[Deal du jour] La DualSense Edge, sans être un modèle indispensable, est un bon accessoire, malheureusement vendu trop cher à sa sortie l'an dernier. La manette pro de la PlayStation 5 est bien plus intéressante lorsque son prix baisse un peu. Des promotions sur la console et ses accessoires sont aussi disponibles.
Alerte rouge dans la galaxie des navigateurs web ! Microsoft vient d’annonce qu’une faille critique 0-day a été découverte dans Edge et corrigée en urgence. Mais attention, cette vulnérabilité ne se limite pas au navigateur de Microsoft puisque c’est toute la famille Chromium qui est touchée !
Google a bien tenté de faire profil bas en publiant discrètement un correctif pour Chrome le 26 mars, sans trop s’étendre sur les détails. Mais c’était sans compter sur la perspicacité de Microsoft qui a mis les pieds dans le plat en confirmant que l’exploit était activement utilisé par des cybercriminels. Aïe !
Baptisée CVE-2024-2883, cette vilaine faille se cache dans le moteur graphique ANGLE (Almost Native Graphics Layer Engine) utilisé par les navigateurs Chromium pour faire tourner le WebGL. En gros, c’est la porte d’entrée parfaite pour exécuter du code malveillant sur votre machine.
Heureusement, Microsoft a réagi au quart de tour en sortant illico presto la version 123.0.2420.65 d’Edge qui colmate la brèche. Mais attention, si vous utilisez un autre navigateur basé sur Chromium comme Chrome, Brave, Vivaldi ou Opera, vous êtes aussi concernés. Alors, foncez vérifier que vous avez bien la dernière version à jour !
Pour ce faire, rien de plus simple : tapez « chrome://settings/help » (ou l’équivalent pour votre navigateur) dans la barre d’adresse et laissez la magie opérer. Si une mise à jour est disponible, elle sera téléchargée et installée automatiquement. Ensuite, relancez le navigateur et le tour est joué !
Ce n’est pas la première fois qu’une faille 0-day fait trembler le monde des navigateurs. En 2021, une vulnérabilité similaire avait été découverte dans Chrome et avait été activement exploitée pendant des semaines avant d’être corrigée. Un vrai cauchemar pour les utilisateurs et les éditeurs !
Vous utilisez Microsoft Edge sur Windows Server et il se ferme au bout de quelques secondes ? Sachez que vous n'êtes pas le seul et que ce problème serait lié à la version 123 du navigateur Edge. Faisons le point sur ce problème.
La Build 123.0.2420.53 de Microsoft Edge semble donner du fil à retordre aux administrateurs systèmes qui exploitent ce navigateur sur Windows Server. En effet, cette version ne semble pas fonctionner correctement : une page blanche s'ouvre au démarrage, puis quelques secondes plus tard, le navigateur se ferme tout seul. Ceci peut s'avérer très problématique sur certains serveurs, notamment les hôtes de sessions Bureau à distance (RDS) où les utilisateurs se connectent directement !
Ce problème fait suite à l'installation de la version 123.0.2420.53 sur Windows Server. Une version disponible depuis quelques jours sur Windows et Windows Server puisqu'elle a introduit le canal Stable de Microsoft Edge le 23 mars 2024.
Actuellement, la solution consiste à revenir en arrière, c'est-à-dire sur une version antérieure de Microsoft Edge. D'ailleurs, sur le forum de Microsoft une ligne de commande a été fournie par un utilisateur pour expliquer comment revenir en arrière à partir du package MSI d'une précédente version d'Edge grâce à l'utilisation du paramètre "ALLOWDOWNGRADE=1" :
Connexionmsiexec /I Microsoft Edge_122.0.2365.106_Machine_X64_msi_en-US.msi ALLOWDOWNGRADE=1Vous pouvez télécharger la version de Microsoft Edge de votre choix à partir de cette page. Sur la page du forum Microsoft, l'agent qui a répondu confirme que d'autres utilisateurs ont rencontré ce problème ! D'ailleurs, ces dernières heures, Microsoft a retiré cette mise à jour de son catalogue et elle n'est plus distribuée via WSUS : preuve qu'il y a un réel problème avec celle ! En attendant, si elle est déjà passée sur vos serveurs, vous risquez de rencontrer ce problème !
Et vous, rencontrez-vous ce bug sur Windows Server ?
PS : merci à Fabien Guérout de chez Délibérata (un ancien collègue !) de m'avoir signalé ce dysfonctionnement et confirmé que le downgrade vers une version antérieure permettait de corriger ce problème !
The post Sur Windows Server, Microsoft Edge 123 ne fonctionne plus ! Que se passe-t-il ? first appeared on IT-Connect.
As a key technology partner with NVIDIA, Canonical is proud to showcase our joint solutions at NVIDIA GTC again. Join us in person at NVIDIA GTC on March 18-21, 2024 to explore what’s next in AI and accelerated computing. We will be at booth 1601 in the MLOps & LLMOps Pavilion, demonstrating how open source AI solutions can take your models to production, from edge to cloud.
As the world becomes more connected, there is a growing need to extend data processing beyond the data centre to edge devices in the field. As we all know, cloud computing provides numerous resources for AI adoption, processing, storage, and analysis, but it cannot support every use case. Deploying models to edge devices can expand the scope of AI devices by enabling you to process some of the data locally and achieve real-time insights without relying exclusively on the centralised data centre or cloud. This is especially relevant when AI applications would be impractical or impossible to deploy in a centralised cloud or enterprise data centre due to issues related to latency, bandwidth and privacy.
Therefore, a solution that enables scalability, reproducibility, and portability is the ideal choice for a production-grade project. Canonical delivers a comprehensive AI stack with the open source software which your organisation might need for your AI projects from cloud to edge, giving you:
To put our AI stack to the test, during NVIDIA GTC 2024, we will present how our Kubernetes-based AI infrastructure solutions can help create a blueprint for smart cities, leveraging best-in-class NVIDIA hardware capabilities. We will cover both training in the cloud and data centres, and showcase the solution deployed at the edge on Jetson Orin based devices. Please check out the details below and meet our expert on-site.
Abstract:
Artificial intelligence is no longer confined to data centres; it has expanded to operate at the edge. Some models require low latency, necessitating execution close to end-users. This is where edge computing, optimised for AI, becomes essential. In the most popular use cases for modern smart cities, many envision city-wide assistants deployed as “point-of-contact” devices that are available on bus stops, subways, etc. They interact with backend infrastructure to take care of changing conditions while users travel around the city. That creates a need to process local data gathered from infrastructure like internet-of-things gateways, smart cameras, or buses. Thanks to NVIDIA Jetson modules, these data can be processed locally for fast, low-latency AI-driven insights. Then, as device-local computational capabilities are limited, data processing should be offloaded to the edge or backend infrastructure. With the power of Tegra SoC, data can first be aggregated at the edge devices to be later sent to the cloud for further processing. Open-source deployment mechanisms enable such complex setups through automated management, Day 2 operations, and security. Canonical, working alongside NVIDIA, has developed an open-source software infrastructure that simplifies the deployment of multiple Kubernetes clusters at the edge with access to GPU. We’ll go over those mechanisms, and how they orchestrate the deployment of Kubernetes-based AI/machine learning infrastructure across the smart cities blueprint to profit from NVIDIA hardware capabilities, both on devices and cloud instances.
Presenter: Gustavo Sanchez, AI Solutions Architect, Canonical
Starting a deep learning pilot within an enterprise has its set of challenges, but scaling projects to production-grade deployments brings a host of additional difficulties. These chiefly relate to the increased hardware, software, and operational requirements that come with larger and more complex initiatives.
Canonical and NVIDIA offer an integrated end-to-end solution – from a hardware optimised Ubuntu to application orchestration and MLOps. We enable organisations to develop, optimise and scale ML workloads.
Canonical will showcase 3 demos to walk you through our joint solutions with NVIDIA on AI/ML:
Visit our Canonical booth 1601 at GTC to check them out.
If you are interested in building or scaling your AI projects with open source solutions, we are here to help you. Visit ubuntu.com/nvidia to explore our joint data centre offerings.
In the fast-paced world of technology, innovation is the key to staying ahead of the curve. As businesses strive for efficiency, speed, and real-time data processing, the spotlight is increasingly turning towards edge computing.
Edge computing represents a paradigm shift in the way data is processed and analysed. Unlike traditional cloud computing, which centralises data processing in distant data centres, edge computing brings the processing power closer to the source of data. This not only reduces latency but also opens up a world of possibilities for industries across the board.
In this blog, we’re excited to explore examples of this cutting-edge technology, with its diverse applications and use cases, with a special focus on how Canonical’s MicroCloud fits seamlessly into this transformative landscape.
Edge computing plays a pivotal role in the development of smart cities. By deploying edge devices such as sensors and cameras throughout urban environments, data can be processed locally to optimise traffic management, enhance public safety, and improve overall city infrastructure. Real-time analytics at the edge enable swift decision-making, leading to more efficient and responsive urban systems.
The healthcare sector is leveraging edge computing to enhance patient care and streamline medical processes. Edge devices in healthcare facilities enable real-time monitoring of patients, ensuring timely intervention and reducing the need for extensive data transfer to centralised servers. In remote areas, edge computing facilitates telemedicine, providing access to healthcare services for those in underserved communities.
Edge computing is revolutionising industrial operations by enabling predictive maintenance through the Internet of Things (IoT). In manufacturing environments, sensors attached to machinery collect and analyse data locally. This allows for early detection of potential issues, minimising downtime and optimising maintenance schedules. The result is increased efficiency, reduced costs, and improved overall equipment effectiveness.
The automotive industry is embracing edge computing to power autonomous vehicles and enhance road safety. Edge devices onboard vehicles process data from numerous sensors, cameras, and lidar in real-time, enabling quick decision-making without relying on distant cloud servers. This low-latency approach is critical for the success and safety of autonomous driving systems.
Edge computing transforms the retail experience by enabling personalised services and improving customer engagement. In-store cameras and sensors analyse customer behaviour, allowing retailers to offer targeted promotions and optimise inventory management. This real-time data processing at the edge enhances customer satisfaction and creates a more seamless shopping experience.
In the dynamic landscape of edge computing, choosing the right solution is paramount. Canonical’s MicroCloud emerges as an ideal edge cloud solution, seamlessly aligning with the diverse edge computing examples presented. Offering a compact and efficient cloud infrastructure, MicroCloud is designed to deliver edge computing capabilities with a focus on simplicity, scalability, and reliability.
Compact Form Factor: MicroCloud’s compact form factor makes it suitable for deployment in diverse environments, from industrial settings to urban landscapes, ensuring that edge computing resources are readily available where they are needed the most.
Scalability: MicroCloud allows for easy scalability, accommodating the varying demands of edge computing applications. Whether it’s in a smart city deployment or an industrial automation setting, MicroCloud can scale to meet the evolving needs of the edge.
Reliability and Security: With a robust architecture, MicroCloud ensures the reliability and security of edge computing operations. Its design aligns with the stringent data security requirements of industries such as healthcare and telecommunications, providing a trustworthy foundation for critical applications.
To delve deeper into the world of edge computing and its dynamic use cases, read more in our whitepaper, “Edge computing use cases across industries”. This whitepaper explores real-world examples, industry-specific applications, and the potential impact of edge computing on businesses and society.
As we navigate the ever-evolving technological landscape, understanding the practical applications of edge computing is crucial for businesses aiming to stay ahead. This whitepaper serves as a valuable resource for those seeking to harness the power of edge computing and unlock new possibilities in their respective industries.
Adopting open-source Industrial IoT software
How a real-time kernel reduces latency in telco edge clouds
CTO’s guide to MicroCloud: Learn how to build your Edge strategy with MicroCloud
