App Insights Overview for SaaS logging and tracing

Overview:  App Insights provides independent infrastructure for logging and tracing activities.  It is tightly coupled with Azure services including PaaS.  This allows for consistent scalable logging.  App Insights now stores logs in Azure Log Analytics, these are all under the umbrella of Azure Monitor, 

On a SaaS solution, I am looking for App Insights to log any errors have the ability to log trace information.  I want a unique correlationId (to allow for distributed tracing) on the front end if there is an error so support can identify the exact issue/transactions.  A unique correlationId in the http header allows for identifying a transaction and this is useful for tracing and performance monitoring.  Using the App Insights SDK's and implementing a common logging module is a good idea.  There are two common areas that need call out to ensure the ability to trace transactions:

1. SPA's (Requirement to generate a unique operation/correlationId per operation not per pageview), and
2. Long running operation such as timer jobs or service bus calls.

Support & DevOps:

Having a correlationId allows first line to log the correlationId and quickly follow the request without asking for replication steps.  This context tracing approach is common on newer applications. Third line support has full traceability of an issue to support who can empirically see the perceived performance parts broken down using the correlationId in the header.

Key API's can be continuously monitored for errors and slow down in performance, alerts can be configured around this monitoring. 

Building a first line support tool that displays the errors in a hierarchy, has help scripts and knowledge bases is a good option for streamlining support.

App Insights has live monitoring and also has Kusto query language is useful for monitoring specific queries.

Summary Report for Support

// I'm sure there are nicer ways to write/improve my Kusto, so pls let me let me know where the code can be improved

let dayminus0 = datetime(now);

let dayminus1 = ago(24h);

let dayminus2 = ago(48h);

let result0 = requests

    | where timestamp > dayminus1 and timestamp < dayminus0

    | summarize requestCount=sum(itemCount), avgDuration=avg(duration) by performanceBucket

    | where performanceBucket == "15sec-30sec" or performanceBucket == "7sec-15sec"

        or performanceBucket == "30sec-1-min" or performanceBucket == "1min-2min";

let dayminus1a = ago(24h);

let dayminus2a = ago(48h);

let result1 = requests

    | where timestamp > dayminus2a and timestamp < dayminus1a

    | summarize requestCount1=sum(itemCount), avgDuration1=avg(duration) by performanceBucket

    | where performanceBucket == "15sec-30sec" or performanceBucket == "7sec-15sec"

        or performanceBucket == "30sec-1-min" or performanceBucket == "1min-2min";

let dayminus1b = ago(2d);

let dayminus2b = ago(3d);

let result2 = requests

    | where timestamp > dayminus2b and timestamp < dayminus1b

    | summarize requestCount2=sum(itemCount), avgDuration2=avg(duration) by performanceBucket

    | where performanceBucket == "15sec-30sec" or performanceBucket == "7sec-15sec"

        or performanceBucket == "30sec-1-min" or performanceBucket == "1min-2min";

let resultTemp = result0

    | join kind=inner result1 on performanceBucket 

    | project performanceBucket, ['Today'] = avgDuration, ['Yesterday'] = avgDuration1;

let resultTemp2 = resultTemp;

resultTemp2

| join kind=inner result2 on performanceBucket 

| project

    performanceBucket,

    ['1) Today']= (round(['Today'], -2) / 1000),

    ['2) Yesterday'] = (round(['Yesterday'], -2) / 1000),

    ['3) Two Day ago'] = (round(avgDuration2, -2) / 1000) 

| render columnchart

    with (

    kind=unstacked,

    ytitle="Seconds Taken",

    xtitle="Performance Group",

    title="Ensure the 'Today' bar is not significantly higher than pervious days");

Monitoring:  Azure dashboards are great for monitoring application health and performance.  Easy to customise, make unique dashboards and security is easy to control.  sentry.io monitors API's, I have not used it.  I like all the Azure stuff coming out for testing and I feel continuously running Postman collections and reporting to App Insights is the best way to go.  Azure Dashboards can be limiting, Azure Grafana can be a great alternative/enhancement.  Check out Azure Managed Grafana.

source cloudiqtech

Alerting: I all to often see an overuse of alerting resulting in recipients ignoring a plethora of emails.  I believe in minimising alerts especially via email, and SMS type messaging.  For me, I like to create a dedicate channel for alerting that includes all DevOps members and either notify via a Teams card, and even easier is to email the channel.  This can be broken down further but to start I create a channel for alerting for each DTAP environment.

Note: The default channel setup only allows members of the teams channel to send email so the alerts from Azure monitor using rules won't be accepted.  On the channel, and admin needs to go to the "advance settings" and change the option from "Only members of this Team" and change it the setting to "Anyone can send".

Options:  There are great services for logging so my default tends to be Azure Monitor.  The main players in Application & API observability and monitoring include: 

• Microsoft: Azure Monitor includes Application Insights & Azure Log Analytics
• Dynatrace (really good if you use multicloud) or Dynatrace AWS cloudwatch,  Dynatrace - Saas offering is on AWS.  Can be on-prem.  OneAgent is deployed on the Compute i.e. VM, Kubernetes.  Can import logs from other SIEMs or Azure Monitor, so you can eventually get Azure service logs such as App Service or Service Bus.  Does Full stack and includes code-level and applications and infrastructure monitoring, also can show User monitoring.  Dynatrace offers scalable API's that are sitting on Kubernetes.  "Davis" is the AI engine used to help figure out the problems.  Alerting is solid.  

High-level Architecture

Dynatrace Admin Monitoring

• AWS: Amazon CloudWatch Synthetics
• AppDynamics,
• Datadog (excellent),
• New Relic,
• SolarWinds (excellent)

SolarWinds admin UI from circa 2013/2014 

Dynatrace

Observability in Azure SaaS Solutions

Problem:  Software has many places where errors and tracing is logged to.   Support get an incident, they need to investigate figure out how widespread the issue is and then try patch together various logs to figure out the problem.

Thoughts:

Observability is not a new concept, we need to be able to: 1) view and connect logs & 2) tracing and view metrics & notifications.

Implementing Observability must cover:

CI/CD allows devOps teams to find issues early using Unit testing.   Automated testing on UI.  API automation testing is also great.

Azure offers continious monitoring by performing various API calls to ensure your servie is running and any failures are picked up hopefully before any customers are aware.  You can also be notified of performance slow down, check performance speed between releases.  Which is great for identifying bottlenecks and with the Azure PaaS world, it is easy to increase the processing causing the bottleneck.  

Performance metrics built into the CI/CD and developers work allows us to identify issues early and costs miles less to correct early. 

Security and LINTing in CI/CD also allows us to pickup issues early and correct at a way lower cost.

Instrument you hardware and software, well on Azure you can use App Insights and you have a fantastic instrumenting platform that captures events.  A big reason to use Azure Services for as many of the function pieces in your solution.

Work In Progress ...

TBC Azure App Insights detail, ParentOperationId, Linking operations with a ServiceBus or work process call.

Distribute tracing using Azure Application Insights across Azure SaaS product

Overview:  Building SaaS products using multiple underlying Azure PaaS, and IaaS services with multiple Microservices supporting and calling each other is great.  The issue is we need to be able to trace, debug, and observe the logic flow through multiple Microservice calls.  Distribute Tracing on Azure supports technical players such as devOps teams, developers, support, technical leads and/or architects to find and trace the entire execution to figure our what is/has happened.  Application Insights provides rich functionality on Azure PaaS services.

Distribute Tracing:  A good option for providing consistent traceable logging is to use Application Insights with the Distributed Tracing to trace the flow of each transaction.  The original request generates an Id which is set as the operation_parentId.  Now we can easily follow the execution of a specific operation.

It is fairly easy to tie multiple operations together.  For example, an operation that fires timer jobs, each timer job would be seen as unique operations with their own full trace.  By referencing the original operation when the timer jobs are setup, long running distributed jobs can be tied together.

Thoughts:  Distributed tracing generally catches exceptions from the underlying infrastructure services such as SQL, Azure Functions, App Service on Windows but in code you can add additional tracing information.  The tracing info can be exception based but most of this is picked up anyway or trace base (when an even happens you want to record).

It is a good idea to instantiate the Telemetry client once per service e.g. webAPI and merely call using the same instantiate telemetry object instance throughout each application.

On exception in both client and Server side code write to App Insights telemetry.  Below is the C# server side code snippet:

try

{

    ...

    telemetry.TrackTrace(message, SeverityLevel.Warning, properties);

}

catch (Exception ex)

{

    telemetry.TrackException(ex);

}

More Info:

Distributed Tracing in Azure Application Insights - Azure Monitor | Microsoft Docs

Application Insights API for custom events and metrics - Azure Monitor | Microsoft Docs

App Insights - Website and API Monitoring

Overview:  App Insights has functionality to run scheduled web requests and log the output in App Insights.  There are multiple advantages to this including end to end active monitoring of web sites and API's, and keeping the application warm.

Below I show a simple request to my blog (public website) and the results, Azure refers to this test type as a URL Ping test which is basically a URL HTTP GET request.  

Wait a few minutes and Refresh to see the results:

Very easy way to include a constant check that your API or Website is running.  There is also the options to create "Multi-step web test" using Visual Studio.  You can record the authentication and assert for known response content to build advanced constant monitoring.

Tip: The URL does need to be publicly available.

The content I used to test out the functionality comes from the Microsoft Docs site.

Also see Live Metric Stream that is part of App Insights.

Monitoring using Azure Monitor Dashboards:

• The image above shows a dashboard that can be used to monitor a SaaS applications PaaS Infrastructure.
• It's a good idea to create multiple dashboards and they can show the overview and allow the user to drill into specific areas.
• Internal boards watching key API's, HTTP uptime ping type requests is also a good idea.

Updated: 11 Jan 2023 - Checkly looks like a great monitoring service that works with Playwright for continuous monitoring.  I like to keep all my SaaS on Azure, but Checkly is independent an as it is monitoring.

More Info: 

App Insights MultiStep Tests  Replacement Option for MultiStep Test based on Azure Functions

App Insights - Basic Introduction

Overview:  Azure App Insights is a great platform for collecting logs and monitoring cloud based applications on Azure.  All Azure Services can push logging information into App Insight instances.  This can be errors, usages, performances logging that in turn is easy to query.  There are SDKs for developers that can be used to add custom logging to applications.  I am a big fan of AppDynamics for logging and monitoring but for SaaS and on a new project I'd go with App Insights.

Retention:  App Insights can keep 730 days worth of logs.  For long term storage, "Continuous Export" can be used to push data into storage accounts as soon as it arrives in AppInsights.  Retaining the App Insight logs for 90 days has no additional cost, so the default to store logs should be set to 90 days at least in most situations.

What is logged and what can be logged:  

• All Azure Services can be configured to send service logs to a specific App Insight instance.
• Instrument packages can be added to services to capture logs such as IIS, or background services.  You can pull in telemetry from infrastructure into App insights e.g. Docker logs, system events.
• Custom code can also call the App Insight instance to add logging and hook into exceptions handling.  There are .NET, Node.JS, Python and other SDK's that should e used to add logging, exception capturing, performance and usage statistics.

App Insights has a REST API to query the logs.  The "API Explorer" tool is awesome for querying App Insights online.  

The data below comes from Microsoft Docs.

"What kinds of data are collected?

The main categories are:

• Web server telemetry - HTTP requests. Uri, time taken to process the request, response code, client IP address. Session id.
• Web pages - Page, user and session counts. Page load times. Exceptions. Ajax calls.
• Performance counters - Memory, CPU, IO, Network occupancy.
• Client and server context - OS, locale, device type, browser, screen resolution.
• Exceptions and crashes - stack dumps, build id, CPU type.
• Dependencies - calls to external services such as REST, SQL, AJAX. URI or connection string, duration, success, command.
• Availability tests - duration of test and steps, responses.
• Trace logs and custom telemetry - anything you code into your logs or telemetry."

App Insights creates a hierarchy of requests built up from the operationId, and operation_parentId.

Application Insights is part of Azure Monitor and makes it easy to trace user interaction.  Independent infrastructure for recording issues and tracing.   App Insights in 3 parts. 

• Collect: Track infra/PaaS via instrumentation (throughput, speed, response times, failure rates, exceptions etc.), and via SDK (e.g. JavaScript SDK, C#) to add custom logging and tracing.  Blue boxes
• Store: Stores the data.  Purple Box
• Insights: Alerts, PowerBI, live metrics, REST API.  Green Box

Extending App Insights:

For long running operations like using queues or ESB you will need to tie the operations together, and it's really easy to connect this in a hierarchy using distributed tracing.  

SPA's:  There is a JavaScript SDK but logging on SPA's needs configuration and understanding as not every operation is logged uniquely for tracing.

Smart Detection: automatically tries to quickly warn you of problems/abnormalities and there root cause.

Snapshot Debugger/profiler: VS remote debugging can be hooked to an issue.  Shows execution traces from your live app.

Transaction Search:  Easy way to query and find data or unique info.

Azure Dashboards: Custom KPI dashboard using App Insights &  More Info 

Power Apps Tracing to App Insights Not Working in edit mode

Overview: Power Apps integrates to directly log to App insights.  This post looks at the issues around Tracing in App insights.

Setup & Verify:

App Insights instance Instrument Key Required, Config you Power App to Trace to App Insights, and create a button to test.

The Monitor Tool is fantastic for tracing all outbound traffic, you no longer need to go to the service and check if Power Apps is reaching.  For example I use to have to look at the APIM Azure App logs for custom Connectors.

I can see all my interactions in Power Apps and travelling out.  This is a massive win for Power Apps so giving Tracing from the front end.

Greg Lindhorst, wrote a post on using the Power Apps Monitor Tool for debugging and performance improvement.

Note: Traces written to App Insights don't work in preview.  Verify, see below.

Problem: It normally takes a few minutes (like 2 minutes) to show up in App Insights, it is not showing up after 15 minutes.  Let's see, I've drop the Power Apps team a message and i think it's a bug that has crept in recently.  Today is 10 July 2020.  I've also notice that none of my Session page tracing is showing up in App Insights.

Update: 11 July 2020, the Power Apps behaviour has been on my mind.  I'm in edit mode, and when I publish the app and use it, App Insights logs perfectly.  When in edit mode running the app, even direct traces, no logging into Power Apps.  I did not realise this, but it kind of makes sense.

Resolution: Publish & Run the app, and the Tracing and Power App session tracing shows up in App Insights.

Only when I Run the Published App to my Page Views and Custom Traces get logged in App Insights.

Catch Error in Power Apps and App Insight Logging

Error Handling:
App Insights logging: https://sharepains.com/2019/01/24/powerapps-experimenting-with-error-handling/  Replaced as Microsoft have built in telemetry as of 3 Feb 2020.
https://powerapps.microsoft.com/en-us/blog/log-telemetry-for-your-apps-using-azure-application-insights/

Example Error capturing and tracing to Azure AppInsights:
IfError( // Perform API Call , // Fallback so log here! ,

    Trace("Pauls Unique PowerApp",TraceSeverity.Error, {UserName:User().Email,         Role:gblRole, ErrorMsg:ErrorInfo.Message, ErrorControl:ErrorInfo.Control,         ErrorProperty:ErrorInfo.Property});     Notify("Err message ..." & ErrorInfo.Message); // Display the error on the UI

More detail..

Possible Canvas Apps Error Handling Pattern:

1. Ensure AppInsights key is added to each canvas app
2. Use IfError() to check calls and logic
3. Use the Trace method to write info to App Insights
4. Do I want to enable the Experimental error handling features (great to trace by correlationId)
5. Consider all Power Automate that use Power Apps (ensure you use the V2 Connector)
6. Never use IfError to handle business logic

To Review your App Insights Logging:
Open you Azure Portal > Open your App Insights blade >
Click the "Search" navigation option > Free text entry e.g. "Loyalty PowerApp"

App Insights, finding Traces generated in Power Apps

Monitoring Tool within Power Apps
The Monitor tool in Power Apps is great for debugging and tracing.

Start a monitor on the open Power App.

Monitor Tool - Showing a GET via a custom Connector and the returned response

Function/Code Logging:

Server-side code should log to App Insights or you logging framework.

It is ideal with the Trace within Power Apps explained above to be used in conjunction with 3rd party API calls.

Overview: C# code needs to have logging. If an error occurs an appropriate response must be bubbled up for the next lay

Possible C# Error Handling Pattern:

1. All catch write exception to Log analytics or App insights 
2. Calls to data sources, Azure Services and third party API's and complex logic ideally should be wrapped in a try catch and log the error to App insights using the C# App Insights SDK 
3. The catch blocks ideally return the failed information so the caller code can deal with the logic using the output.  If you don't deal with the returned message, simply log the exception and rethrowing the error (this needs to be a conscious decision on each catch) 
4. Catch specific errors: log, if you don't pass info to caller rethrow the error if applicable (bubble), respond accordingly i.e. catch the specific error and lastly use a catch all. - Heavy, but only add to existing code where this happens often or we are having problems, i.e. be specific
5. Don't use Try, Catch to deal with business logic

Thought: Bubble up means: Code must log exceptions and returns appropriate reply to the caller, if you don't send the appropriate reply rethrow the exception after logging it so the caller has to deal with it.