In Hardware and Network news this week…

Zayo Launches Agentic Networking to Power AI Operations

Zayo is advancing network infrastructure with agentic networking capabilities designed to support increasingly complex AI operations. The approach brings AI-driven automation into network management, helping organizations respond more intelligently to changing workloads and connectivity requirements. As AI applications place greater demands on network performance, reliability, and scalability, agentic networking could help enterprises move toward more autonomous infrastructure operations while reducing manual intervention.

In Business Technology news this week…

TeamViewer Expands Tia AI Platform From IT Guidance to Governed Action

TeamViewer is expanding its Tia AI platform beyond providing IT guidance to enabling governed actions across technology environments. The development reflects a broader shift toward AI agents that can actively execute operational tasks rather than simply recommend next steps. By introducing governance into these actions, organizations can gain greater control over automation while maintaining oversight of how AI interacts with IT systems. This could help businesses improve service efficiency while addressing concerns around security, accountability, and operational control.

In Cloud Computing & Mobility news this week…

Cloudflare and OpenAI Partner to Redefine Vulnerability Management With AI-Powered Edge Defense

Cloudflare and OpenAI are collaborating to strengthen vulnerability management through AI-powered defenses at the network edge. The partnership highlights how AI can be incorporated into security infrastructure to identify and respond to emerging threats more efficiently. By bringing intelligent security capabilities closer to where traffic and applications operate, enterprises could improve their ability to detect vulnerabilities and respond to attacks while maintaining protection across increasingly distributed digital environments.

In Quantum Computing news this week…

IBM, Lockheed Martin and ETH Zurich Partner to Launch Switzerland’s First Quantum Innovation Hub

IBM, Lockheed Martin, and ETH Zurich are joining forces to establish Switzerland’s first quantum innovation hub. The initiative is expected to strengthen collaboration among industry and academia while accelerating research and practical applications of quantum computing. Such partnerships are becoming increasingly important as organizations explore quantum technologies for complex computational challenges. The new hub could also contribute to Switzerland’s position within the global quantum ecosystem by connecting research capabilities with industrial use cases.

In FinTech news this week…

Ant International, Mastercard and Visa Unveil Know Your Agent Interoperability Framework to Secure Agentic Commerce

Ant International, Mastercard, and Visa are working to establish a Know Your Agent interoperability framework aimed at making agentic commerce more secure. As AI agents increasingly participate in purchasing and financial transactions on behalf of users, financial institutions need reliable mechanisms for identifying and validating those agents. The framework addresses an emerging challenge in digital commerce by supporting greater trust and interoperability. For banks, payment providers, and merchants, such standards could become increasingly important as autonomous transactions move closer to mainstream adoption.

In HealthTech news this week…

Unchained Labs Launches AI Developability Workcell for Biologics R&D

Unchained Labs is introducing an AI-powered developability workcell designed to support biologics research and development. The solution brings automation and artificial intelligence into laboratory workflows, potentially helping researchers evaluate and optimize biologic candidates more efficiently. As pharmaceutical and biotechnology companies face pressure to accelerate discovery while managing increasingly complex research processes, AI-enabled laboratory automation could help reduce repetitive work, improve consistency, and shorten development timelines.

In Information Security news this week…

Hexnode Unveils Hexnode Synapse, Bringing Agentic Orchestration to IT and Security Operations

Hexnode is introducing Hexnode Synapse, an agentic orchestration capability aimed at IT and security operations. The platform reflects the growing use of AI agents to coordinate workflows across enterprise technology environments. By combining orchestration with IT and security operations, organizations can potentially automate routine processes, improve response times, and reduce operational complexity. The move also demonstrates how agentic AI is becoming increasingly embedded in enterprise management and security rather than remaining limited to standalone AI applications.

Article of the Week

Data Breach Incident Response: A Step-by-Step Guide for Detecting, Containing, and Recovering From Cyberattacks

Data breaches require organizations to respond quickly and systematically, from identifying suspicious activity and containing compromised systems to recovering operations and preventing repeat incidents. This guide explores the key stages of an effective data breach incident response strategy and highlights why preparation, monitoring, communication, and recovery planning are essential. As cyberattacks become more sophisticated and enterprise environments grow more distributed, having a structured response framework can help businesses limit damage, protect critical information, and restore operations more effectively.

The post ITDigest’s Weekly News Roundup Featuring Zayo, TeamViewer, Cloudflare, OpenAI, IBM, Mastercard, Visa, Hexnode and more appeared first on ITDigest.

The product releases address a key challenge in enterprise AI adoption: while AI agents excel at natural language processing, they frequently operate in a vacuum without direct access to validated operational rules. According to recent industry data, 71 percent of IT leaders confirm that AI initiatives yield the highest success rates when IT and business teams collaborate closely to bridge the gap between autonomous agents and enterprise business logic.

“As AI changes where and how people interact with enterprise software, the challenge is no longer simply generating answers—it is ensuring those answers reflect trusted data, business context, and governed logic,” said Stewart Bond, Vice President, Data Intelligence and Integration Software at IDC. “By making approved workflows and analytics available through the AI assistants and agents employees already use, Alteryx is addressing an important requirement for moving AI from experimentation into reliable, repeatable business operations at scale.”

Also Read: Teradata Integrates Enterprise AI into Microsoft OneLake

Optimizing Token Economics via Governed Execution

Beyond enforcing compliance, embedding pre-governed Alteryx workflows directly into AI execution significantly improves the unit economics of generative AI. By executing data analytics within the Alteryx engine rather than relying on an LLM to reason through unstructured datasets, enterprises achieve significant reductions in API token consumption.

In a recent deployment by consulting firm NextWave, an Alteryx workflow drove a 20-fold reduction in LLM token consumption during a complex Office of the CFO data reconciliation between front-office and back-office systems. Internal benchmarking validated these performance gains:

Raw, Ungrounded Data Tasks: Combining an LLM with a trusted Alteryx workflow yielded up to a 93% reduction in token consumption and up to an 85% increase in execution speed.

Clean, Grounded Data Tasks: Delivered up to an 83% reduction in token costs alongside a 65% increase in processing speed.

Analyst Insights: 65 percent of surveyed data analysts confirm that AI delivers the greatest enterprise value when business logic is managed directly at the business unit level.

“Generative AI is brilliant at brainstorming, but it often struggles with the precision required for enterprise execution. Organizations don’t need agents that guess at business rules and burn through tokens; they need AI that operates on the same trusted business logic and governance that underpin the rest of the business,” said Ben Canning, Chief Product Officer at Alteryx. “By connecting existing tools to a governed business logic layer, we are allowing enterprises to stop the ‘re-work’ tax of rebuilding business rules for every new agent, ensuring that every AI-driven action is as reliable as the calculations they already trust.”

Core Capabilities Introduced in Alteryx One

The suite of AI features extends trusted analytics and governance models directly into the primary communication tools and AI environments used by enterprise teams:

Ask Alteryx: Provides a natural-language interface for Alteryx One and introduces new users to workflow creation in Designer, as well as performing live data queries against Snowflake, BigQuery, and Databricks.

Agent Studio: Enables business and analytics teams to transform any existing, governed data into a conversational agent without changing any underlying data structure.

Alteryx Insights for OpenAI: Currently available in the ChatGPT Plugin Directory, allowing users to query analyst-approved calculations and data within ChatGPT. The plugin will expand its support base to include Claude, Gemini, Slack, and Microsoft Teams in the future.

Alteryx MCP Server: Integrates third-party AI agents with Alteryx assets using Model Context Protocol (MCP) so that all external requests have automatic access to all the authentication and auditing capabilities associated with the existing asset.

Alteryx Skills: A GitHub-based initiative that trains third-party agentic interfaces such as OpenAI Codex, Microsoft Copilot, Claude Code, and Gemini CLI to build Alteryx assets in a governed fashion.

The post Alteryx Introduces AI Engine to Connect AI Agents with Governed Analytics appeared first on ITDigest.

As enterprise data lakes evolve into mission-critical lakehouses powering AI models and real-time business intelligence, open table formats like Apache Iceberg have become essential infrastructure. However, a key vulnerability has persisted: native Iceberg snapshots are merely metadata pointers, not full backups. If a table is corrupted by ransomware, deleted by an errant script, or overwritten by a misfiring AI agent, those pointers vanish. Restoring underlying storage files leaves organizations with raw, disorganized Parquet files requiring days of manual metadata reconstruction before analytics engines can query the data.

Rubrik’s new capability closes this vulnerability by backing up both data files and table metadata, automatically re-registering tables in the catalog upon recovery. This allows data teams to restore complete, immediately queryable tables in engines like Amazon Athena, Apache Spark, or Trino.

Also Read: Airties Debuts “Aura” Agentic AI Engine to Transform Connected Intelligence for ISPs

Technical Capabilities: Metadata Rewiring and In-Account Sovereignty

Coverage extends across AWS Glue Data Catalog and Amazon Simple Storage Service (S3) Tables. Key technical highlights include:

Iceberg-Aware Metadata Recovery: Captures full table definitions, history, and schema state alongside raw data. Upon restore, Rubrik re-wires the catalog automatically so analytics engines can resume operations without manual file repair.

In-Account Data Sovereignty: it stands out as the first Iceberg-aware protection solution that enables enterprises to keep immutable backups locked inside their own AWS accounts, satisfying data compliance and sovereignty requirements, and complementing Rubrik’s air-gapped Cloud Vault.

Petabyte-Scale Forever-Incremental Backups: makes use of forever-incremental method of compacted snapshot backups which keeps backup window low for a very large scale deployment and lets the companies select their preferred Amazon S3 storage tier to control cost.

Risk Validation Based on branch: gives ability to run backups right before the risky activities like schema changes or large batch writes by having the ability to restore data on a separate Iceberg branch for validation before promotion production environment.

Transforming the Cloud Data Security, Lakehouse, and AI Infrastructure Industry

Rubrik’s release accelerates a fundamental evolution across the broader Cloud Data Security, Data Management, and AI Infrastructure sectors.

The Obsolescence of “Storage-Only” Cloud Backups
Historically, cloud backup providers treated object storage (like Amazon S3) as simple buckets of unstructured files. However, modern analytical workloads rely on abstraction layers catalogs, schema definitions, and metadata pointers to make raw data usable.

This announcement highlights the inadequacy of storage-only backups for lakehouses. The data security market is shifting toward metadata-aware cyber resilience. Security vendors can no longer claim cloud data protection simply by backing up raw bytes; they must protect the catalog and logical table structures that give that data operational meaning.

De-Risking Autonomous AI Agents on Data Lakes
As enterprises deploy autonomous AI agents with write access to internal data lakes for automated ETL, feature engineering, and reporting, the risk of “agentic data corruption” where an AI agent incorrectly modifies schema or overwrites table states at scale has grown significantly.

By introducing Iceberg-aware recovery and isolated branch testing, Rubrik establishes a baseline safety layer for AI-driven data pipelines. Data engineering teams gain a critical safety net, allowing them to grant AI agents broader operational permissions without risking permanent lakehouse corruption.

Operational Impact on Enterprise Businesses

For top enterprise executives responsible for data lakes, mission-critical analytics, and AI on AWS – like CIOs, CISOs, and CDOs – adopting lakehouse-aware protection has numerous operational benefits:

No more Downtime and Lost Revenue
If ransomware attacks or deletions cause company data lakehouses to stop functioning, dashboards for business intelligence, real-time supply chain simulations, and consumer apps will all become inoperable. Shortening the recovery period from many days of manual reconstruction work to just a few minutes of automated catalog re-registration ensures the smooth operation of business as well as the avoidance of possible losses in revenues.

Compliance made Easy by Securing Data Sovereignty
Organizations like financial services, healthcare providers, and public institutions are at a regulatory risk when their sensitive data is moved for cloud backup as they rely on third-party backup solutions that usually require leaving data in the enterprise clouds. Granting these institutions the ability to keep their immutable and air-gapped backups on the same AWS tenant that they use will ensure full mastery over where they keep their data and how to encrypt it, even while cyber insurance and other compliance requirements get satisfied.

The post Rubrik Launches Lakehouse Protection for Apache Iceberg Data on AWS to Close the Cloud Data Resilience Gap appeared first on ITDigest.

The platform launch addresses an emerging class of operational risk brought into focus by the recent OpenAI-Hugging Face incident. During an internal security evaluation, autonomous AI agents identified unexpected configuration paths that extended beyond their designated environments, ultimately accessing external production infrastructure. The event demonstrated how fast-moving AI agents can uncover operational gaps, chain vulnerabilities together, and execute cloud actions at speeds that surpass traditional, human-dependent security operations.

As Greg Brockman, President and Co-Founder of OpenAI, recently wrote in his blog post “The Defender’s Window”: “The OpenAI-Hugging Face incident was a watershed moment for cybersecurity because it gave a peek into how the capabilities of a typical threat actor will evolve in upcoming months. I’ve spoken with many organizations over the past few weeks, and one theme is clear: they know they need to fundamentally uplevel their cybersecurity practices with unprecedented speed.”

“The Hugging Face incident was a warning shot. It showed what capable agents can already do when they go off-script, and why security teams need to prepare for similar techniques being used intentionally by attackers,” said Evan Reiser, Founder & CEO of Abnormal AI. “Our platform already detects behavioral anomalies from human and non-human identities and I’m excited for us to extend these capabilities to protect enterprise cloud environments.”

Also Read: Harness Launches AppSec Alliance to Secure Application, API, and Agent Workflows

Machine-Speed Defense Architecture for Enterprise Cloud Infrastructure

Legacy cybersecurity tools that rely primarily on static threat signatures struggle to identify non-standard, agent-driven exploits that lack historical precedent. Abnormal AI Cloud Security counters these gaps by applying continuous behavioral analysis—establishing baseline operational profiles for every human identity, service account, API key, and autonomous AI agent across an organization’s digital footprint.

Key architectural capabilities of Abnormal AI Cloud Security include:

Real-Time AI Breach Detection: Continuously evaluates behavioral signals across the cloud estate, flagging suspicious activity the moment an identity or agent strays from established operational norms.

Autonomous Incident Containment: Delivers machine-speed response workflows when threat conditions are met. Security administrators can configure the platform to automatically isolate compromised workloads, revoke API tokens, and contain affected resources based on incident severity.

OpenAI Daybreak Investigation Engine: Utilizes OpenAI Daybreak models to assist security teams during incident triage. The system correlates raw telemetry logs with behavioral context to map out incident blast radiuses and suggest remediation paths.

Bridging the Operational Gap in Agentic Security

By extending behavioral analytics natively into cloud workloads, Abnormal AI gives enterprise security operations centers (SOCs) the toolset needed to govern both human and software-driven actors. The platform allows security teams to maintain high-velocity cloud workflows while deploying automated guardrails that prevent autonomous agents from breaching operational boundaries.

The post Abnormal AI Unveils AI Cloud Security Platform with OpenAI Daybreak Models appeared first on ITDigest.

Addressing this escalating crisis, connectivity cloud leader Cloudflare, Inc. announced a landmark integration with OpenAI to launch Vulnerability Discovery and Remediation. Available in early access through Cloudflare Managed Defense, the new service combines frontier AI models including OpenAI’s GPT-5.6 Cyber via the OpenAI Daybreak Defense Network with real-time traffic intelligence across Cloudflare’s global edge network.

The collaboration introduces a proactive defense layer that maps active production traffic directly to source code vulnerabilities, allowing enterprises to block live exploits at the edge in seconds while automated AI agents draft verified code patches.

Technical Performance: Linking Live Traffic Signals with Frontier AI Code Analysis

The core technological advance of the service is its ability to eliminate the disconnect between static source code scanning and dynamic network activity. By analyzing source code alongside real-time internet traffic patterns, the architecture enables defenders to prioritize and neutralize threats before exploit payloads reach core infrastructure.

Also Read: PwC and Palantir Expand Strategic Alliance to Accelerate Production-Grade Enterprise AI Deployment

Key capabilities of the integrated platform include:

Context-Aware Threat Triaging: Correlates live web traffic and attack patterns with source code structures, immediately highlighting vulnerabilities that are actively under fire.

Instant Edge Protection (Virtual Patching): Generates and deploys custom Web Application Firewall (WAF) mitigation rules tailored to specific attack vectors. This shields applications at the edge in seconds while developers work on permanent software fixes.

AI-Assisted Patch Generation: Leverages OpenAI’s GPT-5.6 Cyber model to investigate codebases and automatically draft context-aware code patches for developer review.

Human-in-the-Loop Governance: Enforces explicit human approval for both WAF rules and code modifications, ensuring security teams retain total control over production deployments.

“If your security team is manually fighting AI-driven attacks, you’re not just burning them out you’re losing,” stated Matthew Prince, co-founder and CEO of Cloudflare. “Pairing Cloudflare’s global network with OpenAI GPT-5.6 Cyber shifts defense from chasing patches one by one to stopping attacks before they land.”

Transforming the Enterprise Cybersecurity and Cloud Infrastructure Industry

Cloudflare and OpenAI’s partnership signals a defining structural pivot across the Cybersecurity, Application Security, and Cloud Edge Infrastructure market.

The Obsolescence of Standalone Vulnerability Scanners
For years, the application security market relied on static application security testing (SAST) and vulnerability scanners that produced overwhelming lists of theoretical flaws.

The launch of edge-based AI remediation marks the decline of passive scanning tools. The cybersecurity industry is transitioning toward unified threat intelligence platforms where network telemetry, edge computing, and AI code analysis operate in a continuous feedback loop. Security vendors will no longer be evaluated on how many bugs they surface, but on how fast their platforms apply virtual patches at the edge.

Establishing Frontier AI as a Core Defensive Engine
Historically, security teams worried that generative AI models would primarily benefit threat actors by accelerating zero-day discovery.

By deploying GPT-5.6 Cyber natively within the OpenAI Daybreak Defense Network, Cloudflare and OpenAI establish a benchmark for AI-driven cyber defense. Enterprise buyers will increasingly expect security infrastructure to feature specialized, defensive AI models capable of autonomous code reasoning and real-time mitigation drafting.

Broad Operational Impact on Enterprise Businesses

For corporate leadership, Chief Information Security Officers (CISOs), and Chief Technology Officers (CTOs) facing surging software vulnerability rates, deploying AI-powered edge defense offers direct strategic and commercial advantages:

Shielding Revenue and Preserving Developer Velocity
To fix a critical vulnerability, usually engineering teams are forced to abandon product feature development in favor of writing, testing, and deploying emergency hotfixes. Virtual patching at the edge can instantly block exploits and protects enterprise applications without having a negative impact on product development.

Reducing Breach Liabilities and Alert Fatigue
Closed vulnerable items in a company might result in significant monetary penalties, disruptions caused by ransomware, and also damage to a company’s reputation. Filtering threats using real-time network context will help SOC teams identify the real problems, cut out alert fatigue, and thereby reduce overall cyber risk exposure.

The post Cloudflare and OpenAI Partner to Redefine Vulnerability Management with AI-Powered Edge Defense appeared first on ITDigest.

As enterprise organizations scale artificial intelligence initiatives, data fragmentation and cross-platform transfer costs present significant operational challenges. By connecting Teradata VantageCloud natively to Microsoft OneLake via open delta lake formats, enterprise data science teams, analytics leads, and IT architects can run advanced AI models, machine learning algorithms, and real-time business intelligence across unified enterprise data repositories.

“Enterprises want the flexibility to run their preferred AI and analytics engines directly where their data lives,” said Enterprise Data Strategy Lead at Teradata. “By extending Teradata VantageCloud directly to Microsoft OneLake, we are removing data movement friction, lowering operational overhead, and enabling our joint customers to maximize the return on their cloud data assets with full security and governance.”

Also Read: SandboxAQ Open-Sources Switch to Bring AI Agents into Team Chat Platforms 

Unlocking Zero-Copy AI and Analytics Across Microsoft Fabric

The integration leverages open storage standards, allowing Teradata’s query execution engine to access and analyze OneLake delta tables in place. This zero-copy architecture ensures data integrity, maintains centralized governance protocols, and reduces latency across enterprise workflows.

Key operational benefits of the Teradata and Microsoft OneLake integration include:

Zero-Copy Data Access: Eliminates data duplication and ETL pipelines by running Teradata analytics directly against OneLake data assets.

Unified Governance & Security: Preserves active enterprise access controls, data lineage tracking, and compliance policies across hybrid cloud environments.

Scalable AI Performance: Combines Teradata’s high-concurrency query engine with Microsoft Fabric’s open data ecosystem to accelerate model training and execution.

Cost & Infrastructure Optimization: Significantly reduces data egress fees and cloud storage redundancy for large-scale enterprise deployments.

“Modern enterprise AI requires seamless interoperability across cloud architectures,” said Cloud Solutions Director at Microsoft. “Integrating Teradata VantageCloud with Microsoft Fabric OneLake provides our shared enterprise clients with the speed, scale, and openness required to transform raw enterprise data into actionable AI outcomes.”

Accelerating Enterprise AI Deployment at Scale

With Teradata‘s enterprise processing engine and Microsoft’s open lakehouse ecosystem combined, the solution frees the data engineering and analytics teams from having to spend time on infrastructure integration to focus instead on business value. The combined platform enables businesses worldwide to transform their operations faster, save on operational expenses, and set up a foundation that scales for next-generation enterprise AI.

The post Teradata Integrates Enterprise AI into Microsoft OneLake appeared first on ITDigest.

In Hardware and Network news this week…

Equinix Launches Fabric One to Simplify AI and Multi-Cloud Interconnectivity
Equinix has launched Fabric One to simplify connectivity across AI workloads, cloud platforms, and distributed enterprise infrastructure. The solution is designed to help organizations establish more seamless interconnections across multiple environments while improving flexibility and network management. As enterprises increasingly distribute AI workloads across clouds and data centers, streamlined interconnectivity is becoming critical to maintaining performance and scalability.

In Artificial Intelligence news this week…

PwC and Palantir Expand Strategic Alliance to Accelerate Production-Grade Enterprise AI Deployment
PwC and Palantir are expanding their strategic alliance to help organizations move AI initiatives from experimentation into production. The collaboration focuses on combining Palantir’s AI and data capabilities with PwC’s industry and transformation expertise to support enterprise-scale deployments. The partnership reflects growing demand for practical AI solutions that can deliver measurable business value while addressing governance and operational requirements.

In Cloud Computing & Mobility news this week…

HUMAIN Partners with Compal to Expand Cloud-to-Edge AI Infrastructure
HUMAIN and Compal have partnered to expand AI infrastructure spanning cloud and edge environments. The collaboration aims to support the growing computational requirements of AI applications while enabling workloads to operate closer to where data is generated. Cloud-to-edge architectures can help organizations improve responsiveness, manage data efficiently, and support AI use cases that require low latency.

In Enterprise AI news this week…

Boomi Introduces Agent Control Plane to Solve the Enterprise AI Governance Crisis
Boomi has introduced an Agent Control Plane designed to provide enterprises with greater oversight of AI agents and their activities. The technology focuses on governance, visibility, and control as organizations deploy increasing numbers of autonomous AI systems across business workflows. Establishing centralized management will be increasingly important for enterprises seeking to scale agentic AI while maintaining security, compliance, and accountability.

In FinTech news this week…

Visa Enhances A2A Protect to Help Financial Institutions Combat Real-Time Fraud
Visa has enhanced A2A Protect to help financial institutions detect and combat fraud across real-time account-to-account payments. The solution is designed to strengthen fraud prevention as instant payment systems expand and transactions move faster than traditional monitoring processes. Enhanced real-time protection can help financial institutions reduce fraud exposure while maintaining faster and more convenient payment experiences.

In HealthTech news this week…

Abcam and Genedata Collaborate to Accelerate AI-Driven Antibody Development
Abcam and Genedata are collaborating to accelerate antibody development through AI and advanced scientific data capabilities. The partnership aims to improve research workflows and help scientists work more efficiently with complex biological information. AI-driven approaches could help life sciences organizations shorten research cycles and support the development of new therapeutic candidates.

In Cybersecurity news this week…

Cognizant and CrowdStrike Unify IT and OT Security to Protect Critical Operations
Cognizant and CrowdStrike are combining IT and operational technology security capabilities to help organizations protect critical operations. The collaboration addresses the growing convergence between enterprise IT systems and operational environments, where cyber incidents can have significant operational consequences. Unified visibility and threat detection can help organizations strengthen resilience across increasingly connected infrastructures.

Article of the Week

Eco-Friendly Enterprise Software Initiatives: How Businesses Can Build More Sustainable Digital Operations

Sustainability is becoming an increasingly important consideration in enterprise technology strategy as organizations seek to reduce the environmental impact of their digital operations. Businesses can improve efficiency through optimized software, cloud resource management, automation, energy-conscious infrastructure, and responsible data practices. By embedding sustainability into technology decisions, enterprises can reduce resource consumption while improving operational efficiency and supporting broader environmental objectives.

The post ITDigest’s Weekly News Roundup Featuring Equinix, PwC, HUMAIN, Boomi, Visa, Abcam, Cognizant, and more appeared first on ITDigest.

Also Read: Sinch Unveils Agent Tools to Integrate Communications APIs into AI Coding Workflows

“Developers want powerful AI tools that fit naturally into their workflows, and enterprises need those tools to run in environments they control. Cloudflare Sandboxes gives teams the freedom to use the AI tools they prefer while giving organizations a secure, isolated place to run agent work. Bringing Cursor Cloud Agents to Cloudflare Sandboxes is another step toward making Cloudflare the execution layer for the next generation of agentic applications.” Reaffirming the collaborative value for distributed development teams, Toni Adams, Sr Director of Partnerships at SpaceXAI, added: “SpaceXAI’s goal is to make agents useful wherever developers work. Self-Hosted Machines let teams keep Cursor workflows across desktop, web, and mobile while routing work to infrastructure they operate. Cloudflare Sandboxes give those teams an enterprise-grade option for running agent workloads in a controlled environment.” Ultimately, this solution enables organizations to deploy scalable worker pools dynamically, reinforcing Cloudflare’s position as a foundational execution layer for platform-native agentic software.

Read More: Cloudflare Expands Support for AI Coding Agents with Cursor Cloud Agents on Cloudflare Sandboxes

The post Cloudflare Expands Support for AI Coding Agents via Cursor Integration appeared first on ITDigest.

VMware Cloud Foundation 9.1 provides an integrated private cloud solution designed to support traditional virtualized software as well as containerized application workloads. With instant compatibility testing, enterprises planning to migrate to VCF 9.1 are able to implement the upgraded version without affecting their existing operations or storage infrastructure.

Unifying Enterprise Data Estates Across Hyperscale Clouds

To maximize data utility, modern enterprises require flexible architectures capable of operating fluidly across on-premises data centers and public cloud environments. NetApp’s first-party cloud storage solutions represent the only external enterprise storage certified to support VMware Cloud Foundation across major hyperscale cloud providers. Supported by VCF license portability, organizations can deploy VCF in certified hyperscaler environments and migrate VMware workloads to the cloud without application refactoring.

Also Read: HUMAIN Partners with Compal to Expand Cloud-to-Edge AI Infrastructure 

“To keep up with the rapid pace of innovation required to thrive in a competitive landscape, enterprises need flexibility to move and place workloads in the best environment to which they are suited,” said Alvaro Celis, Chief Partner and Ecosystem Officer at NetApp. “NetApp continues to innovate to ensure VCF customers can operate consistently and without disruption across cloud environments. Together with Broadcom, we are giving organizations the autonomy to optimize, protect, and scale their virtualized environments across any cloud on their own terms, safeguarding their existing operational investments while unlocking the future.”

Operational Benefits of NetApp ONTAP and VCF 9.1 Integration

Integrating the NetApp platform with VCF 9.1 delivers several operational and security advantages for hybrid cloud deployments:

Scalable Cost-Efficient Infrastructure: VCF 9.1 improves the density of virtual machine workloads and container-based AI engines, as well as automates many cloud infrastructure management processes. The use of NetApp ONTAP acts as a primary storage system in the VCF management and workload domain space without necessitating modifications to existing applications.

Cyber Resilience: Improvements such as NetApp Console Backup and Recovery and NetApp Console Data Services help defend against any ransomware attacks on data. Moreover, future ONTAP Tools for VMware will add data store-level replication and consistency groups within the vCenter UI and using REST APIs through the VCF Operations Orchestrator.

Kubernetes and DevOps Management: Validated support for VMware vSphere Kubernetes Service (VKS) in VCF 9.1 allows IT departments to run microservices, CI/CD workflows, and distributed apps in addition to VMs on the same data platform.

“Broadcom and NetApp have long collaborated on solutions that help organizations simplify operations, protect critical data, and innovate faster,” said Paul Turner, Chief Product Officer, VMware Cloud Foundation Division at Broadcom. “With VCF 9.1, we are delivering an AI- and Kubernetes-native private cloud platform that maximizes infrastructure efficiency and security. Because NetApp’s solutions are tested and validated to support VCF 9.1 environments, our mutual customers can adopt these innovations with a data infrastructure foundation that is proven and ready.”

Availability

NetApp‘s validated solutions for VMware Cloud Foundation 9.1 are available immediately to global enterprise customers. Cloud architects, IT infrastructure leads, and systems administrators can evaluate technical configurations or request deployment support by visiting the official NetApp digital portal.

The post NetApp Validates ONTAP to Support VMware Cloud Foundation 9.1 appeared first on ITDigest.

Developed with lead integration partners Amazon Web Services (AWS) and Google Cloud, Equinix Fabric One utilizes open connectivity standards to support seamless interoperability across hybrid enterprise IT ecosystems. Instead of manually engineering individual network links, organizations can define specific connectivity requirements through digital interfaces, allowing Equinix Fabric One to automatically orchestrate and manage underlying network paths. Concurrently, the company announced Equinix® Inference Exchange to accelerate global enterprise AI infrastructure deployments.

“For decades, enterprise networks have been built one connection at a time for each partner and provider they depend on. That approach doesn’t scale in a world of distributed AI that demands dynamic, flexible and real-time connectivity,” said Chris Audie, Chief Product Officer, Equinix. “Equinix Fabric One will reduce the complexity that’s slowing enterprises down by automatically managing connectivity across distributed architectures, based on the customer’s intent.”

Also Read: Lightyear Debuts First Agentic Platform for Enterprise Telecom Lifecycle

Streamlining Complex Multi-Cloud and AI Network Operations

As modern enterprises expand connections across diverse cloud environments, specialized AI models, and regional facilities, traditional network engineering creates administrative bottlenecks. Equinix Fabric One modernizes this framework by allowing teams to request outcomes through natural-language prompts, developer APIs, automation scripts, or management portals.

Once triggered, the managed service automatically handles routing protocols, cloud interconnections, encryption parameters, network resiliency, and failover mechanics as a unified operational layer.

“Networking is still a key area of enterprise infrastructure that remains heavily dependent on manual design and operations,” said Andrew Buss, Senior Research Director, Cloud and Datacenters, Enterprise Infrastructure at IDC. “Organizations are increasingly looking for ways to simplify and automate how connectivity is provisioned and managed across distributed cloud and AI environments, but achieving this transformation remains a major challenge. Advances that enable more integrated automation and intent-driven approaches can reduce operational complexity and risk while supporting the flexibility modern AI and multicloud architectures require.”

Equinix Fabric One builds upon the company’s vendor-neutral ecosystem, which connects over 10,500 enterprise businesses and approximately 3,000 cloud and IT service providers. The infrastructure currently supports active deployments for eight of the top 10 global AI model developers and nine of the top 10 neocloud providers.

Neutral Architecture Built on Open Standards

Equinix Fabric One leverages the open-source OpenAPI 3.0 Interconnect specification co-developed alongside AWS and Google Cloud to maintain cross-platform interoperability. As enterprise computing transitions toward autonomous agentic architectures, software applications and AI agents can discover, request, and configure network connections programmatically without human intervention.

“Customers shouldn’t have to figure out how to connect across multiple clouds and AI environments on their own,” said Robert Kennedy, Vice President, AWS network services. “They should just define what they need and have it work. Fabric One builds on the open interconnect specification that AWS and Google Cloud helped define and deliver exactly that. A managed service that handles the complexity so customers can focus on their AI workloads, not how everything connects.”

“Cross-cloud interoperability is the backbone of the AI era,” said Rob Enns, Vice President of Engineering, Cloud Networking, Google Cloud. “We helped establish the open interconnect specification so enterprises no longer have to manage the complexity of multi-cloud networking. By combining Google Cloud’s Cross-Cloud Network capabilities with Equinix Fabric One, we are giving customers an automated, intent-driven network that lets them quickly deploy distributed AI workloads.”

“As technology environments become more distributed, AI workloads and multicloud architectures require connectivity that is flexible, scalable and easier to manage,” said Paul Hager, CEO, Hyundai AutoEver America. “Equinix Fabric One has the potential to accelerate our efforts to meet those needs.”

The post Equinix Launches Fabric One to Simplify AI and Multi-Cloud Interconnectivity appeared first on ITDigest.