Microsoft has set a hard deadline: AzureFunctions In-Process will retire in November 2026.
If your production apps are still running on the legacy runtime, they are officially on a countdown.

In this episode, Bhanu (Azure Architect with 15+ years of experience) shares the real-world blueprint used to migrate 120+ Azure Function Apps from the In-Process model to the .NET 8 Isolated Worker model with zero downtime and zero production chaos.

This is not just a framework upgrade — it is a fundamental shift in the execution model.
Moving to Isolated Worker separates your code from the Functions Host process, giving you full control over dependency injection, middleware, and applicationlifecycle — but it also breaks long-standing assumptions around triggers, bindings, and observability.

🚀 What You’ll Learn

• How to audit your Azure tenant and instantly find every In-Process Function App using Azure Resource Graph (KQL)
• Why simply changing the Target Framework to .NET 8 causes massive build failures
• How the gRPC boundary between the Functions Host and Worker Process changes execution and telemetry
• How to build a shared “Golden Template” using global middleware for logging, correlation IDs, and exception handling
• Step-by-step refactoring for HTTP, Service Bus, and Event Hub triggers
• Why output bindings should be replaced with explicit SDK-based publishing
• How GitHub Copilot App Modernization can automate up to 60% of the migration work
• How to deploy 100+ Function Apps safely using staging slots and controlled rollout

🛠️ The Golden Template Strategy

Managing dozens of Function Apps individually leads to configuration drift.
This episode explains how to centralize middleware and behavior using a shared NuGet library:

• HTTP pipeline for authentication and authorization
• Messaging pipeline for retries and dead-letter handling
• Streaming pipeline for batch parsing and partition awareness

📦 Extension Replacement Guide

Legacy WebJobs packages must be replaced with Worker SDKs:

• Microsoft.Azure.WebJobs →Microsoft.Azure.Functions.Worker
• Microsoft.Azure.WebJobs.Extensions.ServiceBus →Microsoft.Azure.Functions.Worker.Extensions.ServiceBus

☁️ Hosting After Migration

Migration is the perfect time to modernize hosting.
We discuss why Flex Consumption solves cold-start issues and why the classic Consumption plan is approaching its own lifecycle limits.

⚙️ Why This Matters

In the In-Process model, the host handled the “magic.”
In the Isolated Worker model, the magic is yours to manage.

Mental model failures are the #1 cause of outages during this migration.
If you don’t understand how gRPC boundaries affect telemetry or how host.json sampling can silently drop critical exceptions, you will fail to detect production incidents before customers do.

This episode gives you an architectural blueprint — not just code — so you migrate with confidence, not panic.

👨‍💻 Who This Episode Is For

• Cloud Architects designing high-throughput serverless systems
• Senior .NET developers modernizing legacy Function Apps
• DevOps and Platform Engineers responsible for reliability and observability
• Migration teams moving large Azure estates before the 2026 deadline

🎓 About Azure Counsel
Azure Counsel decodes the inner workings of cloud architecture for professionals.
We skip the “Hello World” basics and focus on production-grade serverless, messaging, and API design.

You deployed your Azure Function…
But now your logs are missing, out of order, or so vague they’re useless.
Worse — your Application Insights bill is exploding while you’re still debugging blind in production.

Sound familiar? 😅

In this episode, Bhanu from Azure Counsel breaks down the exact logging architecture used to build traceable, distributed Azure Functions systems — without burning money on telemetry.

This is not about Console.WriteLine.
It’s about structured logging, correlation IDs, and cost-aware telemetry design for real production workloads.

⚠️ Critical for 2026 and Beyond
With the November 10, 2026 retirement of the Azure Functions In-Process model, your logging strategy must change.
This episode focuses on ILogger + dependency injection for the Isolated Worker model and how logging behavior differs from the old runtime.

🎯 What You’ll Learn:

• How to correctly configure APPLICATIONINSIGHTS_CONNECTION_STRING for local and production

• Why most logs disappear or arrive out of order

• How to tune log levels globally and per function to suppress noise

• How Azure drops telemetry when sampling is misconfigured

• How maxTelemetryItemsPerSecond can cut 90% of your ingestion cost

• When to use LogInformation, LogWarning, and LogCritical

• How to centralize logging using a helper class

• How to inject Correlation IDs for distributed tracing

• Why your error logging strategy defines production stability

🧠 Key Takeaways:

• Pay for insight, not noise

• Preserve statistical accuracy while reducing cost

• Prevent silent outages caused by sampling misconfiguration

• Build traceable request flows across microservices

• Stop debugging blind in production

👨‍💻 Who This Episode Is For:

• Cloud Architects designing high-volume telemetry systems

• Senior Developers building Azure Functions with C#

• DevOps Engineers managing Log Analytics cost and alerts

• Teams migrating to .NET 8/10 Isolated Worker

• Engineers tired of runaway Application Insights bills

🔧 Technical Focus Areas:

• Azure Functions v4 & Isolated Worker model

• Application Insights & Log Analytics

• host.json sampling and aggregator settings

• Structured logging with ILogger

• Distributed tracing & Correlation IDs

If your Azure Functions have ever:
• lost logs
• flooded Application Insights
• missed exceptions
• or cost more to monitor than to run

This episode gives you the logging blueprint to fix it permanently.

🎥 Watch the full walkthrough on YouTube:

https://youtu.be/nDR_LwzS3U8

Most developers assume Azure Functions “just scale automatically.”
The truth? One wrong configuration setting can silently flood your telemetry, expose secrets, overload downstream systems, or trigger a midnight production outage.

In this episode, Bhanu from Azure Counsel breaks down the 5 most dangerous configuration mistakes that cripple real-world Azure Functions deployments — and shows you how to fix them using production-grade patterns.

This is not a beginner tutorial. It’s a practical guide for engineers who care about security, observability, concurrency control, and cost stability.

⚠️ Important for 2026 and beyond
With the November 10, 2026 retirement of the Azure Functions In-Process model, migrating to the Isolated Worker model is no longer optional. This episode focuses on the configuration patterns you must adopt to survive that transition safely.

🎯 What You’ll Learn:

• Why default Azure Functions settings are unsafe for production

• How misconfigured host.json can destroy performance and inflate Application Insights costs

• Why hardcoding connection strings is a security risk

• The correct way to use Managed Identity + Key Vault references

• When to use static vs. dynamic concurrency

• How to tune Service Bus and Event Hub triggers without melting downstream services

• How to prevent HTTP triggers from causing 429 storms

• Why logging to disk (fileLoggingMode) hurts performance

• How to design layered configuration for dev vs. prod

🧠 Key Takeaways:

• Control telemetry volume using metrics.aggregator tuning

• Implement structured logging instead of file-based logging

• Regulate parallelism using trigger-specific limits

• Protect backend systems with concurrency governance

• Build resilient deployments with feature flags and slots

👨‍💻 Who This Episode Is For:

• Cloud Architects designing enterprise serverless systems

• Senior Developers preparing for AZ-204 or AZ-305

• DevOps Engineers optimizing latency and cost

• Teams migrating legacy In-Process Functions to .NET Isolated Worker

• Engineers tired of “it worked in dev” failures

🔧 Technical Focus Areas:

• Azure Functions v4 (Isolated Worker model)

• Service Bus & Event Hub trigger tuning

• Cosmos DB Change Feed lease optimization

• Application Insights sampling & logging strategy

• Infrastructure as Code (Bicep & Terraform)

If your Azure Functions have ever:
• suddenly slowed down
• blown up your telemetry bill
• exposed secrets
• overwhelmed downstream systems
• or failed only in production

This episode gives you the mental model and configuration blueprint to stop those failures before they happen.

🎥 Watch the full visual walkthrough on YouTube:
https://youtu.be/1Y4J6YSqy08