Amazon Rekognition Custom Labels is an automated machine learning (AutoML) service that allows customers to build custom computer vision models to classify and identify objects in images that are specific and unique to their business. Custom Labels does not require customers to have any prior computer vision expertise or knowledge.
We are excited to announce the availability of Amazon EC2 P4d instances in the AWS GovCloud (US) Region. P4d instances are optimized for applications in Machine Learning (ML) and High Performance Computing (HPC).
Starting today, Amazon EC2 High Memory instances with 12TB of memory (u-12tb1.112xlarge) are available in the US East (Ohio) region. Additionally, high memory instances with 6TB of memory (u-6tb1.56xlarge, u-6tb1.112xlarge) are now available in the South America (Sao Paulo) region and instances with 3TB of memory (u-3tb1.56xlarge) are now available in the South America (Sao Paulo) and Asia Pacific (Sydney) regions.
Hoy presentamos la disponibilidad general de AWS Private 5G, un servicio administrado que ayuda a empresas a configurar y escalar redes móviles privadas en sus instalaciones en cuestión de días en lugar de meses. Con solo unos pocos clics en la consola de administración de AWS, puede especificar dónde crear una red móvil y la cantidad de dispositivos que quiere conectar. Luego, AWS entrega y mantiene la unidad de radio de celdas pequeñas, el núcleo de la red móvil y el software de la red de acceso de radio (RAN), y los módulos de identidades de los suscriptores (tarjetas SIM) necesarios para configurar una red móvil privada y conectar dispositivos. AWS Private 5G automatiza la configuración y la implementación de la red. Con AWS Private 5G, no incurre en tarifas iniciales ni costos por dispositivo y solo paga por la capacidad de red que solicita.
Ahora puede habilitar las protecciones de AWS WAF para Amazon Cognito. De esta forma, es aún más fácil proteger la interfaz de usuario alojada y los grupos de usuarios de Amazon Cognito de las vulnerabilidades web comunes.
Amazon EventBridge ahora admite integraciones con GitHub, Stripe y Twilio a través de webhooks usando los Quicks Starts. Puede suscribirse a eventos desde estas aplicaciones SaaS y recibirlos en un bus de eventos de Amazon EventBridge para su posterior procesamiento. Con los Quick Starts, puede usar plantillas de AWS CloudFormation para crear puntos de conexión HTTP para su bus de eventos que están configurados con las mejores prácticas de seguridad para GitHub, Stripe y Twilio. Puede configurar sus webhooks de GitHub, Stripe y Twilio desde las cuentas respectivas. Simplemente, seleccione los tipos de eventos que quiere enviar al punto de conexión recién generado y comience a recibirlos de forma segura en su bus de eventos.
Amazon CloudWatch Synthetics, una capacidad de supervisión indirecta que verifica continuamente la experiencia de sus clientes, incluso cuando no tiene tráfico de clientes en sus aplicaciones, introdujo una nueva capacidad para crear grupos personalizados de valores controlados. Al crear un grupo de valores controlados, puede realizar un seguimiento del estado de aciertos/errores a nivel de grupo o aplicación, pero con un fácil desglose hasta llegar al valor controlado que produce el error. Esto facilita la identificación de los errores de los valores controlados en el contexto del grupo o la aplicación. Cuando los grupos consisten en valores controlados en varias regiones de AWS, esta nueva capacidad le permite aislar más fácilmente los problemas específicos de la región.
Ahora puede utilizar Amazon EKS y Amazon EKS Distro para ejecutar la versión 1.23 de Kubernetes. Los puntos destacados del lanzamiento de la versión 1.23 de Kubernetes incluyen la graduación de los contenedores PodSecurity y Ephemeral a la versión beta, y de HorizontalPodAutoscaler a generalmente disponible. Además, la versión 1.23 de Kubernetes activa la característica de migración de CSI para Amazon EBS de forma predeterminada. Puede obtener más detalles sobre la versión 1.23 de Kubernetes en la publicación del blog de EKS y en las notas de la versión de EKS y en las notas de la versión del proyecto de Kubernetes. La compatibilidad con la versión 1.23 estará disponible en Amazon EKS Anywhere en las próximas dos semanas.
Amazon Rekognition Custom Labels is an automated machine learning (AutoML) service that allows customers to build custom computer vision models to detect objects and scenes specific to their business without in-depth machine learning expertise. Starting today, Custom Labels can automatically scale inference units of a trained model based on customer workload. This reduces model inference cost as customers no longer need to over-provision inference units to support spiky or fluctuating image volumes.
Posted by Wesley Chun (@wescpy), Developer Advocate, Google Cloud
The most recent Serverless Migration Station video demonstrated how to add use of the App Engine’s Blobstore service to a sample Python 2 App Engine app, kicking off the first of a 2-part series on migrating away from Blobstore. In today’s Module 16 video, we complete this journey, arriving at Cloud Storage. Moving away from proprietary App Engine services like Blobstore makes apps more portable, giving them enough flexibility to:
- Update to more recent language releases, say from Python 2 to 3 or Java 8 to 17, and run on App Engine’s 2nd generation service
- Shift across to other serverless platforms, like Cloud Functions or Cloud Run (with or without Docker), or
- Move to VM-based services like GKE or Compute Engine, or to other compute platforms
As described previously, a Blobstore for Python 2 dependency on webapp made the Module 15 content more straightforward to implement if it was still using webapp2. To completely modernize this app here in Module 16, the following migrations should be carried out:
- Migrate from
webapp2(andwebapp) to Flask- Migrate from App Engine NDB to Cloud NDB
- Migrate from App Engine Blobstore to Cloud Storage
- Migrate from Python 2 to Python (2 and) 3
Prior to modifying the application code, a variety of configuration updates need to be made. Updates applying only to Python 2 feature a “Py2” designation while those migrating to Python 3 will see “Py3” annotations.
- Remove the built-in Jinja2 library from
app.yaml—Jinja2 already comes with Flask, so remove use of the older built-in version which may possibly conflict with the contemporary Flask version you’re using. (Py2)- Use of Cloud client libraries (such as those for Cloud NDB and Cloud Storage) require a pair of built-in libraries,
grpcioandsetuptools, so add those toapp.yaml(Py2)- Remove everything in
app.yamlexcept for a valid runtime (Py3)- Add Cloud NDB and Cloud Storage client libraries to
requirements.txt(Py2 & Py3)- Create an
appengine_config.pysupporting both built-in (those inapp.yaml) and non built-in (those inrequirements.txt) libraries used (Py2)
The Module 15 app already migrated away from webapp2‘s (Django) templating system to Jinja2. This is useful when migrating to Flask because Jinja2 is Flask’s default template system. Switching from App Engine NDB to Cloud NDB is fairly straightforward as the latter was designed to be mostly compatible with the original. The only change visible in this sample app is to move Datastore calls into Python with blocks.
The most significant changes occur when moving the upload and download handlers from webapp to Cloud Storage. The video and corresponding codelab go more in-depth into the necessary changes, but in summary, these are the updates required in the main application:
webapp2 is replaced by Flask. Instead of using the older built-in version of Jinja2, use the version that comes with Flask.webapp Blobstore handler functionality is replaced by a combination of the io standard library module plus components from Flask and Werkzeug. Furthermore, the handler classes and methods are replaced by Flask functions.
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| The sample app’s most recent visits page. |
The only difference is that four migrations have been completed where all of the “infrastructure” is now taken care of by non-App Engine legacy services. Furthermore, the Module 16 app could be either a Python 2 or 3 app. As far as the end-user is concerned, “nothing happened.”
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| Migrating sample app from App Engine Blobstore to Cloud Storage |
Module 16 featured four different migrations, modernizing the Module 15 app from using App Engine legacy services like NDB and Blobstore to Cloud NDB and Cloud Storage, respectively. While we recommend users move to the latest offerings from Google Cloud, migrating from Blobstore to Cloud Storage isn’t required, and should you opt to do so, can do it on your own timeline. In addition to today’s video, be sure to check out the Module 16 codelab which leads you step-by-step through the migrations discussed.
In Fall 2021, the App Engine team extended support of many of the bundled services to 2nd generation runtimes (that have a 1st generation runtime), meaning you are no longer required to migrate to Cloud Storage when porting your app to Python 3. You can continue using Blobstore in your Python 3 app so long as you retrofit the code to access bundled services from next-generation runtimes.
If you’re using other App Engine legacy services be sure to check out the other Migration Modules in this series. All Serverless Migration Station content (codelabs, videos, source code [when available]) can be accessed at its open source repo. While our content initially focuses on Python users, the Cloud team is working on covering other language runtimes, so stay tuned. For additional video content, check out our broader Serverless Expeditions series.
AWS IoT SiteWise now supports bulk import of historical measurements from sensors with the launch of three new APIs. The new bulk import APIs help customers to ingest historical data from their operations stored in diverse systems such as historians and time series databases in AWS IoT SiteWise.
Amazon WorkSpaces Web is now generally available in AWS Canada (Central), Europe (Frankfurt), and Europe (London) regions. Creating a WorkSpaces Web portal in a local region provides a more responsive experience for users when streaming web content. It also enables customers to meet local data residency obligations. WorkSpaces Web is now available in a total of 10 regions.
