Latest news with #MicrosoftAzure
Techday NZ
2 days ago
- Techday NZ
Poor cloud security leaves secrets & data at risk, report finds
A new report from Tenable Research has detailed the ongoing risks facing organisations due to poor cloud security practices and widespread misconfigurations. The 2025 Cloud Security Risk Report analyses data from global cloud systems spanning October 2024 to March 2025. It highlights significant vulnerabilities related to data exposure, identity management, cloud workloads, and the use of artificial intelligence resources. The findings indicate that sensitive information and credentials remain at risk due to inconsistent security implementations across major public cloud providers. Exposure of sensitive data According to Tenable Research, 9% of publicly accessible cloud storage contains sensitive data, and 97% of this content is classified as restricted or confidential. These circumstances increase the risk of exploitation, particularly when misconfigurations or embedded secrets are also present. The report notes that cloud environments are subject to significantly heightened risk from exposed data, misconfigured access, and the insecure storage of secrets such as passwords, API keys, and other credentials. These issues are compounded by underlying vulnerabilities and inconsistent security practices across organisations using public cloud providers like Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure. Secrets and workload security The assessment documented that over half of organisations (54%) store at least one secret directly within AWS Elastic Container Service (ECS) task definitions, creating a direct attack path for threat actors. On GCP Cloud Run, similar patterns were observed, with 52% of organisations found to be storing secrets within resources, and 31% on Microsoft Azure Logic Apps workflows. Furthermore, 3.5% of all AWS Elastic Compute Cloud (EC2) instances were identified as containing secrets within user data. AWS EC2's broad adoption means this level of exposure represents a substantial risk across the industry. The report points to some improvement in cloud workload security: the prevalence of the so-called "toxic cloud trilogy"-a situation in which a workload is publicly exposed, critically vulnerable, and endowed with high privilege-has decreased from 38% to 29%. However, Tenable researchers note that this combination continues to represent a significant risk for businesses. Issues in identity and access management One significant finding relates to the use of Identity Providers (IdPs). The research indicates that 83% of AWS organisations employ IdP services to manage cloud identities, which is regarded as best practice. Despite this, risks persist due to permissive default settings, excessive entitlements, and lingering standing permissions that give rise to identity-based threats. "Despite the security incidents we have witnessed over the past few years, organizations continue to leave critical cloud assets, from sensitive data to secrets, exposed through avoidable misconfigurations," said Ari Eitan, Director of Cloud Security Research, Tenable. The report suggests that attackers are often able to find entry points with relative ease, exploiting public access, extracting embedded secrets, or misusing over-privileged identities. Recommendations and risk management "The path for attackers is often simple: exploit public access, steal embedded secrets or abuse overprivileged identities. To close these gaps, security teams need full visibility across their environments and the ability to prioritize and automate remediation before threats escalate. The cloud demands continuous, proactive risk management, and not reactive patchwork," added Eitan. Tenable's analysis is based on telemetry collected from a diverse array of public cloud and enterprise environments and provides detailed insight into the cloud security challenges currently faced by businesses. The report offers practical recommendations to help security professionals reduce risks, mitigate vulnerabilities, and address gaps before they can be exploited. The findings underline the necessity for organisations to adopt unified cloud exposure management, increase visibility across their cloud assets, and take a systematic approach to automation and remediation of security risks, particularly as cloud adoption and reliance on AI-driven resources continue to rise.
Time Business News
4 days ago
- Business
- Time Business News
Leveraging AI and Automation within Managed Azure Services for Proactive Cloud Monitoring
In today's rapidly evolving digital landscape, cloud computing has become the backbone of enterprise IT infrastructure. As organizations migrate more workloads to the cloud, the complexity of managing and monitoring these environments increases exponentially. This complexity drives the need for sophisticated solutions that can not only react to issues but also proactively identify potential risks before they impact business operations. managed Azure services, combined with the power of artificial intelligence (AI) and automation, have emerged as key enablers for achieving proactive cloud monitoring, ensuring reliability, security, and optimized performance. Managed Azure Services refer to third-party or in-house solutions where cloud infrastructure and platform management are outsourced or centrally controlled to optimize operations on Microsoft Azure. These services encompass a wide array of activities, including resource provisioning, configuration management, security enforcement, compliance monitoring, performance optimization, and troubleshooting. By leveraging managed Azure services, organizations benefit from expert handling of their Azure environments, often leading to reduced downtime, better security postures, and enhanced operational efficiencies. The integration of AI and automation within these services is transforming the way cloud monitoring is performed, shifting it from reactive to proactive management. Azure environments can consist of hundreds or even thousands of resources such as virtual machines, databases, containers, networking components, and applications. Monitoring these at scale to ensure uptime, security, and performance is daunting. Traditional monitoring methods—manual checks, static alerts, and simple thresholds—are often insufficient. They generate excessive noise with false positives, delay incident detection, and demand significant human intervention. Moreover, the dynamic nature of cloud workloads, where resources are spun up and down on demand, requires a continuous and adaptive monitoring approach. Here, AI and automation embedded within managed Azure services bring unparalleled advantages. Artificial intelligence, particularly machine learning (ML), excels at pattern recognition, anomaly detection, and predictive analytics—all critical capabilities for proactive cloud monitoring. Anomaly Detection: AI models analyze historical performance metrics, logs, and telemetry data to learn what constitutes 'normal' behavior. When deviations occur—such as unusual CPU spikes, memory leaks, or network latency—the AI flags these anomalies early. This early warning allows administrators or automated workflows to investigate and remediate issues before users notice any degradation. AI models analyze historical performance metrics, logs, and telemetry data to learn what constitutes 'normal' behavior. When deviations occur—such as unusual CPU spikes, memory leaks, or network latency—the AI flags these anomalies early. This early warning allows administrators or automated workflows to investigate and remediate issues before users notice any degradation. Predictive Maintenance: Beyond detecting current issues, AI can forecast potential failures by identifying trends like resource exhaustion or growing error rates. For example, if a storage account shows increasing latency and error counts over several days, the system can predict an impending failure and trigger preemptive actions such as data migration or scaling. Beyond detecting current issues, AI can forecast potential failures by identifying trends like resource exhaustion or growing error rates. For example, if a storage account shows increasing latency and error counts over several days, the system can predict an impending failure and trigger preemptive actions such as data migration or scaling. Intelligent Alerting: AI-driven monitoring reduces alert fatigue by correlating related events, filtering false positives, and prioritizing alerts based on severity and business impact. This ensures the operations team focuses on genuine threats and critical incidents. AI-driven monitoring reduces alert fatigue by correlating related events, filtering false positives, and prioritizing alerts based on severity and business impact. This ensures the operations team focuses on genuine threats and critical incidents. Root Cause Analysis: AI can accelerate problem diagnosis by analyzing logs and telemetry across multiple resources, identifying the root cause faster than manual methods. For instance, AI might correlate a network configuration change with a sudden drop in application performance. Microsoft Azure itself offers AI-powered monitoring tools like Azure Monitor and Azure Sentinel, which managed Azure services teams integrate and customize to suit specific organizational needs. Automation complements AI by taking immediate actions based on AI insights, ensuring rapid response and minimizing human intervention. Automated Remediation: When AI detects an anomaly or predicts a failure, automation scripts or workflows can be triggered to mitigate the issue instantly. Examples include restarting a troubled virtual machine, scaling out a containerized application, or applying a security patch. When AI detects an anomaly or predicts a failure, automation scripts or workflows can be triggered to mitigate the issue instantly. Examples include restarting a troubled virtual machine, scaling out a containerized application, or applying a security patch. Self-Healing Infrastructure: Managed Azure services can implement self-healing mechanisms where systems automatically recover from known issues. For example, if an application service becomes unresponsive, the automation engine can recycle it or provision a new instance without human input. Managed Azure services can implement self-healing mechanisms where systems automatically recover from known issues. For example, if an application service becomes unresponsive, the automation engine can recycle it or provision a new instance without human input. Policy Enforcement: Automation ensures compliance and governance by continuously checking for configuration drift or security misconfigurations and automatically correcting them or alerting administrators. Automation ensures compliance and governance by continuously checking for configuration drift or security misconfigurations and automatically correcting them or alerting administrators. Continuous Deployment and Updates: Automated pipelines enable seamless updates to monitoring rules, AI models, and remediation workflows, ensuring the monitoring system evolves with changing cloud environments. Proactive identification and resolution of issues significantly reduce downtime. Managed Azure services equipped with AI-powered monitoring can detect subtle performance degradation long before it impacts end-users, allowing for timely interventions. AI-driven threat detection tools embedded in managed Azure services continuously scan logs and network traffic to detect suspicious activities such as brute force attempts, data exfiltration, or insider threats. Automated responses can isolate compromised resources immediately, limiting damage. Automating routine monitoring tasks and remediation frees cloud administrators to focus on strategic initiatives. This reduces the need for large operations teams and cuts operational costs. As organizations grow and cloud usage expands, AI and automation scale effortlessly to handle increasing data volumes and resource counts, maintaining consistent monitoring coverage without proportional increases in headcount. Advanced analytics and predictive insights provided by AI empower IT leadership with actionable intelligence for capacity planning, budgeting, and risk management. To successfully leverage AI and automation for proactive cloud monitoring, organizations should consider the following implementation strategies within their managed Azure services framework: Comprehensive Data Collection: Ensure all relevant metrics, logs, and telemetry are collected from Azure resources and integrated systems. This data forms the foundation for AI analysis. Ensure all relevant metrics, logs, and telemetry are collected from Azure resources and integrated systems. This data forms the foundation for AI analysis. Customize AI Models: Use Azure's built-in AI tools but customize machine learning models based on your environment's unique behavior patterns and business priorities. Use Azure's built-in AI tools but customize machine learning models based on your environment's unique behavior patterns and business priorities. Integrate Automated Playbooks: Develop runbooks and workflows in Azure Logic Apps, Azure Functions, or other automation tools that can be triggered by AI-generated alerts for immediate remediation. Develop runbooks and workflows in Azure Logic Apps, Azure Functions, or other automation tools that can be triggered by AI-generated alerts for immediate remediation. Continuous Learning and Improvement: Regularly refine AI models and automation scripts to adapt to evolving cloud workloads, emerging threats, and operational feedback. Regularly refine AI models and automation scripts to adapt to evolving cloud workloads, emerging threats, and operational feedback. Collaboration Between Teams: Foster close collaboration between cloud operations, security, and development teams to define monitoring KPIs, automate incident response, and ensure comprehensive coverage. Foster close collaboration between cloud operations, security, and development teams to define monitoring KPIs, automate incident response, and ensure comprehensive coverage. Leverage Managed Service Providers (MSPs): Many organizations partner with MSPs specializing in managed Azure services who bring deep expertise in AI and automation technologies, accelerating deployment and optimizing outcomes. E-Commerce Platform: An online retailer using managed Azure services integrated AI-driven monitoring to detect and resolve performance bottlenecks during peak sales periods. Automated scaling and remediation maintained smooth user experience and prevented revenue loss. Financial Institution: A bank leveraged AI-powered threat detection and automated incident response within managed Azure services to strengthen its security posture. Suspicious activities were flagged and isolated in real time, minimizing risk. Healthcare Provider: By employing managed Azure services with AI and automation, a healthcare organization ensured continuous compliance monitoring and rapid resolution of system issues, maintaining critical patient data availability. The fusion of AI, automation, and managed Azure services will continue to evolve, with emerging technologies like AI-driven orchestration, natural language processing for conversational monitoring, and advanced edge computing integration enhancing cloud monitoring further. Organizations that adopt these innovations proactively will gain a competitive edge through superior cloud reliability, security, and operational excellence. Conclusion Managed Azure services empowered with AI and automation represent a paradigm shift in cloud monitoring—from reactive firefighting to proactive management. By harnessing AI's predictive capabilities and automation's rapid response, organizations can ensure their Azure environments run smoothly, securely, and efficiently. As cloud complexity grows, these technologies will be indispensable for enterprises seeking to maximize the value of their cloud investments. TIME BUSINESS NEWS
Forbes
4 days ago
- Business
- Forbes
Is Nvidia Competing With Its GPU Cloud Partners?
Nvidia Headquarters in Santa Clara, CA. Nvidia recently announced two new cloud initiatives. First, the company announced DGX Cloud Lepton, designed to connect artificial intelligence developers with Nvidia's wide network of cloud providers. Second, Nvidia announced a new cloud service, the Industrial AI Cloud, intended to provide AI services to manufacturing companies in Europe. While these moves pit Nvidia against its cloud partners, the larger cloud service providers (CSPs) chose to compete with Nvidia using their in-house developed GPU alternatives. Google has the TPU, Amazon has Trainium, Microsoft has Maia, etc. (Nvidia is a client of Cambrian-AI Research.) Turn about is fair play, and Nvidia is helping its cloud partners sell AI services that keep their GPUs running at high utilization, maximizing profit, while also helping developers access a broader inventory of rare and expensive GPUs. Much to the consternation of its cloud partners, Nvidia launched the new DGX Cloud Lepton service at Computex this year, and has already garnered a healthy suite of CSPs to agree to join the service. While Oracle and Google have yet to sign up publicly for Lepton, Amazon AWS and Microsoft Azure have done so. They see the benefits of having their clouds accessible and promoted by Nvidia. The smaller GPU cloud players have also joined the party, including CoreWeave, Crusoe, Firmus, Foxconn, GMI Cloud, Lambda, Yotta Data Services, Nebius, Nscale, Firebird, Fluidstack, Hydra Host, Scaleway, Together AI, Mistral AI, SoftBank Corp. These providers offer both on-demand and long-term GPU access, supporting a wide range of AI development and deployment needs. Other CSPs won't want to miss the train, and will likely join soon. At the Paris GTC, Nvidia CEO Jensen Huang announced that Nvidia and Deutsche Telekom were building an AI Cloud for European manufacturing companies. The Industrial Cloud will provide access to state-of-the-art AI infrastructure and Nvidia's rich portfolio of software. Support will be available for CAD, CAE, Omniverse, Robotics, and Autonomous Vehicles. The cloud is fully configured to support Nvidia's optimized enterprise AI software portfolio, and should be open for business in early 2026. Nvidia's Industrial Cloud for Europe represents a major step in building sovereign, AI-powered infrastructure for the continent's industrial sector. By providing secure, high-performance compute resources and a robust AI software ecosystem, the initiative aims to propel European manufacturing into the next era of digital innovation Nvidia is partnering with Deutche Telekom to build the first Industrial AI Cloud for European ... More manufacturing companies. The Industrial Cloud will be powered by 10,000 Nvidia GPUs, including the latest DGX B200 systems and RTX PRO servers, making it one of the largest industrial AI deployments in Germany. Think of this as a manufacturing-focussed sovereign data center managed and operated by Deutsche Telekom, ensuring data sovereignty and compliance with European regulations, addressing concerns about dependency on non-European cloud providers. The lack of NVL72 racks tells us that Nvidia expects customers to fine-tune and serve AI inferencing, not create new foundation models. Users will have access to Nvidia's CUDA-X libraries and workloads accelerated by Nvidia GPUs and Omniverse, supporting a wide range of industrial applications such as simulation, digital twins, robotics, design, engineering, and factory planning. The cloud will also support applications from leading industrial software providers including Siemens, Ansys, Cadence, and Rescale, enabling advanced manufacturing workflows for companies such as BMW, Maserati, Mercedes-Benz, and Schaeffle. First, it says that Nvidia isn't afraid to compete with its cloud partners in its quest to provide access to state-of-the-art AI infrastructure to its end users. As we noted, the larger CSPs chose to develop competing AI accelerators, so they should not be surprised. Second, in reality Lepton doesn't compete with CSPs; it provides aggregated access to their massive arrays of Nvidia GPUs, not a cloud that is owned and operated by Nvidia. And the Industrial Cloud is filling a gap left by the CSPs to provide focussed and sovereign resources for the European manufacturing base. Customers will love it, and so will the ISVs whose software has been optimized to run on Nvidia GPUs.
Korea Herald
4 days ago
- Business
- Korea Herald
Aduna collaborates with Microsoft to expand global reach and intelligence of network APIs
Microsoft to join the Aduna community to power the platform on Azure, integrate AI, and accelerate CAMARA network API adoption through the Azure ecosystem PLANO, Texas, June 17, 2025 /PRNewswire/ -- Aduna, the global aggregator of network APIs, today announced that Microsoft is joining the Aduna community as a technology partner. This collaboration will focus on scaling Aduna's platform built on Microsoft Azure and integrating Microsoft AI to unlock actionable insights and intelligence for enterprises and developers using network APIs globally. Through this strategic collaboration, Aduna's aggregated network APIs will be made available as native Microsoft services via partners in the Azure Marketplace. This will give Microsoft's global developer and enterprise community direct access to network functionality including SIM Swap detection, phone number verification, real-time device location, and on-demand quality-of-service controls. These APIs are standardized through the CAMARA open-source project, co-led by the GSMA and Linux Foundation, with full specifications, documentation, and code samples openly published on GitHub for easy integration and consistent implementation. "This engagement marks a pivotal step in enabling programmable networks at scale," said Anthony Bartolo, CEO of Aduna. "Built on Azure and aligned with CAMARA, Aduna will deliver intelligent, real-time network capabilities that are exposed via GitHub and Azure to the developers and enterprises who are shaping the digital economy." In addition to powering the platform and hosting the APIs, Microsoft will actively promote the value of network APIs and the CAMARA initiative and through its go-to-market activities with Aduna's partners, including Infobip and Vonage, Microsoft will help accelerate awareness, education, and adoption of network APIs across industries such as financial services, logistics, identity, and customer experience. Perspectives Microsoft Microsoft Spokesperson, Rick Lievano, CTO added, "Our collaboration will focus on the expansion and optimization of the Aduna cloud platform and using Microsoft AI to drive insights and intelligence for both Microsoft and Aduna customers when using Network APIs. Microsoft will also be actively marketing the benefits of network APIs and GSMA Open Gateway to its customer and developer community via partnership with Aduna CPaaS partners, Azure Marketplace and GitHub. Infobip "At Infobip, we see Aduna as an important enabler in bringing the CAMARA vision to life—making network APIs more accessible, consistent, and scalable across markets. Our collaboration with Aduna is rooted in shared goals: simplifying integration for enterprises, accelerating developer adoption, and driving innovation through open standards. With Microsoft and the Azure Marketplace, we're extending that reach even further where Azure Marketplace co-sell ready CAMARA solutions are key for acceleration —ensuring CAMARA-based APIs are available where developers build, and where businesses innovate." Viktorija Radman, Telecom Business Global Director at Infobip. Vonage "Vonage has embarked on a strategic mission to make Network APIs as accessible and intuitive as Communication APIs. We are creating value for our developer partners and enterprises by making it easy for them to access advanced network capabilities to build innovative solutions that scale their businesses, create operational efficiencies and enhance customer experiences," Christophe Van de Weyer, President and Head of Business Unit API, Vonage. "Through Vonage's partnership with Aduna, we are getting access to network APIs that enable us to create demand for network-powered digital solutions through our global community of developers, developer events, and a dedicated startup program to leverage high performance programmable networks to their full potential and drive AI-led digital transformation of businesses worldwide. We are excited to see Aduna expanding with Microsoft as this will significantly accelerate our journey by enabling us to reach and engage with the vast Azure developer community." About Microsoft Microsoft (Nasdaq "MSFT") enables digital transformation for the era of an intelligent cloud and an intelligent edge. Its mission is to empower every person and every organization on the planet to achieve more. About Aduna Aduna is a landmark venture between some of the world's leading telecom operators and Ericsson, dedicated to enabling developers worldwide to accelerate innovation by leveraging networks to their full potential via common network Application Programming Interfaces (APIs). Its venture partners include: AT&T, Bharti Airtel, Deutsche Telekom, e&, KDDI, Orange, Reliance Jio, Singtel, Telefonica, Telstra, T-Mobile, Verizon and Vodafone. Aduna's developer partner platforms include Google Cloud, Infobip, Sinch, and Vonage. By combining network APIs from multiple operators globally under a unified platform based on the CAMARA open-source project, driven by the GSMA and the Linux Foundation, Aduna provides a standardized platform to foster collaboration, enhance user experiences, and drive industry growth.
Cision Canada
4 days ago
- Business
- Cision Canada
Aduna collaborates with Microsoft to expand global reach and intelligence of network APIs
Microsoft to join the Aduna community to power the platform on Azure, integrate AI, and accelerate CAMARA network API adoption through the Azure ecosystem PLANO, TX, June 17, 2025 /CNW/ -- Aduna, the global aggregator of network APIs, today announced that Microsoft is joining the Aduna community as a technology partner. This collaboration will focus on scaling Aduna's platform built on Microsoft Azure and integrating Microsoft AI to unlock actionable insights and intelligence for enterprises and developers using network APIs globally. Through this strategic collaboration, Aduna's aggregated network APIs will be made available as native Microsoft services via partners in the Azure Marketplace. This will give Microsoft's global developer and enterprise community direct access to network functionality including SIM Swap detection, phone number verification, real-time device location, and on-demand quality-of-service controls. These APIs are standardized through the CAMARA open-source project, co-led by the GSMA and Linux Foundation, with full specifications, documentation, and code samples openly published on GitHub for easy integration and consistent implementation. "This engagement marks a pivotal step in enabling programmable networks at scale," said Anthony Bartolo, CEO of Aduna. "Built on Azure and aligned with CAMARA, Aduna will deliver intelligent, real-time network capabilities that are exposed via GitHub and Azure to the developers and enterprises who are shaping the digital economy." In addition to powering the platform and hosting the APIs, Microsoft will actively promote the value of network APIs and the CAMARA initiative and through its go-to-market activities with Aduna's partners, including Infobip and Vonage, Microsoft will help accelerate awareness, education, and adoption of network APIs across industries such as financial services, logistics, identity, and customer experience. Perspectives Microsoft Microsoft Spokesperson, Rick Lievano, CTO added, "Our collaboration will focus on the expansion and optimization of the Aduna cloud platform and using Microsoft AI to drive insights and intelligence for both Microsoft and Aduna customers when using Network APIs. Microsoft will also be actively marketing the benefits of network APIs and GSMA Open Gateway to its customer and developer community via partnership with Aduna CPaaS partners, Azure Marketplace and GitHub. Infobip "At Infobip, we see Aduna as an important enabler in bringing the CAMARA vision to life—making network APIs more accessible, consistent, and scalable across markets. Our collaboration with Aduna is rooted in shared goals: simplifying integration for enterprises, accelerating developer adoption, and driving innovation through open standards. With Microsoft and the Azure Marketplace, we're extending that reach even further where Azure Marketplace co-sell ready CAMARA solutions are key for acceleration —ensuring CAMARA-based APIs are available where developers build, and where businesses innovate." Viktorija Radman, Telecom Business Global Director at Infobip. Vonage "Vonage has embarked on a strategic mission to make Network APIs as accessible and intuitive as Communication APIs. We are creating value for our developer partners and enterprises by making it easy for them to access advanced network capabilities to build innovative solutions that scale their businesses, create operational efficiencies and enhance customer experiences," Christophe Van de Weyer, President and Head of Business Unit API, Vonage. "Through Vonage's partnership with Aduna, we are getting access to network APIs that enable us to create demand for network-powered digital solutions through our global community of developers, developer events, and a dedicated startup program to leverage high performance programmable networks to their full potential and drive AI-led digital transformation of businesses worldwide. We are excited to see Aduna expanding with Microsoft as this will significantly accelerate our journey by enabling us to reach and engage with the vast Azure developer community." About Microsoft Microsoft (Nasdaq "MSFT") enables digital transformation for the era of an intelligent cloud and an intelligent edge. Its mission is to empower every person and every organization on the planet to achieve more. About Aduna Aduna is a landmark venture between some of the world's leading telecom operators and Ericsson, dedicated to enabling developers worldwide to accelerate innovation by leveraging networks to their full potential via common network Application Programming Interfaces (APIs). Its venture partners include: AT&T, Bharti Airtel, Deutsche Telekom, e&, KDDI, Orange, Reliance Jio, Singtel, Telefonica, Telstra, T-Mobile, Verizon and Vodafone. Aduna's developer partner platforms include Google Cloud, Infobip, Sinch, and Vonage. By combining network APIs from multiple operators globally under a unified platform based on the CAMARA open-source project, driven by the GSMA and the Linux Foundation, Aduna provides a standardized platform to foster collaboration, enhance user experiences, and drive industry growth. To find out more about network APIs and Aduna, visit .
