Dynamics & Power Platform browser extensions and tools

Key Tools and Browser Extensions for Dynamics and  Power platform Developers:

• Level up for Dynamics (extension)
• Dynamics 365 Power Pane (extension)
• Microsoft power automate Desktop (extension)

Microsoft Azure Artificial Intelligence (AI) - AZ-900 Notes

1. Artificial Intelligence (AI) 

• AI making PC behave like human intelligence.  
• Teach PC to do task for us.  
• PC predicts using patterns and can act.  And good at looking for anomalies.
• PC uses camera/photos to look for patterns.
• Engage in useful conversations, use multiple sources of knowledge.

2. Machine Learning (ML)

• Train PC's to see patterns and see patterns, and look for anomalies.
• Example. predict stock prices by looking at factors that affect stock price.
• Anomaly Detection - Detects unusual patterns e.g. CC used in Asia when normally in Europe, but transactions 10 min apart.  Therefore likely to be fraudulent.  Sort rubbish.
• Predictive models by finding relationships.  Give model data and train the model.  
• Example: flowers have features/characteristics e.g. colour, size, no petals, ...
• Using data to teach machine
• Supervise ML - need quality data including labels.  Avg humidity, hrs sunshine, rainfall, temp, month of year (features), ice creams sold(label/class), so we feed in temp is Regression ML.  Patient has features (weight, sex, age, bmi,...) give value btwn 0-1 of the person developing diabetes.  is Classification ML
• Unsupervised ML - data is not labelled.  Just feature provided, will group into clusters.  Pulls data out and figures out it's own criteria is Clustering ML.  Useful for fraud detection.
• Training - good data based on a training set and a validation set.  Train model, with most data, then check with remaining - allows us to see how close to what happened.  Service tries to figure out relationships.  Model is used by test data - see how close/useful model is.

3. Compute Vision 

• Self driving cars, sorting. Sort rubbish.
• Facial recognition, object recognition,..
• How do computers see?  picture is cut up into pixels, data is pulled and used to find possible ans. 
• Some types on Azure:  object detection i.e. car, bike, car, bus.  Image classification i.e horse, car.  Semantic segmentation i.e. Teams blur background.   Image analysis contect by bring various tougher.  Face detection.  OCR - read image and converts to text.

4. Natural Language Processing (NLP) 

•     interpret e.g grammerly, spam check, Alexia, 
•     Knowledge Mining - Extract info from knowledge and gain insights e.g. social media marketing.

Principals:

1. Fairness - ensure bias is excluded e.g based on gender.
2. Reliable & Safety - need high confidence and in certain systems cannot fail e.g. health systems, autonomous cars.
3. Privacy & Security - Ensure data is protected and not giving away sensitive data.
4. Inclusiveness - should be fair i.e. VI users
5. Transparency - what is the model based on, what could be an issue.
6. Accountability - who is liable for AI decisions

Azure:

1. Scalability & Reliability
2. AI Resources: sit in an Azure Resource Group

AI Services in Azure:

1. Azure Machine Learning - Developers to train, test and deploy ML models.  Within a subscription, create a Azure ML Workspace (consists of: compute, data, jobs, models) can then publish as a service.  Azure ML Designer, used for creating ML pipeline, data in to train model.  Automated Machine Learning user only needs to provide the data and select the model to use, service figures it out. 
2. Cognitive Services - vision, speak, language, decision.  Rest API endpoints - have already been trained, choose the model.  Can deploy multiple parts individually or together.

    3. Azure Bot Service - develop & managing intelligent bots like chat-bots
    4. Azure Cognitive Search - Data extraction, & enrichment for indexing.  Makes data searchable.

Anomaly detector resource - wizard to setup - Add Keys and endpoints to allow access.

Create a new Azure Machine Learning Service, will create a Workspace.  Use multiple azure services such as key-vault, AI, storage accounts.   

• Launch Studio
• Add Compute Cluster
• Add Data (csv, spreadsheets, nearly any form,...)
• AutomateML (figure it out without me) and run job
• Will show trends
• Deploy the model (i.e. to a web service)
• Shows "Endpoints" - get url and a test rig.

Notes for running Agile Power Platform Projects including DevOps

Overview:  General overview notes on setting up Power Platform projects/programs.  Before I get into the mechanics, my overriding goal is to have high functioning teams, and be a member of high functioning teams.  "Create an environment where team members can do there best work".  for instance, I visit and work with a lot of businesses and I many teams that are in an "Artificial Harmony" state (pretend all is well with the world). Everyone says it's wonderful but it's a snake-pit with relationships and fear.  Teams members need to be happy, open to conversations, accept risk and aware mistakes are going to happen.  Basically, these teams need to be identified and trust build, this often involves an adjustment to a particular mid-level manager.  The worst offenders tend to be offshore teams, and there are amazing teams and people so this definitely is a generalization. The teams tend to be hierarchical as opposed to flat or matrix. it's terrible for software projects.  Look out for Technical leads, ISV Project managers, Deliver Leads, they can breed the wrong tone/attitude across multiple team members and teams.  Check out Amy Edmondson's book the Right kind of wrong: the Science of failing well.  Anyway, rant over.   

Learn from mistakes, simple mistakes, remove them ASAP, strategically think automation, if we learn mistakes ensure they don't happen on the next project or sooner.  Encourage transparency, and open communication.

Here are my notes for setting up ADO and guidance for Agile PP projects....

Agile Artifact Hierarchy:

Epics > User Stories (max 5 days work) > Tasks 

                                                                  > Bugs

Epics > Spike

Guide:

• User Stories mush be written in the format: As the <role> , I want to <feature> so that <benefit>., and have 1 to many Acceptance Criteria using Gherkin 
• Ability to add a release note to User Story, Spike, Task or Bug.
• Automate pipelines from unmanaged to UAT Managed.
• Min three env (Dev-unmanaged), and UAT/Prod-both managed), use ADO pipelines or Power platform pipelines
• Adding annotated images is great for improved communication.  Recorded voice narrated mp4 walk thrus are also great for proofs, and explaining issues.
• US, bug, Task, Spike artifact items, each has a Release note tab.  So if a User Story needs more than 1 solution package changed, use child tasks and add the release notes to the User Story.

Flow of bugs and User Stories:

1. New (Anyone)
2. Approved (Product Owner (PO)) 
3. Ready - (PO)
4. Committed - (Team Member/dev)
5. Dev - In Progress (dev)
6. Dev - Complete (dev)
7. Dev - Show QA (dev & QA)
8. UAT - Ready to Deploy in UAT (dev)
9. UAT - Deployed Ready for Testing (QA)
10. UAT - In Tested Manaual (QA & PO)
11. UAT - Complete Ready for Deployment to Prd (QA)
12. PRD - Deployed
13. PRD - Sanity Check (can include automate smoke testing)
14. PRD - Done

Example Status's

Other states:

• Removed
• Duplicate
• Not Applicable

Release Notes for Power Platform packages need to include the following fields in ADO against artefacts:

1. Package Name (dropdownlist), 
2. Current Package Version, 
3. New Package Version (Default TBC), 
4. Change Note,  
5. Deployed Status (dropdown list: NA, UAT, PRD), 
6. Pre deployment steps, 
7. Post Deployment steps

Example of ADO Release Notes assigned against tasks, bugs, and user stories.

Quick fixes/urgent bugs/Emergency changes:

• Try make release cycles as short as possible, and only do emergency changes if absolutely required.
• Take a snapshot copy of dev/label, for each proposed production deployment - unmanaged env - part of ADO pipeline, this allows us to build Dev, and UAT env for the specific emergency change.
• Take a snapshot of UAT - managed env - part of ADO pipeline
• Deploy to PRD from Emergency UAT.
• Developer integrates emergency change into Dev from the Dev Copy.  And follows the full path.

Team/Teams:

• Try keep teams as small as possible.  I prefer 1 team to multiple scrum teams unless their is a clear distinction/break.
• Product Owner (PO) needs to be available all the time and answer immediately.  To me they act as the business and the traditional BA role, and are responsible for the product backlog.
• Scrum masters.  Your job is to ensure the team members are happy and confident to take risks and work, Scrum ceremonies are merely a way to help out.
• Team members are mainly pro and citizen developers, if I use dedicated QA testers in the scrum team, they need to be responsible for the AC with the PO.  They tend to be analyst/developers.
• Automate, automate, automate.  there are fantastic tools including low code test tools, use them.  Ensure you have automate smoke tests, regression tests, and performance tests for each DTAP env.
• Have short coding standards and naming conventions, error handling patterns and enforce them, have a defined ADO process, have a pipeline for deployments, automate tests and continuously update.  Have a Monitoring strategy i.e. Azure Monitor, log via AppInsights on a Log Analytics workspace.  Each env logs to it's own Azure Log Analytics.  Does each Log analytics belong to their own workspace?  I pref Non-prod, and prod workspaces. 
• Teams/Slack, okay just Microsoft Teams, remote work make happier team members and gives people more time, use it.  But encourage camera to be on, email is not a defence (ever), people must IM/chat/ping and call each other.  
• Encourage meeting up, join with social inclusive events at once a month to once a week.  Encourage people to work together online including peer programming.  

Extend Power Automate Logging

1. Power Automate has a Connector to query other Power Automate environments to list, update flows,...
2. PowerShell to examine Flow/Power automate

https://www.cloudsecuritea.com/2019/09/generate-an-overview-of-all-microsoft-flows-with-powershell/

Use postman to Interact with an API - get the bearer token first.

App Insights for Power Platform - Part 11 - Custom Connector

Overview:  Power Automate can set retry policies on custom connectors, Canvas apps using a Custom Connector, does not have any retry configuration.  FYI is the Custom Connector gets a 5.x.x error it shall retry 4 times.  Proven using 500 and 502 errors.  408 (timeout) and 429 (to busy) errors appear to throw 4 times (retry driven by canvas app; using the Custom Connector trigger shall only try once).  

My example:  My Canvas app uses a custom connector, that calls my Azure Function, in turn this calls my APIM, and APIM calls the 3rd party.

My Azure function returns a 500 or 502 or 408 (response timeout) or 429 if the response has not been received in 10 seconds, and I push the http code back to the Custom connector.  I can see the response from the 3rd party is taking +-35 seconds.  I can see from network traces 4 invoked calls that all fail with 408 http response codes.

Result:  The custom connector retries 4 times resulting in my Power App being locked for 40+ seconds.

Possible remediation: 

1. Return a 418 HTTP response code (I am a teapot), my app calls the function using the custom connector once.  So using 418 (also tested with 400 - but 400 is not the right response) errors behaves differently from the 5xx, 408, 429 errors from the API.  

Note: Originally I was caught out as I trigger using the custom connector test rig, this only tries once.  But when called from Power Apps, it shall try four times.  Returning 408 is not a fix.  Returning 418 ensures I only try once, get a better user experience and now I have 418 logs that I add error details to.

2. 3rd party API should not take 35 seconds, improve it.  

3. I could set my timeout on the specific function to 40 seconds, however if the call starts going to 41 seconds, my canvas app will be locked for over 160 seconds.  

4. Go to all API's and if they are fast set the timeout as short as possible so the app does not get locked out while waiting for the 4 responses.

Summary: Examine the 3rd party API's, get them stable and performant and per the agreed SLA's.  If you only want to try once ensure that time outs on the 3rd arty are set to the SLA or if you intercept the request, you can choose the timeout, by examining the API's you can see the optimum time to avoid timeouts and using the 418 response code, the call only happens once.

Series

App Insights for Power Platform - Part 1 - Series Overview 

App Insights for Power Platform - Part 2 - App Insights and Azure Log Analytics 

App Insights for Power Platform - Part 3 - Canvas App Logging (Instrumentation key)

App Insights for Power Platform - Part 4 - Model App Logging

App Insights for Power Platform - Part 5 - Logging for APIM 

App Insights for Power Platform - Part 6 - Power Automate Logging

App Insights for Power Platform - Part 7 - Monitoring Azure Dashboards 

App Insights for Power Platform - Part 8 - Verify logging is going to the correct Log analytics

App Insights for Power Platform - Part 9 - Power Automate Licencing

App Insights for Power Platform - Part 10 - Custom Connector enable logging

App Insights for Power Platform - Part 11 - Custom Connector Behaviour from Canvas Apps Concern (this post)

App Insights for Power Platform - Part 10 - Custom Connector Logging Thoughts

Overview: One of our developers was asking about a log he was struggling to trace, and it took me awhile and a lot of help from the community to truly understand the issue.  My scenario is shown below:

Scenario: I have a Dataverse change triggering a flow, the flow calls a Custom Connector, that in turn calls an Azure Function (that I control).  So the flow fails, and I have used a pattern in the flow to catch the error and log it into Log Analytics.  All good, then I don't see the event where the action calls the function, my function has logging enabled.  I can see I am getting a 401 unauthorized error.  

Initial Hypothesis: The Power Platform use APIM internally to implement Custom Connectors, and there is no access for clients/tenants to see the internal logging/traffic.  Microsoft have provide the ability to use iLogger on the custom connector to log the traffic.  

We have flows that intermittently get a 401, when the flow is manually rerun, the flow works and I can see the traffic coming into the Function.

The failure rate is extremely low and retries almost always fix the issue, and a third try always ensures the transaction goes thru.

Resolution:  Add logging to the custom connector so we can speak with MS support about the issue.  Add alerting to notify support, they can contact the user or chose to rerun the flow. 

Alternative: If I  enable the code, I can override the behaviour and inject C# code to work with the backend, or handle logic such as replacing text,... 

1. In step "4. Code" tab of the custom connector, add the code below:

You can do any C# logic, I'm sending the original request thru and if it doesn't return me a 200, I'm logging it as critical. 

2. Update the connector, go to the next step "5. Test" > "Update Connector" (Tip: follow the steps)

3. Run the "Test operation", open the Response and validate the response body is correct, then open the "Code logs" tab.  If it is blank, re-run the "Update Connector" (irritating but true). 

304 return from the API, which is cached and not a problem, but 400, 500 would be an issue, could also look out for 429s.

Full C# Code:

public class Script : ScriptBase

{

    public override async Task<HttpResponseMessage> ExecuteAsync()

    {       

        this.Context.Request.Method = HttpMethod.Get;

        HttpResponseMessage response = await this.Context.SendAsync(this.Context.Request, this.CancellationToken).ConfigureAwait(continueOnCapturedContext: false);

        Context.Logger.LogTrace("Custom Connector ListBooks called "); 

        if (response.StatusCode == HttpStatusCode.OK)

        {    Context.Logger.LogTrace("Success");      }   

        {    Context.Logger.LogCritical("Critical | " + response);     }

        return response;

    }

}

More Info:

https://learn.microsoft.com/en-us/connectors/custom-connectors/write-code (NB)

https://never-stop-learning.de/logging-in-custom-connector-code/ (NB) The 2nd part of this post on the Alternative , is a rehash of this amazing post - I amended the logic and now I'm wondering is I could write to App Insights using the SDK?

Series

App Insights for Power Platform - Part 1 - Series Overview 

App Insights for Power Platform - Part 2 - App Insights and Azure Log Analytics 

App Insights for Power Platform - Part 3 - Canvas App Logging (Instrumentation key)

App Insights for Power Platform - Part 4 - Model App Logging

App Insights for Power Platform - Part 5 - Logging for APIM 

App Insights for Power Platform - Part 6 - Power Automate Logging

App Insights for Power Platform - Part 7 - Monitoring Azure Dashboards 

App Insights for Power Platform - Part 8 - Verify logging is going to the correct Log analytics

App Insights for Power Platform - Part 9 - Power Automate Licencing

App Insights for Power Platform - Part 10 - Custom Connector enable logging (this post)

App Insights for Power Platform - Part 11 - Custom Connector Behaviour from Canvas Apps Concern

Common Scrum Team improvements

 WIP

Problem: Bugs must not change scope - common to see a bug and it morphs into improvements, other changes.  

Fix: Raise new bug. Don't keep amending and adding new features.

Problem: Team testers/automation testers do not understand the requirement.  Cause by the User Story (US) or bug being ambiguous and Acceptance Criteria (AC)

Fix: Ensure User Stories are in a standard format i.e. "As a <>, I want to <>, so that <>.".  Ensure Gherkin is used for AC (Scenario, Given, When, Then, and preferably more than 1 AC per user story.  Could have: Annotate diagrams to clearly convey artefact information.  Also a narrated recording for bugs.  This could be the person recording the bug, the person that fixed the bug as proof to increase understanding.