now and in the future by adopting a lightweight, microservices architecture. We found that being architecturally led elevates the customer and their needs so we can design the right solution for the right problem.
This post will discuss agentic AI driven architecture and ways of implementing. These AI agents have demonstrated remarkable versatility, being able to perform tasks ranging from creative writing and code generation to data analysis and decision support.
For instance, a skilled developer might not just debug code but also optimize it to improve system performance. For instance, assigning a project that involves designing a scalable database architecture can reveal a candidates technical depth and strategic thinking. Contribute to hackathons, sprints, or brainstorming sessions.
In the world of modern web development, creating scalable, efficient, and maintainable applications is a top priority for developers. stands out due to its following features: Component-Based Architecture React breaks down the UI into reusable and isolated components. Among the many tools and frameworks available, React.js
high-performance computing GPU), data centers, and energy. VMware Private AI Foundation brings together industry-leading scalable NVIDIA and ecosystem applications for AI, and can be customized to meet local demands.
To address this, customers often begin by enhancing generative AI accuracy through vector-based retrieval systems and the Retrieval Augmented Generation (RAG) architectural pattern, which integrates dense embeddings to ground AI outputs in relevant context.
He says, My role evolved beyond IT when leadership recognized that platform scalability, AI-driven matchmaking, personalized recommendations, and data-driven insights were crucial for business success. A high-performing database architecture can significantly improve user retention and lead generation.
Because data management is a key variable for overcoming these challenges, carriers are turning to hybrid cloud solutions, which provide the flexibility and scalability needed to adapt to the evolving landscape 5G enables. Cost is also a constant concern, especially as carriers work to scale their infrastructure to support 5G networks.
” “Fungible’s technologies help enable high-performance, scalable, disaggregated, scaled-out data center infrastructure with reliability and security,” Girish Bablani, the CVP of Microsoft’s Azure Core division, wrote in a blog post.
We walk through the key components and services needed to build the end-to-end architecture, offering example code snippets and explanations for each critical element that help achieve the core functionality. Amazon DynamoDB is a fully managed NoSQL database service that provides fast and predictable performance with seamless scalability.
No single platform architecture can satisfy all the needs and use cases of large complex enterprises, so SAP partnered with a small handful of companies to enhance and enlarge the scope of their offering. It enables seamless and scalable access to SAP and non-SAP data with its business context, logic, and semantic relationships preserved.
As enterprises increasingly embrace serverless computing to build event-driven, scalable applications, the need for robust architectural patterns and operational best practices has become paramount. Enterprises and SMEs, all share a common objective for their cloud infra – reduced operational workloads and achieve greater scalability.
By taking EXLs expertise in helping enterprises design both legacy and modern architectures and building it into these agents, the tool tackles every migration task with greater accuracy and efficiency: Business Analyst: Code explanation, documentation, pseudo code.
With a wide range of services, including virtual machines, Kubernetes clusters, and serverless computing, Azure requires advanced management strategies to ensure optimal performance, enhanced security, and cost efficiency. Resource right-sizing is a significant part of cost optimization without affecting the systems efficiency or performance.
As successful proof-of-concepts transition into production, organizations are increasingly in need of enterprise scalable solutions. However, to unlock the long-term success and viability of these AI-powered solutions, it is crucial to align them with well-established architectural principles.
After a shaky start, Googles Gemini models have become solid performers. Many of the open models can deliver acceptable performance when running on laptops and phones; some are even targeted at embedded devices. Interest in Data Lake architectures rose 59%, while the much older Data Warehouse held steady, with a 0.3%
Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon through a single API, along with a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI.
Additionally, scalability remains a critical concern; as user adoption grows, the super-app design must handle high traffic volumes without compromising performance or escalating costs. Enterprises must enact robust security measures to protect user data and maintain regulatory compliance.
You can also bring your own customized models and deploy them to Amazon Bedrock for supported architectures. If it leads to better performance, your existing default prompt in the application is overridden with the new one. Refer to Perform AI prompt-chaining with Amazon Bedrock for more details.
Tech roles are rarely performed in isolation. Example: A candidate might perform well in a calm, structured interview environment but struggle to collaborate effectively in high-pressure, real-world scenarios like product launches or tight deadlines. Why interpersonal skills matter in tech hiring ?
The Cloudera AI Inference service is a highly scalable, secure, and high-performance deployment environment for serving production AI models and related applications. Conclusion In this first post, we introduced the Cloudera AI Inference service, explained why we built it, and took a high-level tour of its architecture.
The rise of service-oriented architecture (SOA) and microservices architecture has led to a major shift in software development, enabling the creation of complex, distributed systems composed of independent, loosely coupled services. These architectures offer numerous benefits, including scalability, flexibility, and resilience.
Dell Technologies takes this a step further with a scalable and modular architecture that lets enterprises customize a range of GenAI-powered digital assistants. They can also tailor AI-assisted coding solutions to their on-premises environments, offering companies the scalability and flexibility to supercharge the development process.
As a result, the emphasis is often around financial performance, drilling down to detailed metrics such as gross margins, sales rep productivity, LTV, CAC, payback periods and more. Getting the tech architecture to scale is critical. The focus of diligence tends to be on aspects of a product that can be measured.
By implementing this architectural pattern, organizations that use Google Workspace can empower their workforce to access groundbreaking AI solutions powered by Amazon Web Services (AWS) and make informed decisions without leaving their collaboration tool. In the following sections, we explain how to deploy this architecture.
Without a scalable approach to controlling costs, organizations risk unbudgeted usage and cost overruns. This scalable, programmatic approach eliminates inefficient manual processes, reduces the risk of excess spending, and ensures that critical applications receive priority. However, there are considerations to keep in mind.
Utilizing standard 2u servers outfitted with a robust set of specifications ensures the reliability and performance needed for critical operations. This architecture integrates a strategic assembly of server types across 10 racks to ensure peak performance and scalability.
. “Since its inception, NVMe has been revolutionizing the data storage industry with orders of magnitude higher levels of performance at increasing cost-effectiveness. But the problem is that traditional approaches to data storage are not a good match for NVMe’s performance capabilities and cost-effectiveness,” Kirzner said.
You either need: Experienced developers to maintain architectural integrity, maintainability and licensing considerations, or A cloud platform built to adapt to the changing landscape and build, migrate and manage cloud applications. Until you get those, here are some best practices for getting started.
We organize all of the trending information in your field so you don't have to. Join 49,000+ users and stay up to date on the latest articles your peers are reading.
You know about us, now we want to get to know you!
Let's personalize your content
Let's get even more personalized
We recognize your account from another site in our network, please click 'Send Email' below to continue with verifying your account and setting a password.
Let's personalize your content