We are thrilled to announce the availability of B-series VM’s, burstable VM’s in Azure Container Service (AKS).
Burstable VM’s (B-series) are significantly cheaper compared to standard and optimal recommended VM’s like Standard_DS2_V2. B-series VM’s are particularly suited for development and test environments where performance requirements are bursts rather than consistent. In fact, B-Series provides the cheapest cost with bursts CPU usage and thus reduces development and test environment costs significantly. We hope that this addition will significantly reduce the cost of learning Kubernetes AKS, building proof of concepts on Azure Container Service (AKS), running dev/test workloads, etc.
The following configurations are available today.
SKU Type VCPUS GB Ram Data Disks Max IOPS Local SSD B1s Standard 1 1 2 800 2GB B1ms Standard 1 2 2 1600 4GB B2s Standard 2 4 4 3200 8GB B2ms Standard 2 8 4 4800 16GB B4ms Standard 4 16 8 7200 32GB B8ms Standard 8 32 16 10800 64GB
In comparison, a Standard_DS2_V2 node costs greater than five times the B1/B2 SKU’s today. Check the latest VM pricing.
To get started log on to the Azure portal and search for Container Service (managed). As you follow the AKS create cluster workflow, you will
We are happy to share that Azure Service Bus is now able to send events to Azure Event Grid. The key scenario this feature enables is for Service Bus queues, topics, or subscriptions with low message volumes to not require a receiver to be polling for messages at all times. Service Bus will now send events to Azure Event Grid when there are messages in a queue if no receivers are present. You can create Azure Event Grid subscriptions for your Service Bus namespaces, listen to these events, and react to the events by starting a receiver. With this feature, Service Bus can be used in reactive programming models.
Today, Azure Service Bus sends events for two scenarios:
Active messages with no listeners available Deadletter messages available
Additionally, it uses the standard Azure Event Grid security and authentication mechanisms.
How often and how many events are emitted?
If you have multiple queues and topics/subscriptions in the namespace, you get at least one event per queue and subscription. The events are immediately emitted if there are no messages in the Service Bus entity and a new message arrives, or every two minutes unless Azure Service Bus detects an active receiver.
Azure recently introduced an advanced, more efficient Load Balancer platform. This platform adds a whole new set of abilities for customer workloads using the new Standard Load Balancer. One of the key additions the new Load Balancer platform brings, is a simplified, more predictable and efficient outbound port allocation algorithm.
While already integrated with Standard Load Balancer, we are now bringing this advantage to the rest of Azure.
Load Balancer and Source NAT
Azure deployments use one or more of three scenarios for outbound connectivity, depending on the customer’s deployment model and the resources utilized and configured. Azure uses Source Network Address Translation (SNAT) to enable these scenarios. When multiple private IP addresses or roles share the same public IP (public IP address assign to Load Balancer or automatically assigned public IP address for standalone VMs), Azure uses port masquerading SNAT (PAT) to translate private IP addresses to public IP addresses using the ephemeral ports of the public IP address. PAT does not apply when Instance Level Public IP addresses (ILPIP) are assigned.
For the cases where multiple instances share a public IP address, each instance behind an Azure Load Balancer VIP is pre-allocated a fixed number of ephemeral ports
https://blogs.msdn.microsoft.com/sql_server_team/sql-server-replication-enhancement-dynamic-reloading-of-agent-profile-parameters/Source: https://blogs.msdn.microsoft.com/sql_server_team/sql-server-replication-enhancement-dynamic-reloading-of-agent-profile-parameters/ With SQL Server 2017 Cumulative Update 3, we introduced an improvement to SQL Server Replication wherein, changes to the Replication agent parameters can be reloaded dynamically, without having to restart the agent. This improvement will be available READ MORE
https://powerbi.microsoft.com/en-us/blog/automatically-install-apps/Source: https://powerbi.microsoft.com/en-us/blog/automatically-install-apps/ I’m excited to announce the ability to automatically install apps for end users, making it easier to distribute the right apps to the right set of people. Apps deliver data that your end READ MORE
This post is the second in a three-part series by guest blogger, Adrian Rosebrock. Adrian writes at PyImageSearch.com about computer vision and deep learning using Python. He recently finished authoring a new book on deep learning for computer vision and image recognition.
A few weeks ago I wrote a blog post on deep learning and computer vision in the Microsoft Azure cloud that was meant to be a gentle introduction to Microsoft’s Data Science Virtual Machine (DSVM). Today we’re going to get a bit more hands-on and practical, beginning with an email I received from PyImageSearch reader, Kostas:
“Hey Adrian, I’m interested in competing in Kaggle competitions (in particular the computer vision ones). I have some experience in computer vision and machine learning/deep learning but not a lot. Is it even worth my time? Do I even stand a chance against other competitors?”
Great question, Kostas — and I’m sure you’re not alone feeling this way.
Let me answer your question with a story:
When I first set out to write my new book, Deep Learning for Computer Vision with Python, my goal was to create a book/self-study program that was accessible to both novices and experienced researchers
This post is the first part of two blog posts, describing how to setup a CI/CD pipeline using VSTS for deploying a dockerized custom WordPress website working with Azure WebApp for Containers and Azure Database for MySQL.
The main motivation for building a WordPress CI/CD pipeline is the fact that WordPress is limited in supporting dynamic configuration to allow easy modification between different environments. Some values are hardcoded in the WordPress MySQL database. This limitation causing a time consuming task which limits our ability to deploy fast and more frequently.
We will have four environments: local, dev, test and production. The local environment is for the developer that will run the docker images locally, commit the required changes, and will push the code to the master branch once they completed their work. The push action will initiate a CI process, which will build and push a new docker image to our Azure Container Registry. The base image of this docker image will be the WordPress image from the docker hub. As part of the dockerfile, a copy action will be executed for copying the new content into the new docker image.
After the CI process completion
This blog post was co-authored by Anitha Adusumilli, Principal Program Manager, Azure Networking.
We are excited to announce the general availability of Virtual Network (VNet) Service Endpoints for Azure SQL Database in all Azure regions. This ability allows you to isolate connectivity to your logical server from only a given subnet or set of subnets within your virtual network. The traffic to Azure SQL Database from your VNet will always stay within the Azure backbone network. This direct route will be preferred over any specific routes that take Internet traffic through virtual appliances or on-premises.
There is no additional billing for virtual network access through service endpoints. Current pricing model for Azure SQL DB applies as is.
VNet service endpoints for SQL Data Warehouse (DW) continues to be in public preview, for all Azure regions.
Firewall rules and VNet Service Endpoints can be used together
Turning on VNet Service Endpoints does not override Firewall rules that you have provisioned on your SQL Server or Database. Both continue to be applicable.
VNet Service Endpoints don’t extend to on-premises. To allow access from on-premises, Firewall rules can be used to limit connectivity only to your public (NAT) IPs.
To enable VNet
In the last few years, many law enforcement agencies have adopted body worn cameras. In this blog post, I will provide some background on what is driving the growth and will talk about how AI can help law enforcement agencies with the processing of videos captured by body-worn cameras.
Background on body-worn cameras
A body worn camera is a wearable audio, video or photographic recording system. Law enforcement agencies are not the only consumers of body-worn cameras. Other consumers include journalists, medical professionals, athletes, and so on. The forecast unit shipments of body-worn cameras can be seen on this webpage published by Statista.
The National Institute of Justice (NIJ), the research, development and evaluation agency of the US Department of Justice, conducted research on body-worn cameras for law enforcement and conducted a market survey on body-worn cameras for criminal justice. The survey updated in 2016, aggregates and summarizes information on a number of makes and models of body-worn cameras available today, including the approximate costs of each unit. The full market survey on body-worn camera technologies can be found on NIJ’s website.
Freedom of Information Act (FOIA)
FOIA is defined on foia.gov as a law that gives citizens the right
This blog post was co-authored by Riham Mansour, Principal Program Manager, Fuse Labs.
Conversational systems are rapidly becoming a key component of solutions such as virtual assistants, customer care, and the Internet of Things. When we talk about conversational systems, we refer to a computer’s ability to understand the human voice and take action based on understanding what the user meant. What’s more, these systems won’t be relying on voice and text alone. They’ll be using sight, sound, and feeling to process and understand these interactions, further blurring the lines between the digital sphere and the reality in which we are living. Chatbots are one common example of conversational systems.
Chatbots are a very trendy example of conversational systems that can maintain a conversation with a user in natural language, understand the user’s intent and send responses based on the organization’s business rules and data. These chatbots use Artificial Intelligence to process language, enabling them to understand human speech. They can decipher verbal or written questions and provide responses with appropriate information or direction. Many customers first experienced chatbots through dialogue boxes on company websites. Chatbots also interact verbally with consumers, such as Cortana, Siri and Amazon’s Alexa. Chatbots are