Auch in zweiter Instanz hat Amazon verloren. Die Preiserhöhung für das Prime-Abo vor drei Jahren war unwirksam. Eine Sammelklage ist geplant. (Amazon Prime, Amazon)
Quelle: Golem
Apple steigert seinen Umsatz und Gewinn deutlich, obwohl das China-Geschäft zurückgeht. Für das Weihnachtsquartal erwartet der Konzern neue Rekorde. (Apple, iPhone)
Quelle: Golem
Ein Manager hat durch den Handel mit Exploit-Komponenten etwa 1,3 Millionen US-Dollar eingenommen. Der Schaden bei L3Harris ist jedoch weitaus größer. (Security, Virus)
Quelle: Golem
AMD versichert, dass Windows 10 allerdings weiterhin vollständig unterstützt werde. Schließlich gibt es weiterhin Sicherheitspatches. (Windows 10, AMD)
Quelle: Golem
Einige Apps für Fire TV ermöglichen den Zugriff auf urheberrechtlich geschützte Inhalte. Diesen schiebt Amazon nun einen Riegel vor. (Fire TV, Amazon)
Quelle: Golem
Docker’s impact on agentic AI, security, developer productivity, costs, ROI.
An independent study by theCUBE Research.
To investigate Docker’s impact on developer productivity, software supply chain security, agentic AI development, cost savings, and ROI, theCUBE Research asked nearly 400 enterprise IT & AppDev leaders from medium to large global enterprises. The industry context is that enterprise developers face mounting pressure to rapidly ship features, build agentic AI applications, and maintain security. All while navigating a fragmented array of development tools and open source code that require engineering cycles and introduce security risks. Docker transformed software development through containers and DevSecOps workflows, and is now doing the same for agentic AI development and software supply chain security. theCUBE Research quantified Docker’s impact: teams build agentic AI apps faster, achieve near-zero CVEs, remediate vulnerabilities before exploits, ship modern cloud-native applications, save developer hours, and generate financial returns.
Keep reading to get key highlights and analysis. Download theCube Research report and ebook to take a deep dive.
Agentic AI development streamlined using familiar technologies
Developers can build, run, and share agents and compose agentic systems using familiar Docker container workflows. To do this, developers would build agents safely using Docker MCP Gateway Catalog and Toolkit; run agents securely with Docker Sandboxes; and run models with Docker Model Runner. These capabilities align with theCUBE Research findings that 87% of organizations reduced AI setup time by over 25% and 80% report accelerating AI time-to-market by at least 26%. Using Docker’s modern and secure software delivery practices, development teams can implement AI feature experiments faster and in days test agentic AI capabilities that previously took months. Nearly 78% of developers experienced significant improvement in the standardization and streamlining of AI development workflows, enabling better testing and validation of AI models. Docker helps enterprises generate business advantages through deploying new customer experiences that leverage agentic AI applications. This is phenomenal, given the nascent stage of agentic AI development in enterprises.
Software supply chain security and innovation can move in lockstep
Security engineering and vulnerability remediation can slow development to a crawl. Furthermore, checkpoints or controls may be applied too late in the software development cycle, or after dangerous exploits, creating compounded friction between security teams seeking to prevent vulnerability exploits and developers seeking to rapidly ship features. Docker embeds security directly into development workflows through vulnerability analysis and continuously-patched certified container images. theCUBE Research analysis supports these Docker security capabilities: 79% of organizations find Docker extremely or very effective at maintaining security & compliance, while 95% of respondents reported that Docker improved their ability to identify and remediate vulnerabilities. By making it very simple for developers to use secure images as a default, Docker enables engineering teams to plan, build, and deploy securely without sacrificing feature velocity or creating deployment bottlenecks. Security and innovation can move in lockstep because Docker concurrently secures software supply chains and eliminates vulnerabilities.
Developer productivity becomes a competitive advantage
Consistent container environments eliminate friction, accelerate software delivery cycles, and enable teams to focus on building features rather than overcoming infrastructure challenges. When developers spend less time on environment setup and troubleshooting, they ship more features. Application features that previously took months now reach customers in weeks. The research demonstrates Docker’s ability to increase developer productivity. 72% of organizations reported significant productivity gains in development workflows, while 75% have transformed or adopted DevOps practices when using Docker. Furthermore, when it comes to AI and supply chain security, the findings mentioned above further support how Docker unlocks developer productivity.
Financial returns exceed expectations
CFOs demand quantifiable returns for technology investments, and Docker delivers them. 95% of organizations reported substantial annual savings, with 28% saving more than $250,000 and another 43% reporting $50,000-$250,000 in cost reductions from infrastructure efficiency, reduced rework, and faster time-to-market. The ROI story is equally compelling: 69% of organizations report ROI exceeding 101%, with 28% achieving ROI above 201%. When factoring in faster feature delivery, improved developer satisfaction, and reduced security incidents, the business case for Docker becomes even more tangible. The direct costs of a security breach can surpass $500 million, so mitigating even a fraction of this cost may provide enough financial justification for enterprises to deploy Docker to every developer.
Modernization and cloud native apps remain top of mind
For enterprises who maintain extensive legacy systems, Docker serves as a proven catalyst for cloud-native transformation at scale. Results show that nearly nine in ten (88%) of organizations report Docker has enabled modernization of at least 10% of their applications, with half achieving modernization across 31-60% of workloads and another 20% modernizing over 60%. Docker accelerates the shift from monolithic architectures to modern containerized cloud-native environments while also delivering substantial business value. For example, 37% of organizations report 26% to >50% faster product time-to-market, and 72% report annual cost savings ranging from $50,000 to over $1 million.
Learn more about Docker’s impact on enterprise software development
Docker has evolved from a containerization suite into a development platform for testing, building, securing, and deploying modern software, including agentic AI applications. Docker enables enterprises to apply proven containerization and DevSecOps practices to agentic AI development and software supply chain security.
Download (below) the full report and the ebook from theCUBE Research analysis to learn Docker’s impact on developer productivity, software supply chain security, agentic AI application development, CI/CD and DevSecOps, modernization, cost savings, and ROI. Learn how enterprises leverage Docker to transform application development and win in markets where speed and innovation determine success.
theCUBE Research economic validation of Docker’s development platform
> Download the Report
> Download the eBook
Quelle: https://blog.docker.com/feed/
Amazon Elastic Container Service (Amazon ECS) Service Connect now supports Envoy access logs, providing deeper observability into request-level traffic patterns and service interactions. This new capability captures detailed per-request telemetry for end-to-end tracing, debugging, and compliance monitoring. Amazon ECS Service Connect makes it simple to build secure, resilient service-to-service communication across clusters, VPCs, and AWS accounts. It integrates service discovery and service mesh capabilities by automatically injecting AWS-managed Envoy proxies as sidecars that handle traffic routing, load balancing, and inter-service connectivity. Envoy Access logs capture detailed traffic metadata enabling request-level visibility into service communication patterns. This enables you to perform network diagnostics, troubleshoot issues efficiently, and maintain audit trails for compliance requirements. You can now configure access logs within ECS Service Connect by updating the ServiceConnectConfiguration to enable access logging. Query strings are redacted by default to protect sensitive data. Envoy access logs will output to the standard output (STDOUT) stream alongside application logs and flow through the existing ECS log pipeline without requiring additional infrastructure. This configuration supports all existing application protocols (HTTP, HTTP2, GRPC and TCP). This feature is available in all regions where Amazon ECS Service Connect is supported. To learn more, visit the Amazon ECS Developer Guide.
Quelle: aws.amazon.com
AWS Elastic Beanstalk now enables customers to build and deploy Java applications using Amazon Corretto 25 on Amazon Linux 2023 (AL2023) platform. This latest platform support allows developers to leverage the newest Java 25 features while benefiting from AL2023’s enhanced security and performance capabilities. AWS Elastic Beanstalk is a service that provides the ability to deploy and manage applications in AWS without worrying about the infrastructure that runs those applications. Corretto 25 on AL2023 allows developers to take advantage of the latest Java language features including compact object headers, ahead-of-time (AOT) caching, and structured concurrency. Developers can create Elastic Beanstalk environments running Corretto 25 through the Elastic Beanstalk Console, CLI, or API. This platform is generally available in commercial regions where Elastic Beanstalk is available including the AWS GovCloud (US) Regions. For a complete list of regions and service offerings, see AWS Regions. For more information about Corretto 25 and Linux Platforms, see the Elastic Beanstalk developer guide. To learn more about Elastic Beanstalk, visit the Elastic Beanstalk product page.
Quelle: aws.amazon.com
AWS announces the general availability of the Amazon Elastic Compute Cloud (EC2) Capacity Reservation Topology API. It joins the Instance Topology API in enabling customers to efficiently manage capacity, schedule jobs, and rank nodes for Artificial Intelligence, Machine Learning, and High-Performance Computing distributed workloads. The Capacity Reservation Topology API gives customers a unique per-account hierarchical view of the relative location of their capacity reservations.
Customers running distributed parallel workloads are managing thousands of instances across tens to hundreds of capacity reservations. With the Capacity Reservation Topology API, customers can describe the topology of their reservations as a network node set, which will show the relative proximity of their capacity without the need to launch an instance. This enables efficient capacity planning and management as customers provision workloads on tightly coupled capacity. Customers can then use the Instance Topology API, which provides consistent network nodes from the Capacity Reservation Topology API with further granularity, enabling a consistent and seamless way to schedule jobs and rank nodes for optimal performance in distributed parallel workloads.
The Capacity Reservation Topology API is available in the following AWS regions: US East (N. Virginia), US East (Ohio), US West (N. California), US West (Oregon), Africa (Cape Town), Asia Pacific (Jakarta), Asia Pacific (Hong Kong), Asia Pacific (Hyderabad), Asia Pacific (Melbourne), Asia Pacific (Mumbai), Asia Pacific (Osaka), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Canada (Central), Europe (Frankfurt), Europe (Ireland), Europe (London), Europe (Paris), Europe (Spain), Europe (Stockholm), Europe (Zurich), Middle East (Bahrain), Middle East (UAE), and South America (São Paulo), and it is supported on all instances available with the Instance Topology API.
To learn more, please visit the latest EC2 user guide.
Quelle: aws.amazon.com
Amazon Elastic Container Service (Amazon ECS) announces support for linear and canary deployment strategies, giving you more flexibility and control when deploying containerized applications. These new strategies complement ECS built-in blue/green deployments, enabling you to choose the traffic shifting approach that best matches your application’s risk profile and validation requirements.
With linear deployments, you can gradually shift traffic from your current service revision to the new revision in equal percentage increments over a specified time period. You configure the step percentage (for example, 10%) to control how much traffic shifts at each increment, and set a step bake time to wait between each traffic shift for monitoring and validation. This allows you to validate your new application version at multiple stages with increasing amounts of production traffic. With canary deployments, you can route a small percentage of production traffic to your new service revision while the majority of traffic remains on the current stable version. You set a canary bake time to monitor the new revision’s performance, after which Amazon ECS shifts the remaining traffic to the new revision. Both strategies support a deployment bake time that waits after all production traffic has shifted to the new revision before terminating the old revision, enabling quick rollback without downtime if issues are detected. You can configure deployment lifecycle hooks to perform custom validation steps, and use Amazon CloudWatch alarms to automatically detect failures and trigger rollbacks.
The feature is available in all commercial AWS Regions where Amazon ECS is available. You can use linear and canary deployment strategies for new and existing Amazon ECS services that use Application Load Balancer (ALB) or ECS Service Connect, using the Console, SDK, CLI, CloudFormation, CDK, and Terraform. To learn more, see our documentation on Amazon ECS linear deployments and Amazon ECS canary deployments.
Quelle: aws.amazon.com
