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Subject: AWS Media & Entertainment : Quoi de Neuf
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From: "Marchand, Guillaume" <gmarchan@amazon.fr>
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Date: Fri, 28 Jun 2024 17:18:41 +0200
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                       <div><span>Newsletter Media & Entertainment du lundi  9 février 2026 au vendredi 20 février 2026</span>
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                       <div><span>Innovations AWS en streaming, IA et infrastructure pour transformer vos applications</span>
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          <!-- BEGIN MODULE: Link Menu -->
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                                <span>#CloudOperation</span>
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                               <a class="pc-font-alt" href="#Compute" style="text-decoration: none; line-height: 150%; letter-spacing: -0.2px; font-family: 'Fira Sans', Arial, Helvetica, sans-serif; font-size: 12px; font-weight: 500; font-variant-ligatures: normal; color: #40be65; text-align: center; text-align-last: center;">
                                <span>#Compute</span>
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                                <span>#K8s</span>
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                                <span>#DB</span>
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                               <a class="pc-font-alt" href="#DeveloperTools" style="text-decoration: none; line-height: 150%; letter-spacing: -0.2px; font-family: 'Fira Sans', Arial, Helvetica, sans-serif; font-size: 12px; font-weight: 500; font-variant-ligatures: normal; color: #40be65; text-align: center; text-align-last: center;">
                                <span>#DeveloperTools</span>
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                                <span>#GenAI</span>
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                                <span>#ML</span>
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                               <a class="pc-font-alt" href="#Network" style="text-decoration: none; line-height: 150%; letter-spacing: -0.2px; font-family: 'Fira Sans', Arial, Helvetica, sans-serif; font-size: 12px; font-weight: 500; font-variant-ligatures: normal; color: #40be65; text-align: center; text-align-last: center;">
                                <span>#Network</span>
                               </a>
                              </td>
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                  </td>
                 </tr>
                </table>
               </td>
              </tr>
             </table>
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           </tr>
          </table>
          <!-- END MODULE: Link Menu -->

 
          <!-- BEGIN MODULE: Subtitle -->
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            <td style="padding: 0px 0px 0px 0px;">
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               <td valign="top" class="pc-w520-padding-15-30-0-30 pc-w620-padding-15-35-0-35" style="padding: 10px 40px 10px 40px; border-radius: 0px; border-top: 1px dotted #e3e3e3; background-color: #ffffff;" bgcolor="#ffffff">
                <table border="0" cellpadding="0" cellspacing="0" role="presentation" width="100%" style="border-collapse: separate; border-spacing: 0; margin-right: auto; margin-left: auto;">
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                   <div class="pc-font-alt" style="line-height: 133%; letter-spacing: -0.2px; font-family: 'Fira Sans', Arial, Helvetica, sans-serif; font-size: 12px; font-weight: normal;font-style: italic; font-variant-ligatures: normal; color: #707070; text-align: left; text-align-last: left;">
                    <div><span>Cette newsletter présente les dernières avancées AWS couvrant la diffusion vidéo à grande échelle, les capacités multilingues de support assisté par IA, les nouvelles instances optimisées en mémoire, l'amélioration de la résilience Kubernetes, l'automatisation des migrations de bases de données, et les stratégies avancées pour développer et optimiser des applications Generative AI robustes avec Amazon Bedrock.</span>
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          <!-- END MODULE: Subtitle -->

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          <!-- BEGIN MODULE: Content 17 -->
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                     <a name="Media" id="Media"></a>
                      <div class="pc-font-alt" style="line-height: 121%; letter-spacing: -0.2px; font-family: 'Fira Sans', Arial, Helvetica, sans-serif; font-size: 12px; font-weight: 500; font-variant-ligatures: normal; color: #40be65; text-align: left; text-align-last: left;">
                       <div><span>Media, Sport and Video</span>
                       </div>
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                <table width="100%" border="0" cellpadding="0" cellspacing="0" role="presentation">
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                      <a class="pc-font-alt" href="https://aws.amazon.com/blogs/media/tv-2-norway-scales-to-support-20000-live-sports-streams-with-aws/" style="text-decoration: none; line-height: 142%; letter-spacing: -0.4px; font-family: 'Fira Sans', Arial, Helvetica, sans-serif; font-size: 18px; font-weight: bold; font-variant-ligatures: normal; color: #151515; text-align: left; text-align-last: left;">
                       <span>TV 2 Norway évolue pour prendre en charge 20 000 streams sportifs en direct avec AWS</span>
                      </a>
                       </div>
                      </div>
                     </td>
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                  </td>
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                <table border="0" cellpadding="0" cellspacing="0" role="presentation" width="100%" style="border-collapse: separate; border-spacing: 0; margin-right: auto; margin-left: auto;">
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                   <a class="pc-font-alt" href="https://aws.amazon.com/blogs/media/tv-2-norway-scales-to-support-20000-live-sports-streams-with-aws/" style="text-decoration: none; line-height: 156%; letter-spacing: -0.2px; font-family: 'Fira Sans', Arial, Helvetica, sans-serif; font-size: 12px; font-weight: normal; font-variant-ligatures: normal; color: #9b9b9b; text-align: left; text-align-last: left;">
                    <span>TV 2 Norway a construit une plateforme vidéo sur AWS capable de diffuser plus de 20 000 événements sportifs en direct par an grâce à l'automatisation et au scaling des AWS Media Services, permettant de gérer jusqu'à 1 000 diffusions simultanées tout en libérant les équipes des tâches manuelles de routage des signaux.</span>
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                       <div><span>Cloud Operation</span>
                       </div>
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                      <a class="pc-font-alt" href="https://aws.amazon.com/about-aws/whats-new/2026/02/ai-troubleshooting-in-aws-support-center/" style="text-decoration: none; line-height: 142%; letter-spacing: -0.4px; font-family: 'Fira Sans', Arial, Helvetica, sans-serif; font-size: 18px; font-weight: bold; font-variant-ligatures: normal; color: #151515; text-align: left; text-align-last: left;">
                       <span>AI Troubleshooting dans la console AWS Support Center prend désormais en charge 7 langues supplémentaires</span>
                      </a>
                       </div>
                      </div>
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                   <a class="pc-font-alt" href="https://aws.amazon.com/about-aws/whats-new/2026/02/ai-troubleshooting-in-aws-support-center/" style="text-decoration: none; line-height: 156%; letter-spacing: -0.2px; font-family: 'Fira Sans', Arial, Helvetica, sans-serif; font-size: 12px; font-weight: normal; font-variant-ligatures: normal; color: #9b9b9b; text-align: left; text-align-last: left;">
                    <span>La résolution de problèmes par IA dans la console AWS Support Center est désormais disponible en sept langues supplémentaires (japonais, coréen, mandarin simplifié et traditionnel, espagnol, portugais et français), permettant à tous les clients d'accéder à des recommandations contextuelles instantanées dans leur langue préférée lors de la création de cas de support.</span>
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                     <a name="Compute" id="Compute"></a>
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                       <div><span>Compute</span>
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                      <a class="pc-font-alt" href="https://aws.amazon.com/about-aws/whats-new/2026/02/amazon-ec2-r8i-r8i-flex-instances-DUB-region/" style="text-decoration: none; line-height: 142%; letter-spacing: -0.4px; font-family: 'Fira Sans', Arial, Helvetica, sans-serif; font-size: 18px; font-weight: bold; font-variant-ligatures: normal; color: #151515; text-align: left; text-align-last: left;">
                       <span>Les instances Amazon EC2 R8i et R8i-flex sont désormais disponibles dans la région Europe (Irlande)</span>
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                   <a class="pc-font-alt" href="https://aws.amazon.com/about-aws/whats-new/2026/02/amazon-ec2-r8i-r8i-flex-instances-DUB-region/" style="text-decoration: none; line-height: 156%; letter-spacing: -0.2px; font-family: 'Fira Sans', Arial, Helvetica, sans-serif; font-size: 12px; font-weight: normal; font-variant-ligatures: normal; color: #9b9b9b; text-align: left; text-align-last: left;">
                    <span>Les instances Amazon EC2 R8i et R8i-flex, propulsées par des processeurs Intel Xeon 6 personnalisés exclusifs à AWS, sont désormais disponibles dans la région Europe (Irlande) et offrent jusqu'à 15% de meilleure performance-prix, 2,5 fois plus de bande passante mémoire que la génération précédente, et des gains de performance allant jusqu'à 60% pour certains workloads spécifiques comme les applications web NGINX.</span>
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                     <a name="K8s" id="K8s"></a>
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                       <div><span>Container and Kubernetes</span>
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                      <a class="pc-font-alt" href="https://aws.amazon.com/about-aws/whats-new/2026/02/amazon-eks-auto-mode-enhanced-logging" style="text-decoration: none; line-height: 142%; letter-spacing: -0.4px; font-family: 'Fira Sans', Arial, Helvetica, sans-serif; font-size: 18px; font-weight: bold; font-variant-ligatures: normal; color: #151515; text-align: left; text-align-last: left;">
                       <span>Amazon EKS Auto Mode annonce l'amélioration du logging pour ses capacités Kubernetes gérées</span>
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                   <a class="pc-font-alt" href="https://aws.amazon.com/about-aws/whats-new/2026/02/amazon-eks-auto-mode-enhanced-logging" style="text-decoration: none; line-height: 156%; letter-spacing: -0.2px; font-family: 'Fira Sans', Arial, Helvetica, sans-serif; font-size: 12px; font-weight: normal; font-variant-ligatures: normal; color: #9b9b9b; text-align: left; text-align-last: left;">
                    <span>Amazon EKS Auto Mode permet désormais de configurer ses capacités Kubernetes managées comme sources de logs via Amazon CloudWatch Vended Logs, offrant aux clients un monitoring et un dépannage améliorés de leurs clusters avec une livraison sécurisée vers CloudWatch Logs, Amazon S3 ou Amazon Kinesis Data Firehose à prix réduit.</span>
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                       <div><span>Container and Kubernetes</span>
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                      <a class="pc-font-alt" href="https://aws.amazon.com/blogs/containers/enhance-kubernetes-high-availability-with-amazon-application-recovery-controller-and-karpenter-integration/" style="text-decoration: none; line-height: 142%; letter-spacing: -0.4px; font-family: 'Fira Sans', Arial, Helvetica, sans-serif; font-size: 18px; font-weight: bold; font-variant-ligatures: normal; color: #151515; text-align: left; text-align-last: left;">
                       <span>Améliorez la haute disponibilité de Kubernetes avec l'intégration d'Amazon Application Recovery Controller et Karpenter</span>
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                   <a class="pc-font-alt" href="https://aws.amazon.com/blogs/containers/enhance-kubernetes-high-availability-with-amazon-application-recovery-controller-and-karpenter-integration/" style="text-decoration: none; line-height: 156%; letter-spacing: -0.2px; font-family: 'Fira Sans', Arial, Helvetica, sans-serif; font-size: 12px; font-weight: normal; font-variant-ligatures: normal; color: #9b9b9b; text-align: left; text-align-last: left;">
                    <span>Apprenez comment un nouveau contrôleur Kubernetes open source intègre Karpenter avec Amazon Application Recovery Controller pour reconfigurer automatiquement les node pools lors d'un zonal shift, garantissant ainsi que les applications critiques maintiennent leur haute disponibilité en évitant les zones dégradées sans intervention manuelle.</span>
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                     <a name="DB" id="DB"></a>
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                       <div><span>Database</span>
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                      <a class="pc-font-alt" href="https://netflixtechblog.com/automating-rds-postgres-to-aurora-postgres-migration-261ca045447f?source=rss----2615bd06b42e---4" style="text-decoration: none; line-height: 142%; letter-spacing: -0.4px; font-family: 'Fira Sans', Arial, Helvetica, sans-serif; font-size: 18px; font-weight: bold; font-variant-ligatures: normal; color: #151515; text-align: left; text-align-last: left;">
                       <span>Automatisation de la migration de RDS Postgres vers Aurora Postgres</span>
                      </a>
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                   <a class="pc-font-alt" href="https://netflixtechblog.com/automating-rds-postgres-to-aurora-postgres-migration-261ca045447f?source=rss----2615bd06b42e---4" style="text-decoration: none; line-height: 156%; letter-spacing: -0.2px; font-family: 'Fira Sans', Arial, Helvetica, sans-serif; font-size: 12px; font-weight: normal; font-variant-ligatures: normal; color: #9b9b9b; text-align: left; text-align-last: left;">
                    <span>Netflix a automatisé la migration de près de 400 clusters PostgreSQL depuis RDS vers Aurora PostgreSQL en développant un workflow self-service qui gère l'orchestration, la réplication des données, la validation et le basculement avec un temps d'arrêt minimal d'environ 10 minutes, tout en garantissant zéro perte de données grâce à une architecture de Data Access Layer qui permet de rediriger le trafic de manière transparente sans modification des applications clientes.</span>
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                     <a name="DB" id="DB"></a>
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                       <div><span>Database</span>
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                      <a class="pc-font-alt" href="https://www.youtube.com/watch?v=m_AuuhBfHwo" style="text-decoration: none; line-height: 142%; letter-spacing: -0.4px; font-family: 'Fira Sans', Arial, Helvetica, sans-serif; font-size: 18px; font-weight: bold; font-variant-ligatures: normal; color: #151515; text-align: left; text-align-last: left;">
                       <span>Créer un moteur de recommandation IA étape par étape (Graph + Bedrock) | Bases de données pour l'IA</span>
                      </a>
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                   <a class="pc-font-alt" href="https://www.youtube.com/watch?v=m_AuuhBfHwo" style="text-decoration: none; line-height: 156%; letter-spacing: -0.2px; font-family: 'Fira Sans', Arial, Helvetica, sans-serif; font-size: 12px; font-weight: normal; font-variant-ligatures: normal; color: #9b9b9b; text-align: left; text-align-last: left;">
                    <span>Ce tutoriel pratique montre comment construire un moteur de recommandation basé sur l'IA en transformant des données tabulaires en graphe de connaissances interrogeable en langage naturel, en utilisant Neptune, Opensearch et Bedrock sur des données réelles d'avis Yelp.</span>
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                     <a name="DeveloperTools" id="DeveloperTools"></a>
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                       <div><span>Developer Tools</span>
                       </div>
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                      <a class="pc-font-alt" href="https://www.youtube.com/watch?v=u1Lu1DsZNd8" style="text-decoration: none; line-height: 142%; letter-spacing: -0.4px; font-family: 'Fira Sans', Arial, Helvetica, sans-serif; font-size: 18px; font-weight: bold; font-variant-ligatures: normal; color: #151515; text-align: left; text-align-last: left;">
                       <span>Innover avec le cycle de vie de développement piloté par l'IA (AI-DLC)</span>
                      </a>
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                   <a class="pc-font-alt" href="https://www.youtube.com/watch?v=u1Lu1DsZNd8" style="text-decoration: none; line-height: 156%; letter-spacing: -0.2px; font-family: 'Fira Sans', Arial, Helvetica, sans-serif; font-size: 12px; font-weight: normal; font-variant-ligatures: normal; color: #9b9b9b; text-align: left; text-align-last: left;">
                    <span>MJ Zulueta et Tamara Gagliardi explorent avec Titi Ogundeji l'AI-DLC, une approche qui positionne l'IA comme collaborateur central tout au long du cycle de développement logiciel, avec des stratégies d'implémentation pratiques pour démarrer en une journée.</span>
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                     <a name="GenAI" id="GenAI"></a>
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                       <div><span>Generative AI</span>
                       </div>
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                      <a class="pc-font-alt" href="https://www.aboutamazon.com/news/aws/aws-ceo-ai-inference-transforms-developer-capabilities?utm_source=rss" style="text-decoration: none; line-height: 142%; letter-spacing: -0.4px; font-family: 'Fira Sans', Arial, Helvetica, sans-serif; font-size: 18px; font-weight: bold; font-variant-ligatures: normal; color: #151515; text-align: left; text-align-last: left;">
                       <span>Le PDG d'AWS qualifie l'inférence IA de nouveau bloc de construction qui transforme ce que les développeurs peuvent créer</span>
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                   <a class="pc-font-alt" href="https://www.aboutamazon.com/news/aws/aws-ceo-ai-inference-transforms-developer-capabilities?utm_source=rss" style="text-decoration: none; line-height: 156%; letter-spacing: -0.2px; font-family: 'Fira Sans', Arial, Helvetica, sans-serif; font-size: 12px; font-weight: normal; font-variant-ligatures: normal; color: #9b9b9b; text-align: left; text-align-last: left;">
                    <span>Le CEO d'AWS Matt Garman explique comment l'inférence IA devient un nouveau bloc de construction fondamental qui permet aux développeurs de créer des agents accomplissant des tâches complexes, générant des retours sur investissement massifs pour les entreprises dès 2026.</span>
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                     <a name="GenAI" id="GenAI"></a>
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                       <div><span>Generative AI</span>
                       </div>
                      </div>
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                      <a class="pc-font-alt" href="https://aws.amazon.com/blogs/machine-learning/supercharge-regulated-workloads-with-claude-code-and-amazon-bedrock/" style="text-decoration: none; line-height: 142%; letter-spacing: -0.4px; font-family: 'Fira Sans', Arial, Helvetica, sans-serif; font-size: 18px; font-weight: bold; font-variant-ligatures: normal; color: #151515; text-align: left; text-align-last: left;">
                       <span>Boostez les workloads réglementés avec Claude Code et Amazon Bedrock</span>
                      </a>
                       </div>
                      </div>
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                   <a class="pc-font-alt" href="https://aws.amazon.com/blogs/machine-learning/supercharge-regulated-workloads-with-claude-code-and-amazon-bedrock/" style="text-decoration: none; line-height: 156%; letter-spacing: -0.2px; font-family: 'Fira Sans', Arial, Helvetica, sans-serif; font-size: 12px; font-weight: normal; font-variant-ligatures: normal; color: #9b9b9b; text-align: left; text-align-last: left;">
                    <span>Ce blog post explique comment configurer Claude Code avec Amazon Bedrock dans AWS GovCloud (US) pour permettre aux organisations des secteurs réglementés de bénéficier d'un assistant de codage IA tout en maintenant la conformité stricte avec les exigences FedRAMP High, ITAR et Impact Level 4/5.</span>
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                <table width="100%" border="0" cellpadding="0" cellspacing="0" role="presentation">
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                     <a name="GenAI" id="GenAI"></a>
                      <div class="pc-font-alt" style="line-height: 121%; letter-spacing: -0.2px; font-family: 'Fira Sans', Arial, Helvetica, sans-serif; font-size: 12px; font-weight: 500; font-variant-ligatures: normal; color: #40be65; text-align: left; text-align-last: left;">
                       <div><span>Generative AI</span>
                       </div>
                      </div>
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                      <a class="pc-font-alt" href="https://aws.amazon.com/blogs/machine-learning/mastering-amazon-bedrock-throttling-and-service-availability-a-comprehensive-guide/" style="text-decoration: none; line-height: 142%; letter-spacing: -0.4px; font-family: 'Fira Sans', Arial, Helvetica, sans-serif; font-size: 18px; font-weight: bold; font-variant-ligatures: normal; color: #151515; text-align: left; text-align-last: left;">
                       <span>Maîtriser le throttling et la disponibilité du service Amazon Bedrock : Un guide complet</span>
                      </a>
                       </div>
                      </div>
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                   <a class="pc-font-alt" href="https://aws.amazon.com/blogs/machine-learning/mastering-amazon-bedrock-throttling-and-service-availability-a-comprehensive-guide/" style="text-decoration: none; line-height: 156%; letter-spacing: -0.2px; font-family: 'Fira Sans', Arial, Helvetica, sans-serif; font-size: 12px; font-weight: normal; font-variant-ligatures: normal; color: #9b9b9b; text-align: left; text-align-last: left;">
                    <span>Ce guide technique explique comment gérer efficacement les erreurs 429 ThrottlingException et 503 ServiceUnavailableException dans Amazon Bedrock en implémentant des stratégies de retry avec backoff exponentiel, des limiteurs de débit basés sur les tokens, des circuit breakers, du failover cross-Region avec CRIS, et un monitoring CloudWatch complet pour maintenir la résilience et l'expérience utilisateur des applications Generative AI en production.</span>
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                <table width="100%" border="0" cellpadding="0" cellspacing="0" role="presentation">
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                  <td align="left" valign="top" style="padding: 0px 0px 6px 0px;">
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                     <a name="ML" id="ML"></a>
                      <div class="pc-font-alt" style="line-height: 121%; letter-spacing: -0.2px; font-family: 'Fira Sans', Arial, Helvetica, sans-serif; font-size: 12px; font-weight: 500; font-variant-ligatures: normal; color: #40be65; text-align: left; text-align-last: left;">
                       <div><span>Machine Learning</span>
                       </div>
                      </div>
                     </td>
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                      <a class="pc-font-alt" href="https://aws.amazon.com/blogs/machine-learning/evaluating-ai-agents-real-world-lessons-from-building-agentic-systems-at-amazon/" style="text-decoration: none; line-height: 142%; letter-spacing: -0.4px; font-family: 'Fira Sans', Arial, Helvetica, sans-serif; font-size: 18px; font-weight: bold; font-variant-ligatures: normal; color: #151515; text-align: left; text-align-last: left;">
                       <span>Évaluation des agents IA : Leçons concrètes tirées de la construction de systèmes agentiques chez Amazon</span>
                      </a>
                       </div>
                      </div>
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                   <a class="pc-font-alt" href="https://aws.amazon.com/blogs/machine-learning/evaluating-ai-agents-real-world-lessons-from-building-agentic-systems-at-amazon/" style="text-decoration: none; line-height: 156%; letter-spacing: -0.2px; font-family: 'Fira Sans', Arial, Helvetica, sans-serif; font-size: 12px; font-weight: normal; font-variant-ligatures: normal; color: #9b9b9b; text-align: left; text-align-last: left;">
                    <span>Amazon partage son framework d'évaluation complet pour les systèmes d'agents IA, développé à partir de milliers d'implémentations internes, qui combine un workflow d'évaluation automatisé avec une bibliothèque de métriques couvrant la qualité des réponses, l'utilisation des outils, le raisonnement multi-étapes et la complétion des tâches, tout en intégrant des processus human-in-the-loop pour garantir des performances fiables dans des environnements de production à grande échelle.</span>
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                <table width="100%" border="0" cellpadding="0" cellspacing="0" role="presentation">
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                     <a name="ML" id="ML"></a>
                      <div class="pc-font-alt" style="line-height: 121%; letter-spacing: -0.2px; font-family: 'Fira Sans', Arial, Helvetica, sans-serif; font-size: 12px; font-weight: 500; font-variant-ligatures: normal; color: #40be65; text-align: left; text-align-last: left;">
                       <div><span>Machine Learning</span>
                       </div>
                      </div>
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                      <a class="pc-font-alt" href="https://aws.amazon.com/blogs/machine-learning/automated-reasoning-checks-rewriting-chatbot-reference-implementation/" style="text-decoration: none; line-height: 142%; letter-spacing: -0.4px; font-family: 'Fira Sans', Arial, Helvetica, sans-serif; font-size: 18px; font-weight: bold; font-variant-ligatures: normal; color: #151515; text-align: left; text-align-last: left;">
                       <span>Implémentation de référence de réécriture de chatbot avec vérifications Automated Reasoning</span>
                      </a>
                       </div>
                      </div>
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                   <a class="pc-font-alt" href="https://aws.amazon.com/blogs/machine-learning/automated-reasoning-checks-rewriting-chatbot-reference-implementation/" style="text-decoration: none; line-height: 156%; letter-spacing: -0.2px; font-family: 'Fira Sans', Arial, Helvetica, sans-serif; font-size: 12px; font-weight: normal; font-variant-ligatures: normal; color: #9b9b9b; text-align: left; text-align-last: left;">
                    <span>AWS publie un chatbot open source de référence qui utilise les vérifications Automated Reasoning pour itérer sur le contenu généré, poser des questions de clarification et prouver mathématiquement la validité des réponses, tout en produisant un log d'audit avec des explications vérifiables et une interface utilisateur qui expose le processus de réécriture itératif.</span>
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                <table width="100%" border="0" cellpadding="0" cellspacing="0" role="presentation">
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                  <td align="left" valign="top" style="padding: 0px 0px 6px 0px;">
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                     <a name="ML" id="ML"></a>
                      <div class="pc-font-alt" style="line-height: 121%; letter-spacing: -0.2px; font-family: 'Fira Sans', Arial, Helvetica, sans-serif; font-size: 12px; font-weight: 500; font-variant-ligatures: normal; color: #40be65; text-align: left; text-align-last: left;">
                       <div><span>Machine Learning</span>
                       </div>
                      </div>
                     </td>
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                      <a class="pc-font-alt" href="https://aws.amazon.com/blogs/machine-learning/agent-to-agent-collaboration-using-amazon-nova-2-lite-and-amazon-nova-act-for-multi-agent-systems/" style="text-decoration: none; line-height: 142%; letter-spacing: -0.4px; font-family: 'Fira Sans', Arial, Helvetica, sans-serif; font-size: 18px; font-weight: bold; font-variant-ligatures: normal; color: #151515; text-align: left; text-align-last: left;">
                       <span>Collaboration agent-à-agent : Utilisation d'Amazon Nova 2 Lite et Amazon Nova Act pour les systèmes multi-agents</span>
                      </a>
                       </div>
                      </div>
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                   <a class="pc-font-alt" href="https://aws.amazon.com/blogs/machine-learning/agent-to-agent-collaboration-using-amazon-nova-2-lite-and-amazon-nova-act-for-multi-agent-systems/" style="text-decoration: none; line-height: 156%; letter-spacing: -0.2px; font-family: 'Fira Sans', Arial, Helvetica, sans-serif; font-size: 12px; font-weight: normal; font-variant-ligatures: normal; color: #9b9b9b; text-align: left; text-align-last: left;">
                    <span>Ce blog post explique comment construire un système multi-agents efficace en utilisant Amazon Nova 2 Lite pour la planification et Amazon Nova Act pour l'interaction avec les navigateurs, en remplaçant un agent unique surchargé par trois agents spécialisés qui communiquent via des messages structurés pour gérer la recherche de vols, d'hôtels et l'orchestration globale d'un planificateur de voyage.</span>
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                <table width="100%" border="0" cellpadding="0" cellspacing="0" role="presentation">
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                  <td align="left" valign="top" style="padding: 0px 0px 6px 0px;">
                   <table border="0" cellpadding="0" cellspacing="0" role="presentation" width="100%" style="border-collapse: separate; border-spacing: 0; margin-right: auto; margin-left: auto;">
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                     <a name="ML" id="ML"></a>
                      <div class="pc-font-alt" style="line-height: 121%; letter-spacing: -0.2px; font-family: 'Fira Sans', Arial, Helvetica, sans-serif; font-size: 12px; font-weight: 500; font-variant-ligatures: normal; color: #40be65; text-align: left; text-align-last: left;">
                       <div><span>Machine Learning</span>
                       </div>
                      </div>
                     </td>
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                      <a class="pc-font-alt" href="https://aws.amazon.com/blogs/machine-learning/scale-llm-fine-tuning-with-hugging-face-and-amazon-sagemaker-ai/" style="text-decoration: none; line-height: 142%; letter-spacing: -0.4px; font-family: 'Fira Sans', Arial, Helvetica, sans-serif; font-size: 18px; font-weight: bold; font-variant-ligatures: normal; color: #151515; text-align: left; text-align-last: left;">
                       <span>Effectuez le scaling du fine-tuning de LLM avec Hugging Face et Amazon SageMaker AI</span>
                      </a>
                       </div>
                      </div>
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                   <a class="pc-font-alt" href="https://aws.amazon.com/blogs/machine-learning/scale-llm-fine-tuning-with-hugging-face-and-amazon-sagemaker-ai/" style="text-decoration: none; line-height: 156%; letter-spacing: -0.2px; font-family: 'Fira Sans', Arial, Helvetica, sans-serif; font-size: 12px; font-weight: normal; font-variant-ligatures: normal; color: #9b9b9b; text-align: left; text-align-last: left;">
                    <span>Ce blog post explique comment les entreprises peuvent optimiser le fine-tuning de modèles de langage de grande taille en combinant la bibliothèque Hugging Face Transformers avec Amazon SageMaker AI Training Jobs, en utilisant des techniques avancées comme FSDP et LoRA pour réduire les coûts et le temps d'entraînement tout en maintenant la qualité des modèles, illustré par un exemple pratique avec le modèle meta-llama/Llama-3.1-8B sur le dataset MedReason.</span>
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                <table width="100%" border="0" cellpadding="0" cellspacing="0" role="presentation">
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                  <td align="left" valign="top" style="padding: 0px 0px 6px 0px;">
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                     <a name="ML" id="ML"></a>
                      <div class="pc-font-alt" style="line-height: 121%; letter-spacing: -0.2px; font-family: 'Fira Sans', Arial, Helvetica, sans-serif; font-size: 12px; font-weight: 500; font-variant-ligatures: normal; color: #40be65; text-align: left; text-align-last: left;">
                       <div><span>Machine Learning</span>
                       </div>
                      </div>
                     </td>
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                      <a class="pc-font-alt" href="https://aws.amazon.com/about-aws/whats-new/2026/02/bedrock-agentcore-browser-proxy" style="text-decoration: none; line-height: 142%; letter-spacing: -0.4px; font-family: 'Fira Sans', Arial, Helvetica, sans-serif; font-size: 18px; font-weight: bold; font-variant-ligatures: normal; color: #151515; text-align: left; text-align-last: left;">
                       <span>Amazon Bedrock AgentCore Browser prend désormais en charge la configuration proxy</span>
                      </a>
                       </div>
                      </div>
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                   <a class="pc-font-alt" href="https://aws.amazon.com/about-aws/whats-new/2026/02/bedrock-agentcore-browser-proxy" style="text-decoration: none; line-height: 156%; letter-spacing: -0.2px; font-family: 'Fira Sans', Arial, Helvetica, sans-serif; font-size: 12px; font-weight: normal; font-variant-ligatures: normal; color: #9b9b9b; text-align: left; text-align-last: left;">
                    <span>Amazon Bedrock AgentCore Browser permet désormais aux organisations de configurer leurs propres proxies pour router les sessions de navigation à travers leur infrastructure, facilitant l'accès au contenu géo-restreint, la conformité réglementaire et l'application des politiques de sécurité dans quatorze régions AWS.</span>
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                     <a name="ML" id="ML"></a>
                      <div class="pc-font-alt" style="line-height: 121%; letter-spacing: -0.2px; font-family: 'Fira Sans', Arial, Helvetica, sans-serif; font-size: 12px; font-weight: 500; font-variant-ligatures: normal; color: #40be65; text-align: left; text-align-last: left;">
                       <div><span>Machine Learning</span>
                       </div>
                      </div>
                     </td>
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                      <a class="pc-font-alt" href="https://aws.amazon.com/about-aws/whats-new/2026/02/amazon-bedrock-reinforcement-fine-tuning-openai" style="text-decoration: none; line-height: 142%; letter-spacing: -0.4px; font-family: 'Fira Sans', Arial, Helvetica, sans-serif; font-size: 18px; font-weight: bold; font-variant-ligatures: normal; color: #151515; text-align: left; text-align-last: left;">
                       <span>Le fine-tuning par renforcement d'Amazon Bedrock ajoute la prise en charge des modèles open-weight avec des APIs compatibles OpenAI</span>
                      </a>
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                   <a class="pc-font-alt" href="https://aws.amazon.com/about-aws/whats-new/2026/02/amazon-bedrock-reinforcement-fine-tuning-openai" style="text-decoration: none; line-height: 156%; letter-spacing: -0.2px; font-family: 'Fira Sans', Arial, Helvetica, sans-serif; font-size: 12px; font-weight: normal; font-variant-ligatures: normal; color: #9b9b9b; text-align: left; text-align-last: left;">
                    <span>Amazon Bedrock étend le reinforcement fine-tuning aux modèles open-weight populaires comme OpenAI GPT-OSS et Qwen avec des APIs compatibles OpenAI, permettant aux développeurs d'améliorer la précision des modèles sans expertise approfondie en machine learning ni grands volumes de données étiquetées grâce à un workflow de personnalisation entièrement automatisé et géré.</span>
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                       <div><span>Machine Learning</span>
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                      <a class="pc-font-alt" href="https://www.youtube.com/watch?v=i0h7xA8cqYs" style="text-decoration: none; line-height: 142%; letter-spacing: -0.4px; font-family: 'Fira Sans', Arial, Helvetica, sans-serif; font-size: 18px; font-weight: bold; font-variant-ligatures: normal; color: #151515; text-align: left; text-align-last: left;">
                       <span>Série d'approfondissement Amazon Bedrock AgentCore : Évaluations AgentCore | AWS Show and Tell</span>
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                   <a class="pc-font-alt" href="https://www.youtube.com/watch?v=i0h7xA8cqYs" style="text-decoration: none; line-height: 156%; letter-spacing: -0.2px; font-family: 'Fira Sans', Arial, Helvetica, sans-serif; font-size: 12px; font-weight: normal; font-variant-ligatures: normal; color: #9b9b9b; text-align: left; text-align-last: left;">
                    <span>Cet épisode de "AWS Show and Tell" explore en profondeur Amazon Bedrock AgentCore Evaluations, en couvrant les fondamentaux de l'évaluation d'agents non déterministes, le monitoring continu en production, et l'amélioration des performances à travers une démonstration pratique d'analyse au niveau des sessions, traces et outils.</span>
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                       <div><span>Network</span>
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                      <a class="pc-font-alt" href="https://www.aboutamazon.com/news/amazon-leo/amazon-leo-arianespace-first-mission-satellites?utm_source=rss" style="text-decoration: none; line-height: 142%; letter-spacing: -0.4px; font-family: 'Fira Sans', Arial, Helvetica, sans-serif; font-size: 18px; font-weight: bold; font-variant-ligatures: normal; color: #151515; text-align: left; text-align-last: left;">
                       <span>Amazon Leo se prépare pour sa première mission de lancement lourd de 2026 avec Arianespace</span>
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                   <a class="pc-font-alt" href="https://www.aboutamazon.com/news/amazon-leo/amazon-leo-arianespace-first-mission-satellites?utm_source=rss" style="text-decoration: none; line-height: 156%; letter-spacing: -0.2px; font-family: 'Fira Sans', Arial, Helvetica, sans-serif; font-size: 12px; font-weight: normal; font-variant-ligatures: normal; color: #9b9b9b; text-align: left; text-align-last: left;">
                    <span>Amazon s'apprête à lancer 32 satellites Leo supplémentaires lors de sa première mission avec Arianespace en 2026, utilisant la fusée Ariane 64 pour étendre sa constellation.</span>
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                       <div><span>Network</span>
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                      <a class="pc-font-alt" href="https://aws.amazon.com/blogs/networking-and-content-delivery/part-2-implementing-dynamic-origin-modification-in-amazon-cloudfront/" style="text-decoration: none; line-height: 142%; letter-spacing: -0.4px; font-family: 'Fira Sans', Arial, Helvetica, sans-serif; font-size: 18px; font-weight: bold; font-variant-ligatures: normal; color: #151515; text-align: left; text-align-last: left;">
                       <span>Implémentation de la modification dynamique d'origine dans Amazon CloudFront – Partie 2</span>
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                   <a class="pc-font-alt" href="https://aws.amazon.com/blogs/networking-and-content-delivery/part-2-implementing-dynamic-origin-modification-in-amazon-cloudfront/" style="text-decoration: none; line-height: 156%; letter-spacing: -0.2px; font-family: 'Fira Sans', Arial, Helvetica, sans-serif; font-size: 12px; font-weight: normal; font-variant-ligatures: normal; color: #9b9b9b; text-align: left; text-align-last: left;">
                    <span>Ce guide technique détaille l'implémentation de la modification dynamique d'origine dans Amazon CloudFront en utilisant CloudFront Functions avec KeyValueStore pour le routage basé sur des paramètres de requête, et Lambda@Edge avec Amazon DynamoDB pour des scénarios multi-locataires nécessitant l'accès au corps de la requête, incluant des exemples de code complets et des instructions de configuration étape par étape.</span>
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