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
Enterprises know everything is not moving to the cloud that was the lesson of 2024, and it triggered some extreme reactions that fueled the cloud repatriation stories we all heard. Its that some things are, and should be, moving to the cloud. Whatever is between the two means a redo of applications, perhaps a major redesign.
Kyndryl and Google Cloud are expanding their partnership to help customers use generative AI to move data off the mainframe and into the cloud. Googles Gemini LLMs are integrated into the Google Cloud platform and offer AI-based help across services and workflows, Google stated.
As organizations globally discover new opportunities created by AI, many are investing significantly in GenAI, including as part of their cloud modernization efforts. Many legacy applications were not designed for flexibility and scalability. In this context, GenAI can be used to speed up release times.
With the incremental differences in the major enterprise cloud environments today, that may be enough. He said that the new services are, not unexpectedly, trying to get enterprises to align with AWS services, which should make it more difficult to later move to a competing cloud platform. “Is Which means cost, cost, cost.
Speaker: Ahmad Jubran, Cloud Product Innovation Consultant
In order to maintain a competitive advantage, CTOs and product managers are shifting their products to the cloud. Many do this by simply replicating their current architectures in the cloud. Join Ahmad Jubran, Cloud Product Innovation Consultant, and learn how to adapt your solutions for cloud models the right way.
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.
In todays fast-paced digital landscape, the cloud has emerged as a cornerstone of modern business infrastructure, offering unparalleled scalability, agility, and cost-efficiency. As organizations increasingly migrate to the cloud, however, CIOs face the daunting challenge of navigating a complex and rapidly evolving cloud ecosystem.
As organizations globally discover new opportunities created by AI, many are investing significantly in GenAI, including as part of their cloud modernization efforts. Many legacy applications were not designed for flexibility and scalability. In this context, GenAI can be used to speed up release times.
The company also bolstered its SolarWinds Observability product with new integrations and support for cloud environments, including Google Cloud Platform (GCP), Amazon Web Services (AWS), and Microsoft Azure. These updates are important for monitoring todays IT environments, Sai says, as networks and applications become more complex.
Digital transformation is not just about adopting new tools but also about reshaping business processes, culture and customer experiences to meet the evolving demands of the digital age. One of the most significant enablers of digital transformation is cloud computing. Public cloud. Private cloud. Hybrid cloud.
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. It’s a tall order, because as technologies, business needs, and applications change, so must the environments where they are deployed.
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.
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. Cisco’s Nexus 9000 data center switches are a core component of the vendor’s enterprise AI offerings.
Fortinet has reached an agreement to buy cloud security company Lacework for an undisclosed amount. Founded in 2015, Lacework is known for its cloud-based machine learning, AI and automation technology that lets customers manage and secure cloud workflows.
NextHop AI, founded by former Arista Networks Chief Operating Officer Anshul Sadana, announced this week that it has secured $110 million in funding to develop highly customized networking solutions specifically for the worlds largest cloud providers. Today, whats happening is the cloud companies have their own operating system, Sadana said.
There was also a lot of work focused on improving Ethernet to better meet the growing need of AI/ML workloads. At the other end of the speed spectrum, the Ethernet Alliance also produced the first Single Pair Ethernet plugfest to advance seamless interoperability for products and services designed for 10BASE-T1L applications.
However, many face challenges finding the right IT environment and AI applications for their business due to a lack of established frameworks. Currently, enterprises primarily use AI for generative video, text, and image applications, as well as enhancing virtual assistance and customer support.
Secure Access Service Edge (SASE) is a network architecture that combines software-defined wide area networking (SD-WAN ) and security functionality into a unified cloud service that promises simplified WAN deployments, improved efficiency and security, and application-specific bandwidth policies. billion by 2025. What is SASE?
Loads of news came out of a hot Google Cloud Next 2025 in Las Vegas. Sovereign AI solutions on-prem, developer innovations that meet timely needs, very applicable multimodality for content and CX, and new elements for building the enterprise agentic AI stack. The most notable announcements? What was lacking?
Many are reframing how to manage infrastructure, especially as demand for AI and cloud-native innovation escalates,” Carter said. Organizations can maintain high-risk parts of their legacy VMware infrastructure while exploring how an alternative hypervisor can run business-critical applications and build new capabilities,” said Carter.
At the same time, they need to expand their cloud and security skill sets to accommodate more complex tools and technologies. From AI and network automation to cloud computing and security, the critical networking skills needed to excel in 2025 are shifting.
Virtually every company relied on cloud, connectivity, and security solutions, but no technology organization provided all three. Diamond founded 11:11 Systems to meet that need – and 11:11 hasn’t stopped growing since. These ensure that organizations match the right workloads and applications with the right cloud.
Modern data architectures must be designed for security, and they must support data policies and access controls directly on the raw data, not in a web of downstream data stores and applications. Cloud storage. Cloud computing. Application programming interfaces. Establish a common vocabulary. Seamless data integration.
We have seen the emergence of hyperscalers building modular nuclear reactors beside their data centers to meet the energy demands of AI, which underscores the scale of this challenge, Jokel said. Building power-efficient systems is imperative to maximize resources and ensure we can meet ongoing technology demands, Jokel said.
Two things play an essential role in a firms 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. Thats why the issue is so important today.
Meeting these requirements necessitates a shift in how CIOs, CTOs, and IT leaders manage their IT ecosystems, making comprehensive IT management platforms like BMC Helix essential. By aligning IT processes with regulatory expectations, BMC Helix empowers financial IT leaders to meet the stringent demands of operational resilience.
Data protection for hybrid clouds thus involves security products and cloud management products, as well as implementation strategies that traverse both specialties. Download our editors’ PDF hybrid cloud data protection buyer’s guide today!] And 80% of enterprises have adopted a hybrid computing model.
Regardless of the driver of transformation, your companys culture, leadership, and operating practices must continuously improve to meet the demands of a globally competitive, faster-paced, and technology-enabled world with increasing security and other operational risks.
A year ago, VMware’s big annual VMware Explore conference was all about generative AI – specifically, about companies running AI applications within a hybrid cloud infrastructure. This year, attendees heard more about VMware’s partnership with Nvidia to deliver generative AI models and tools – but in the context of a private cloud.
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.
tagging, component/application mapping, key metric collection) and tools incorporated to ensure data can be reported on sufficiently and efficiently without creating an industry in itself! Solution architecture: Crafting an enterprise architecture that meets both technical and business requirements.
For example, a company could have a best-in-class mainframe system running legacy applications that are homegrown and outdated, he adds. These types of applications can be migrated to modern cloud solutions that require much less IT talent overall and are cheaper and easier to maintain and keep current.”
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. In a time where trust and reliability are paramount, meeting these expectations through technology isnt just a differentiator its now a business imperative, Pappas says.
Similarly, telemedicine solutions in healthcare not only meet patient expectations for convenience but also align with broader business goals such as reducing operational costs and increasing reach. CIOs must implement governance frameworks to consistently evaluate IT investments, ensuring they meet both performance and strategic objectives.
Whisper is also embedded in Microsoft’s and Oracle’s cloud computing platforms and integrated with certain versions of ChatGPT. In one study of public meetings cited by AP, a researcher from the University of Michigan found hallucinations in eight of every 10 audio transcriptions.
The evolution of cloud-first strategies, real-time integration and AI-driven automation has set a new benchmark for data systems and heightened concerns over data privacy, regulatory compliance and ethical AI governance demand advanced solutions that are both robust and adaptive.
Re-platforming to reduce friction Marsh McLennan had been running several strategic data centers globally, with some workloads on the cloud that had sprung up organically. But the CIO had several key objectives to meet before launching the transformation.
Delivering high-quality applications predictability and securely is far simpler when you cut back on variety for variety’s sake. Application platforms can do just that, inject standardization and repeatability into the app development and delivery process. And things can heat up quickly. Many platforms?
These tools enable employees to develop applications and automate processes without extensive programming knowledge. Additionally, while these tools are excellent for simple applications, they might not be suitable for more complex systems that require specialized IT expertise.
After marked increase in cloud adoption through the pandemic, enterprises are facing new challenges, namely around the security, maintenance, and management of cloud infrastructure. According to the Foundry report, 78% of organizations say that, in response to cloud investments made by the organization, they have added new roles.
To meet the rapidly growing demand for its cloud services, Oracle has announced plans to open a third public cloud region in Saudi Arabia. Located in Riyadh, the new cloud region will be part of a planned $1.5 billion USD investment from Oracle to expand cloud infrastructure capabilities in the Kingdom.
The reality of what can be accomplished with current GenAI models, and the state of CIO’s data will not meet today’s lofty expectations.” GenAI will easily eclipse the effects that cloud and outsourcing vendors had on previous years regarding data center systems,” according to Lovelock. “It
Customer relationship management (CRM) software provider Salesforce on Thursday added new capabilities to its Sales Cloud and Service Cloud with updates to its Einstein AI and Data Cloud offerings. The company also added another capability that it calls Sales Signals to the Sales Cloud to help build a sales pipeline.
Hypershield uses AI to dynamically refine security policies based on application identity and behavior. While AI applications have brought the bandwidth and latency concerns back to the top of the networking requirements, additional capabilities are also top-of-mind. The research showed that 74.4%
We organize all of the trending information in your field so you don't have to. Join 83,000+ 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