by Contributed | Jun 21, 2021 | Technology
This article is contributed. See the original author and article here.
Event Agenda
Calling all web developers! We’re so excited to announce Static Web Apps – Code to Scale, a special live event to celebrate the official release of Azure Static Web Apps! Join our team for a free live event on June 30 @ 9am PT (4pm GMT) and learn how to deploy Azure Static Web Apps on your Azure for Student subscription.
Join us at 9:00 AM PDT / 16:00 UTC 30th June
by Contributed | Jun 21, 2021 | Technology
This article is contributed. See the original author and article here.
You can create a type of custom field that allows you to quickly choose from several options. Choice custom fields are great for scenarios such as having a Risk column with “High”, “Medium”, and “Low” values. Also, try using them for rough planning of tasks such as “This week”, “Next Week”, and “Later”. Like other custom fields, you can use them in the Grid, in the Board view, and in the task details card. Try them out!
Getting Started
Like other custom fields, click the “Add column” button and choose the “New field” option.
Then, select the “Choice” field type.
Now give your field a name and a set of options. Press the delete icon next to a choice and the Add a Choice button at the bottom to manage the number of choices you would like to have. You can use the handle on the left side to reorder the choices. You can also use Ctrl + Up/Down on Windows, or Command + Up/Down on Mac to reorder choices with your keyboard.
Frequently Asked Questions
How many choices can I make?
20 for now. We will support 25 soon. Let us know if you need more!
How can I use emojis in my fields?
Windows and Mac both include an emoji menu. Press Win + ; (Windows key plus semicolon) to open it. On Mac, press Control + Command+ Space.
Are choice fields included when I make copies of a project?
Yes! Both the fields and the values are included when you copy a project.
Where can I go to learn about the other types of custom fields?
Head over to our support site to learn more about the types of custom fields available in Project for the web.
Are these “enterprise” fields? Can I build reports using them?
No. Like the other types of custom fields, this field type is only visible in Project for the web.
by Contributed | Jun 21, 2021 | Technology
This article is contributed. See the original author and article here.
This video series shows how you can adopt a Zero Trust approach for security and benefit from the core ways in which Microsoft can help. In the past, your defenses may have been focused on protecting network access with on-premises firewalls and VPNs, assuming everything inside the network was safe. But as corporate data footprints have expanded to sit outside your corporate network, to live in the Cloud or a hybrid across both, the Zero Trust security model has evolved to address a more holistic set of attack vectors.
Based on the principles of “verify explicitly”, “apply least privileged access” and “always assume breach”, Zero Trust establishes a comprehensive control plane across multiple layers of defense:
- Identity
- Endpoints
- Applications
- Network
- Infrastructure
- Data
Introduction to Zero Trust
Identity:
Join our host, Jeremy Chapman, as he unpacks the foundational layer of the model with identity. As the primary control plane for Zero Trust, it acts as the front door for people, service accounts, and devices as each requests access to resources. Identity is at the core of the Zero Trust concepts of never trust, always verify and grant the appropriate level of access through the principle of least privilege.
Zero Trust | Identity
Endpoints & Applications:
See how you can apply Zero Trust principles and policies to your endpoints and apps; the conduits for users to access your data, network, and resources. For Zero Trust, endpoints refer to the devices people use every day — both corporate or personally owned computers and mobile devices. The prevalence of remote work means devices can be connected from anywhere and the controls you apply should be correlated to the level of risk at those endpoints.
For corporate managed endpoints that run within your firewall or your VPN, you will still want to use principles of Zero Trust: Verify explicitly, apply least privileged access, and assume breach.Jeremy Chapman walks through your options, controls, and recent updates to implement the Zero Trust security model.
Zero Trust | Endpoints & Applications
by Contributed | Jun 21, 2021 | Technology
This article is contributed. See the original author and article here.
This series of videos shows team leaders and admin the underlying tech and options for enabling and configuring the four core modules of Microsoft Viva. Viva is the new employee experience platform that connects learning, insights, resources, and communication. It has a unique set of curated and AI-enriched experiences built on top of and integrated with the foundational services of Microsoft 365.
Introduction to Microsoft Viva
Microsoft Viva’s 4 core modules:
- Viva Topics — builds a knowledge system for your organization
- Viva Connections — boosts employee engagement
- Viva Learning — creates a central hub to discover learning content and build new skills
- Viva Insights — recommends actions to help improve productivity and wellbeing
Microsoft Viva Topics:
Viva Topics builds a system that transforms information into knowledge and actively delivers it to you in the context of your work. As many of us are working remotely or in more hybrid office environments, it can be harder to stay informed. With Topics, we connect you to the knowledge and the people closest to it. CJ Tan, Lead Program Manager, joins host Jeremy Chapman to cover the overall experience for users, knowledge managers, and admins.
Microsoft Viva Topics
Microsoft Viva Connections:
Viva Connections is specifically about boosting employee engagement. This spans everyone in your organization, from everyday users, specific groups in departments, to frontline workers. It expands on your SharePoint home site and newsfeed and is designed to offer a destination that delivers personalized news, conversations, and commonly used resources. Adam Harmetz, lead engineer, joins host Jeremy Chapman to walk through the user experience, how to set it up, and options for personalizing information sharing by role.
Microsoft Viva Connections
Microsoft Viva Learning:
With Viva Learning, you have a center for personalized skill development that offers a unique social experience where learning content is available in the flow of work. It recommends and manages the progress of key trainings all from one place and is built on top of SharePoint, Microsoft Search, Microsoft Teams, Microsoft Graph, and Substrate. Swati Jhawar, Principal Program Manager for Microsoft Viva, joins Jeremy Chapman to share options for setup, learning content curation, and integration with your existing learning management system.
Microsoft Viva Learning
Microsoft Viva Insights:
With hybrid work at home and in the office as the new normal, Viva Insights gives individuals, managers, and leaders the insight to develop healthier work habits and a better work environment. It is an intelligent experience designed to leverage MyAnalytics, Workplace Analytics, and Exchange Online to deliver insights that recommend actions to help prioritize well-being and productivity. Engineering leader, Kamal Janardhan, joins Jeremy Chapman for a deep dive and a view of your options for configuration.
Microsoft Viva Insights
by Contributed | Jun 21, 2021 | Technology
This article is contributed. See the original author and article here.
With our recent announcement of support for custom containers in Azure Machine Learning comes support for a wide variety of machine learning frameworks and servers including TensorFlow Serving, R, and ML.NET. In this blog post, we’ll show you how to deploy a PyTorch model using TorchServe.
The steps below reference our existing TorchServe sample here.
Export your model as a .mar file
To use TorchServe, you first need to export your model in the “Model Archive Repository” (.mar) format. Follow the PyTorch quickstart to learn how to do this for your PyTorch model.
Save your .mar file in a directory called “torchserve.”
Construct a Dockerfile
In the existing sample, we have a two-line Dockerfile:
FROM pytorch/torchserve:latest-cpu
CMD ["torchserve","--start","--model-store","$MODEL_BASE_PATH/torchserve","--models","densenet161.mar","--ts-config","$MODEL_BASE_PATH/torchserve/config.properties"]
Modify this Dockerfile to pass the name of your exported model from the previous step for the “–models” argument.
Build an image
Now, build a Docker image from the Dockerfile in the previous step, and store this image in the Azure Container Registry associated with your workspace:
WORKSPACE=$(az config get --query "defaults[?name == 'workspace'].value" -o tsv)
ACR_NAME=$(az ml workspace show -w $WORKSPACE --query container_registry -o tsv | cut -d'/' -f9-)
if [[ $ACR_NAME == "" ]]
then
echo "ACR login failed, exiting"
exit 1
fi
az acr login -n $ACR_NAME
IMAGE_TAG=${ACR_NAME}.azurecr.io/torchserve:8080
az acr build $BASE_PATH/ -f $BASE_PATH/torchserve.dockerfile -t $IMAGE_TAG -r $ACR_NAME
Test locally
Ensure that you can serve your model by doing a local test. You will need to have Docker installed for this to work. Below, we show you how to run the image, download some sample data, and send a test liveness and scoring request.
# Run image locally for testing
docker run --rm -d -p 8080:8080 --name torchserve-test
-e MODEL_BASE_PATH=$MODEL_BASE_PATH
-v $PWD/$BASE_PATH/torchserve:$MODEL_BASE_PATH/torchserve $IMAGE_TAG
# Check Torchserve health
echo "Checking Torchserve health..."
curl http://localhost:8080/ping
# Download test image
echo "Downloading test image..."
wget https://aka.ms/torchserve-test-image -O kitten_small.jpg
# Check scoring locally
echo "Uploading testing image, the scoring is..."
curl http://localhost:8080/predictions/densenet161 -T kitten_small.jpg
docker stop torchserve-test
Create endpoint YAML
Create a YAML file that specifies the properties of the managed online endpoint you would like to create. In the example below, we specify the location of the model we will use as well as the Azure Virtual Machine size to use when deploying.
$schema: https://azuremlsdk2.blob.core.windows.net/latest/managedOnlineEndpoint.schema.json
name: torchserve-endpoint
type: online
auth_mode: aml_token
traffic:
torchserve: 100
deployments:
- name: torchserve
model:
name: torchserve-densenet161
version: 1
local_path: ./torchserve
environment_variables:
MODEL_BASE_PATH: /var/azureml-app/azureml-models/torchserve-densenet161/1
environment:
name: torchserve
version: 1
docker:
image: {{acr_name}}.azurecr.io/torchserve:8080
inference_config:
liveness_route:
port: 8080
path: /ping
readiness_route:
port: 8080
path: /ping
scoring_route:
port: 8080
path: /predictions/densenet161
instance_type: Standard_F2s_v2
scale_settings:
scale_type: manual
instance_count: 1
min_instances: 1
max_instances: 2
Create endpoint
Now that you have tested locally and you have a YAML file, you can create your endpoint:
az ml endpoint create -f $BASE_PATH/$ENDPOINT_NAME.yml -n $ENDPOINT_NAME
Send a scoring request
Once your endpoint finishes deploying, you can send it unlabeled data for scoring:
# Get accessToken
echo "Getting access token..."
TOKEN=$(az ml endpoint get-credentials -n $ENDPOINT_NAME --query accessToken -o tsv)
# Get scoring url
echo "Getting scoring url..."
SCORING_URL=$(az ml endpoint show -n $ENDPOINT_NAME --query scoring_uri -o tsv)
echo "Scoring url is $SCORING_URL"
# Check scoring
echo "Uploading testing image, the scoring is..."
curl -H "Authorization: {Bearer $TOKEN}" -T kitten_small.jpg $SCORING_URL
Delete resources
Now that you have successfully created and tested your TorchServe endpoint, you can delete it.
# Delete endpoint
echo "Deleting endpoint..."
az ml endpoint delete -n $ENDPOINT_NAME --yes
# Delete model
echo "Deleting model..."
az ml model delete -n $AML_MODEL_NAME --version 1
Next steps
Read our documentation to learn more and see our other samples.
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