AWS Elemental MediaConnect unterstützt jetzt den Anrufermodus von Secure Reliable Transport (SRT) für sowohl Quellen- als auch Ausgangsverbindungen in MediaConnect-Flows. Der SRT-Anrufermodus bietet mehr Flexibilität bei der Konfiguration von Videotransport-Workflows mit MediaConnect.
Quelle: aws.amazon.com
Die automatische Modelloptimierung von Amazon SageMaker ermöglicht es Ihnen, die genaueste Version Ihres Machine-Learning-Modells zu finden, indem der optimale Satz von Hyperparameterkonfigurationen für Ihren Datensatz ermittelt wird. Die automatische Modelloptimierung von SageMaker ist jetzt in die SageMaker Search-API integriert, mit der Sie schnell die relevantesten Modellanpassungs-Jobs aus möglicherweise Hunderten oder Tausenden von Jobs finden und bewerten können.
Quelle: aws.amazon.com
Amazon Polly ist ein Service, der Text in natürliche Sprache konvertiert. Wir freuen uns, heute die allgemeine Verfügbarkeit von Hiujin, Amazon Pollys erster neuronaler Text-zu-Sprache-Stimme in Kantonesisch bekanntgeben zu dürfen.
Quelle: aws.amazon.com
Vor 40 Jahren starb Philip K. Dick. Das Vermächtnis des visionären Science-Fiction-Autors lebt mit vielen Filmen und Serien fort. Von Peter Osteried (Science-Fiction, Blade Runner)
Quelle: Golem
Die TU München baut eine Hyperloop-Teststrecke in Ottobrunn/Taufkirchen. Der erste Spatenstich erfolgte durch Markus Söder. (Hyperloop, Elon Musk)
Quelle: Golem
Data is critical for any organization to build and operationalize a comprehensive analytics strategy. For example, each transaction in the BFSI (Banking, Finance, Services, and Insurance) sector produces data. In Manufacturing, sensor data can be vast and heterogeneous. Most organizations maintain many different systems, and each organization has unique rules and processes for handling the data contained within those systems.Google Cloud provides end-to-end data cloud solutions to store, manage, process, and activate data starting with BigQuery. BigQuery is a fully managed data warehouse that is designed for running analytical processing (OLAP) at any scale. BigQuery has built-in features like machine learning, geospatial analysis, data sharing, log analytics, and business intelligence. MongoDB is a document-based database that handles the real-time operational application with thousands of concurrent sessions with millisecond response times. Often, curated subsets of data from MongoDB are replicated to BigQuery for aggregation and complex analytics and to further enrich the operational data and end-customer experience. As you can see, MongoDB Atlas and Google Cloud BigQuery are complementary technologies. Introduction to Google Cloud DataflowDataflow is a truly unified stream and batch data processing system that’s serverless, fast, and cost-effective. Dataflow allows teams to focus on programming instead of managing server clusters as Dataflow’s serverless approach removes operational overhead from data engineering workloads. Dataflow is very efficient at implementing streaming transformations, which makes it a great fit for moving data from one platform to another with any changes in the data model required. As part of Data Movement with Dataflow, you can also implement additional use cases such as identifying fraudulent transactions, real-time recommendations, etc.Announcing new Dataflow Templates for MongoDB Atlas and BigQueryCustomers have been using Dataflow widely to move and transform data from Atlas to BigQuery and vice versa. For this, they have been writing custom code using Apache Beamlibraries and deploying it on the Dataflow runtime. To make moving and transforming data between Atlas and BigQuery easier, the MongoDB and Google teams worked together to build templates for the same and make them available as part of the Dataflow page in the Google Cloud console. Dataflow templates allow you to package a Dataflow pipeline for deployment. Templates have several advantages over directly deploying a pipeline to Dataflow. The Dataflow templates and the Dataflow page make it easier to define the source, target, transformations, and other logic to apply to the data. You can key in all the connection parameters through the Dataflow page, and with a click, the Dataflow job is triggered to move the data. To start with, we have built three templates. Two of these templates are batch templates to read and write from MongoDB to BigQuery and vice versa. And the third is to read the change stream data pushed on Pub/Sub and write to BigQuery. Below are the templates for interacting with MongoDB and Google Cloud native services currently available:1. MongoDB to BigQuery template:The MongoDB to BigQuery template is a batch pipeline that reads documents from MongoDB and writes them to BigQuery2. BigQuery to MongoDB template:The BigQuery to MongoDB template can be used to read the tables from BigQuery and write to MongoDB.3. MongoDB to BigQuery CDC template:The MongoDB to BigQuery CDC (Change Data Capture) template is a streaming pipeline that works together with MongoDB change streams. The pipeline reads the JSON records pushed to Pub/Sub via a MongoDB change stream and writes them to BigQueryThe Dataflow page in the Google Cloud console can help accelerate job creation. This eliminates the requirement to set up a java environment and other additional dependencies. Users can instantly create a job by passing parameters including URI, database name, collection name, and BigQuery table name through the UI.Below you can see these new MongoDB templates currently available in the Dataflow page:Below is the parameter configuration screen for the MongoDB to BigQuery (Batch) template. The required parameters vary based on the template you select.Getting startedRefer to the Google provided Dataflow templates documentation page for more information on these templates. If you have any questions, feel free to contact us or engage with the Google Cloud Community Forum.ReferenceApache beam I/O connectorsAcknowledgement: We thank the many Google Cloud and MongoDB team members who contributed to this collaboration, and review, led by Paresh Saraf from MongoDB and Maruti C from Google Cloud.Related ArticleSimplify data processing and data science jobs with Serverless Spark, now available on Google CloudSpark on Google Cloud, Serverless and Integrated for Data Science and ETL jobs.Read Article
Quelle: Google Cloud Platform
Welcome to September’s Cloud CISO Perspectives. This month, we’re focusing on Google Cloud’s acquisition of Mandiant and what it means for us and the broader cybersecurity community. Mandiant has long been recognized as a leader in dynamic cyber defense, threat intelligence, and incident response services. As I explain below, integrating their technology and intelligence with Google Cloud’s will help improve our ability to stop threats and to modernize the overall state of security operations faster than ever before. As with all Cloud CISO Perspectives, the contents of this newsletter will continue to be posted to the Google Cloud blog. If you’re reading this on the website and you’d like to receive the email version, you can subscribe here.Why Mandiant mattersCybersecurity is moving through a tumultuous period of growth, change, and modernization as small organizations, global enterprises, and entire industries move to the cloud. Their digital transformations are an opportunity to do security better and more efficiently than before. At Google Cloud, we believe that our industry should evolve beyond defense strategies and incident response techniques that, in some cases, predate the wide availability of broadband Internet. Our acquisition of Mandiant only underscores how important this belief is to how we work with our customers, putting their security first. Mandiant has been a leader in incident response and threat intelligence for well over a decade. In my experience, they’ve been at the forefront in dealing with all major developments of threats, threat actors, and landmark events in the industry. We have no intention of changing this – their expertise and capabilities will be even more amplified within Google Cloud. In fact, we see this as a terrific opportunity to combine what we’re both good at when it comes to security operations. Google Cloud already has excellent SIEM and SOAR capabilities with Chronicle and Siemplify. With Mandiant, we’re able to provide more threat intelligence and incident response capabilities than ever before. At the end of the day, this is a natural and complementary combination of products and services.We hope to lead the industry towards a democratization of security operations that focuses on “workflows, personnel, and underlying technologies to achieve an autonomic state of existence,” as Google Cloud CEO Thomas Kurian said. And as Mandiant CEO and founder Kevin Mandia wrote, protecting good people from bad is what this is all about. “We can help organizations find and validate potential security issues before they become an incident,” he said.Mandiant also embraces our shared fate vision, where we are actively involved in the outcomes of our customers. We want to work with customers where they are, and help them achieve better outcomes at every phase of their security lifecycle. From building secure infrastructure, to understanding and defending against new threats, to reacting to security incidents, we want to be there for our customers – and so does Mandiant.Mandiant is the largest acquisition ever at Google Cloud, and the second-largest in Google history. As cybercriminals continue to exploit new and old vulnerabilities — see last month’s column for more on that — bringing Mandiant on as part of Google Cloud only underscores how important effective cybersecurity has become. Coming in October: Google Cloud Next and Mandiant MwiseOur big annual user conference Google Cloud Next ‘22 is just around the corner, and it’s going to be an incredible three days of news, conversations, and hopefully more than a little inspiration. For current cloud customers and those among you who are cloud-curious, security is a foundational element in everything we do at Google Cloud and will be ever-present at Next.From October 11 – 13, you’ll be able to dive into the latest cloud tech innovations, hear from Google experts and leaders, learn what your peers are up to, and even try new skills out in the lab sessions. You can read more about the sessions for further details, and sign up here. The following week, Mandiant hosts its inaugural mWISE conference from October 18 – 20. This vendor-neutral conference is a must for SecOps leaders and security analysts, which will bring together cybersecurity leaders to transform knowledge into collective action in the fight against persistent and evolving cyber threats. You can read more about the sessions for further details, and sign up here. Google Cybersecurity Action Team highlightsHere are the latest updates, products, services and resources from our security teams this month: SecurityBest Kept Security Secrets: Organization Policy Service: Our Organization Policy Service is a highly-configurable set of platform guardrails for security teams to set broad yet unbendable limits for engineers before they start working. Learn more. Custom Organization Policy comes to GKE: Sometimes, predefined policies aren’t an exact fit for what an organization wants to accomplish. Now in Preview, the Custom Organization Policy for GKE can define and tailor policies to their organization’s unique needs. Read more.What makes our security special: Our reflections 1 year after joining OCISO: Google Cloud’s Office of the CISO Taylor Lehmann and David Stone reflect on their first year helping customers be more secure at Google Cloud. Read more.How to use Google Cloud to find and protect PII: Google Professional Services has developed a solution using Google Cloud Data Loss Prevention to inspect and classify sensitive data, and then apply these insights to automatically tag and protect data in BigQuery tables. Read more.Introducing Workforce Identity Federation, a new way to manage Google Cloud access: This new Google Cloud Identity and Access Management (IAM) feature can rapidly onboard workforce user identities from external identity providers and provide direct secure access to Google Cloud services and resources. Learn more.Three new features come to Google Cloud Firewall: Firewalls provide one of the basic building blocks for a secure cloud infrastructure, and three new features are now generally available: Global Network Firewall Policies, Regional Network Firewall Policies, and IAM-governed Tags. Here’s what they do. New ways BeyondCorp Enterprise can protect corporate applications: Following our announcement with Jamf Pro for MacOS earlier this year, we are excited to announce a new BeyondCorp Enterprise integration: Microsoft Intune, now available in Preview. Read more.Connect Gateway and ArgoCD: Integrating your ArgoCD deployment with Connect Gateway and Workload Identity provides a seamless path to deploy to Kubernetes on many platforms. ArgoCD can easily be configured to centrally manage various cluster platforms including GKE clusters, Anthos clusters, and many more. Read more. Architecting for database encryption on Google Cloud: Learn security design considerations and how to accelerate your decision making when migrating or building databases with the various encryption options supported on Google Cloud. Read more.Introducing fine-grained access control for Cloud Spanner: As Google Cloud’s fully managed relational database, Cloud Spanner powers applications of all sizes. Now in Preview, Spanner gets fine-grained access control for more nuanced IAM decisions. Read more.Building a secure CI/CD pipeline using Google Cloud built-in services: In this post, we show how to create a secure software delivery pipeline that builds a sample Node.js application as a container image and deploys it on GKE clusters. Read more.Introducing deployment verification to Google Cloud Deploy: Deployment verification can help developers and operators orchestrate and execute post-deployment testing without having to undertake a more extensive testing integration, such as with Cloud Deploy notifications or manually testing. Read more.Industry updatesThe 2022 Accelerate State of DevOps Report: Our 8th annual deep dive into the state of DevOps finds broad adoption of emerging security practices, especially among high-trust, low-blame cultures focused on performance. Read the full report.Compliance & ControlsEvolving our data processing commitments for Google Cloud and Google Workspace: We are pleased to announce that we have updated and merged our data processing terms for Google Cloud, Google Workspace, and Cloud Identity into one combined Cloud Data Processing Addendum. Read more.Data governance building blocks for financial services: How does data governance for financial services correspond to Google Cloud services and beyond? Here we propose an architecture capable of supporting the entire data lifecycle, based on our experience implementing data governance solutions with world-class financial services organizations. Read more.Update on regulatory developments and Google Cloud: As part of our commitment to be the most trusted cloud, we continue to pursue global industry standards, frameworks, and codes of conduct that tackle our customers’ foundational need for a documented baseline of addressable requirements. Here’s a summary of our efforts over the past several months. Read more.Google Cloud Security PodcastsWe launched a new weekly podcast focusing on Cloud Security in February 2021. Hosts Anton Chuvakin and Timothy Peacock chat with cybersecurity experts about the most important and challenging topics facing the industry today. This month, they discussed:Everything you wanted to know about securing AI (but were afraid to ask): What threats does artificial intelligence face? What are the best ways to approach those threats? What do we know so far about what works to secure AI? Hear answers to these questions and more with Alex Polyakov, CEO of Adversa.ai. Listen here.Inside reCAPTCHA’s magic: More than just “click on buses,” here’s how reCAPTCHA actually protects people, with Badr Salmi, product manager for reCAPTCHA. Listen here. SRE explains how to deploy security at scale: The art of Site Reliability Engineering has a lot to teach security teams about safe and rapid deployment, with our own Steve McGhee, reliability advocate at Google Cloud. Listen here.An XDR skeptic discusses all things XDR with Dimitri McKay, principal security strategist at Splunk. Listen here.To have our Cloud CISO Perspectives post delivered every month to your inbox, sign up for our newsletter. We’ll be back next month with more security-related updates.Related ArticleCloud CISO Perspectives: June 2022Google Cloud CISO Phil Venables shares his thoughts on the RSA Conference and the latest security updates from the Google Cybersecurity A…Read Article
Quelle: Google Cloud Platform
Amazon MSK Serverless ist jetzt HIPAA (Health Insurance Portability and Accountability Act)-konform. Dadurch können Sie jetzt von Amazon MSK Serverless verwaltetes Apache Kafka verwenden, um PHI (Protected Health Information, geschützte Gesundheitsdaten)-Daten zu speichern, zu verarbeiten und darauf zuzugreifen und um sichere Anwendungen für das Gesundheitswesen und Biowissenschaften zu betreiben. MSK Serverless ist ein Clustertyp für Amazon MSK, mit dem Sie Apache Kafka ausführen können, ohne die Clusterkapazität verwalten und skalieren zu müssen.
Quelle: aws.amazon.com
Heute haben wir AWS Certificate Manager Private Certificate Authority in AWS Private Certificate Authority (AWS Private CA) umbenannt. Somit können Kunden besser zwischen AWS Certificate Manager (ACM) und AWS Private CA entscheiden. ACM und AWS Private CA haben unterschiedliche Rollen im Prozess der Erstellung und Verwaltung der digitalen Zertifikate, die zur Identifizierung von Ressourcen und zur Sicherung der Netzwerkkommunikation über das Internet, in der Cloud und in privaten Netzwerken verwendet werden. ACM verwaltet den Lebenszyklus von Zertifikaten: Erstellen, Speichern, Bereitstellen und Verwalten von Erneuerungen für AWS-Services wie Elastic Load Balancing, Amazon CloudFront und Amazon API Gateway. Mit AWS Private CA können Kunden anpassbare private Zertifikate für eine breite Palette von Szenarien erstellen. AWS-Services wie ACM, Amazon Managed Streaming für Apache Kafka (MSK), IAM Roles Anywhere und Amazon Elastic Kubernetes Service (EKS) können alle private Zertifikate von Private CA nutzen. Es unterstützt auch die Erstellung von privaten Zertifikaten für Geräte des Internets der Dinge (IoT) sowie für Benutzer, Systeme und Dienste in Unternehmen.
Quelle: aws.amazon.com
AWS IoT FleetWise ist jetzt allgemein verfügbar, um Automobilunternehmen dabei zu unterstützen, Fahrzeugdaten zu erheben, umzuwandeln und nahezu in Echtzeit in die Cloud zu übertragen. Automobilunternehmen können die Daten in der Cloud verwenden, um den Zustand der Fahrzeugflotte eingehend zu analysieren. Mit den gewonnenen Erkenntnissen können Unternehmen schnell mögliche Wartungsprobleme identifizieren, Infotainment-Systeme im Fahrzeug aufrüsten oder mit Analyse und Machine Learning (ML) das autonome Fahren und Fahrerassistenzsysteme (ADAS) verbessern.
Quelle: aws.amazon.com
