Now it is time for a large Iced Capped from @timhortons & @timhortonses at #barcelona .
#timhortons #barcelona #catalonia #spain #relax #foodporn #instadaily https://t.co/NpbLiMdXcR https://t.co/qst8PLbMFz
RT @Seahawks: A special milestone for a one of a kind QB.
@DangeRussWilson has the most wins in a QB’s first 7 seasons in @NFL history! https://t.co/LdZzO0uF4p
RT @Seahawks: Undefeated in #ActionGreen, just sayin. 😎 https://t.co/mD9ThgG82W
As part of the Cognitive Search preview, the ability to extract information from unstructured files and the ability to execute cognitive skills were introduced in May 2018. This allowed you to extract images from unstructured documents such as PDFs and then enrich those documents through the execution of skills such as OCR, key phrase extraction, and named entity recognition to get more insights from your data. Until now, both skillset execution and the extraction of images from documents have been offered for free.
Starting December 21, 2018, you’ll be able to associate your Cognitive Services subscription with an Azure Search skillset. The skillset execution will be charged as part of the Cognitive Services subscription. On December 21, 2018, we’ll also begin charging for image extraction as part of our document-cracking stage. Text extraction from documents will continue to be offered at no additional cost.
The execution of built-in skills will be charged at the existing Cognitive Services pay-as-you go price. Image extraction pricing will be charged at preview pricing, and is described on the Azure Search pricing page. If you’re not currently using Cognitive Search capabilities as part of Azure Search, you shouldn’t be impacted by these price changes.
To associate a Cognitive Services subscription, follow these instructions.
Starting February 1, 2019, if you haven’t associated a Cognitive Services subscription, you’ll be limited to a certain number of free skill executions per month. Learn more.
from Azure service updates https://ift.tt/2UxtYNv
The experience of running Python apps on Azure App Service has been greatly improved. Previously, customers seeking to deploy Python on Azure could choose to run Python on Windows or on our Linux containers. Now, the built-in Python images for App Service for Linux (in preview) offer a far better and more comprehensive support for Python packages, as well as the ability to get started quickly without needing to use custom Docker containers. The new Python offering detects common Flask and Django application structures for hosting in gunicorn and works with common database drivers for MySQL and PostgreSQL.
from Azure service updates https://ift.tt/2BcMiCm
Azure Monitor for containers, now generally available, monitors the health and performance of Kubernetes clusters hosted on Azure Kubernetes Service (AKS). Since the launch of the preview of this service at Build (May 2018), there has been a lot of excitement from customers about the new capabilities, such as the ability to enable monitoring as soon as you create an AKS cluster. It’s also now possible to get all the monitoring telemetry in a centralized location in Azure without having to sign into containers or rely on other tools. Since the preview, several new capabilities have been added including:
- Multi-cluster view—The multi-cluster view discovers all AKS clusters across subscriptions, resource group, and workspaces, and provides you a health roll up view. You can even discover clusters that aren’t being monitored and start monitoring them with just few clicks.
- Performance grid view—To investigate further, drill down to performance grid view that shows the health and performance of your nodes, controllers, and containers. From the node view tab, it’s easy to spot the noisy neighbor issue on the pod and drill further to see the controller it’s part of. In addition, see the controller limits, request setting, and actual usage, and determine if you’ve configured your controller correctly. Continue investigating by looking at the Kubernetes event logs associated to that controller.
- Live debugging—With live logs, you get a real time, live stream of your container logs directly in your Azure portal to help you interactively troubleshoot issues. You can pause the live stream and search within the log file for errors or issues. Unlike the Azure Monitor logs, the live stream data is ephemeral and is meant for real time troubleshooting.
- Onboarding—In addition to the Azure portal, there are now more ways for you to automate onboarding Azure Monitor for containers: use Azure CLI (a single command), ARM template, and Terraform.
To learn more, read this blog post and our documentation.
from Azure service updates https://ift.tt/2UuL1jb
Perform offline (one-time) migrations from on-premises or cloud implementations of MongoDB to Azure Cosmos DB by using the Azure Database Migration Service, which enables resilient migrations of MongoDB data at scale and with high reliability. To perform the migration, provision an instance of the Database Migration Service from the Azure portal or via Azure CLI and create a project.
Read our documentation to learn more about performing these migrations.
from Azure service updates https://ift.tt/2BcdLV7