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

Confused about Azure messaging? In this episode, Azure Architect Bhanu Prakash explains Event Grid vs Event Hub vs Service Bus, helping developers and architects choose the right Azure service for event-driven and serverless systems.

Learn when to use Event Grid for events, Event Hubs for telemetry and streaming, and Service Bus for reliable enterprise messaging — with real-world Azure architecture examples in under 5 minutes.

Event Grid, Event Hub, and Service Bus are some of the most misunderstood services in Azure — and treating them as interchangeable is a common reason event-driven systems fail in production.

In this short, focused episode, Bhanu Prakash (Azure Architect & Developer Advocate) explains Azure messaging the right way, using a clear mental model that helps developers and architects confidently choose between Event Grid, Event Hubs, and Service Bus.

You’ll learn:
• The real difference between events vs messages — and why it matters
• When to use Event Grid for reactive notifications and integrations
• When Event Hubs is the right choice for telemetry and streaming data
• When Service Bus is essential for reliable, ordered, enterprise messaging
• How throughput, ordering, retries, and guarantees affect architecture decisions

This episode cuts through Azure documentation noise and focuses on real-world design trade-offs, not demos or theory. Perfect if you’re building APIs, serverless systems, IoT pipelines, or event-driven architectures on Azure.

If you’ve ever dealt with lost messages, broken ordering, scaling issues, or the wrong messaging choice slowing your system down — this 5-minute episode will reset how you think about Azure messaging.

Chapters
00:00 – 💣 Logic Apps vs Azure Functions: Both Are Serverless, Right?
00:01:12 – 🧩 #1 Decision Paralysis: Why Azure Makes It Confusing
00:01:48 – ❄️ #2 Cost Pitfalls: The Truth Behind Azure Billing
00:02:26 – 🔥 #3 Debugging & Monitoring: Visual vs Code Insights
00:02:56 – ⚡ #4 Orchestration & Workflow Complexity
00:03:27 – 💎 #5 Security & Networking: The Hidden Gaps
00:03:57 – 🧱 #6 Developer Experience & CI/CD
00:04:29 – 🐳 #7 Side-by-Side Comparison
00:06:37 – 💰 #8 Decision Framework: When to Code, When to ClickAzure Logic Apps and Azure Functions are both serverless—but once you step into production, they behave like completely different worlds. If you’ve ever wondered which one to choose for APIs, integrations, automation, or event-driven workloads, this episode is your deep-clarity guide. In just eight minutes, Bhanu (Azure Architect & Developer Advocate) breaks down the real-world differences no documentation page will tell you.

This episode goes far beyond “low-code vs code-first.” Instead, it exposes the subtle architectural trade-offs that impact cost, performance, observability, governance, and operational reliability. You’ll learn how Logic Apps can become expensive from connector calls and loops, why Azure Functions offer more control but demand stronger engineering discipline, and where both services shine when used together.

🧠 What You’ll Learn

• The true differences between Logic Apps and Functions in real production systems
• How consumption-based billing works behind the scenes—and how to avoid surprise invoices
• Why Logic Apps offer powerful visual debugging, while Functions give you full code-level insights
• When workflow automation becomes spaghetti in Logic Apps—and when Function orchestration explodes in complexity
• The networking, identity, and security gaps developers overlook
• The CI/CD challenges of Logic Apps compared to the smooth pipelines of Functions
• A practical, reusable decision framework for choosing the right serverless tool

🚀 Who This Episode Is For

• Developers building APIs, event processors, or integration workflows
• Architects designing scalable, secure cloud backends
• DevOps engineers focused on observability, deployment automation, and cost control
• Technical leads evaluating serverless choices for reliable enterprise systems

If you’ve ever dealt with connector-heavy bills, messy workflow dependencies, retry storms in Functions, or deployment blockers in Logic Apps, this episode will give you clarity and confidence.

🔎 Why This Comparison Matters

Both services promise serverless simplicity, but choosing the wrong one can:
• Inflate monthly costs 💸
• Slow down release cycles 🐢
• Break monitoring and troubleshooting workflows 🔍
• Complicate networking and identity design 🔐
• Misalign with your DevOps strategy 🚧

By the end, you’ll know exactly when to choose code (Functions), when to choose clicks (Logic Apps), and when a hybrid approach gives you the best architectural balance.

👩‍💻 For Developers & Architects

This breakdown gives you practical design guidance:
• When to use Durable Functions for long-running workflows
• How to build reliable, secure Logic Apps
• Designing event-driven architectures that scale predictably
• Balancing low-code speed with code-first control

If you build or maintain Azure serverless systems, this is your concise masterclass.

🎓 About Azure Counsel

Azure Counsel simplifies complex Azure architecture through practical, visual explanations. From serverless design patterns to cost optimization, monitoring, and DevOps pipelines, we help developers and architects build cloud systems that are scalable, secure, and maintainable. Subscribe for more deep-dive Azure insights, real-world patterns, and step-by-step architecture guidance.

Are your Azure Functions silently failing, scaling unpredictably, or breaking due to hidden configuration issues?
This in-depth podcast walks developers and cloud architects through the 12 most dangerous and commonly overlooked Azure Functions pitfalls—specifically in Triggers, Bindings, Scaling, Message Processing, Observability, and Serverless Architecture.

Designed for real-world production environments, this session reveals how small mistakes in bindings, host.json, schema design, Event Hub partitions, Service Bus sessions, and Cosmos DB leases can cause massive reliability issues in distributed systems. Whether you're building event-driven microservices, data ingestion pipelines, automation workflows, or mission-critical enterprise serverless apps, this podcast brings clarity to what really goes wrong behind the scenes in Azure Functions and how to fix it.

• Wrong Binding Types — why Functions fail silently when your binding direction or type mismatches the trigger
• Schema Coupling Mistakes — how tightly coupled payload shapes break serverless workflows
• Service Bus Poison Message Pitfalls — preventing dead-letter loops that halt entire pipelines
• Over-Reliance on Bindings — when too much magic hides critical operational control
• Misconfigured host.json — scaling failures caused by wrong batch sizes, concurrency, or prefetch
• Missing Service Bus Sessions — ordering, locking, and workflow execution breaks
• Event Hub Partition Misalignment — Why your functions under-scale or over-load partitions
• Cosmos DB Change Feed Lease Issues — how bad lease configuration stops change feed processing
• Authentication Pitfalls — MSI vs connection strings vs Azure AD misalignment
• Binding Expression Failures — runtime surprises caused by naming mismatches or invalid patterns
• Durability Assumptions — when functions are not durable the way you believe they are
• Monitoring Blind Spots — hidden errors in Application Insights that developers never notice

Each pitfall is explained with clear examples, production impact, and the exact fix.

This session is crafted for:

• Azure Developers building Functions in C#, .NET, Python, or Node

• Cloud Architects designing event-driven or serverless systems

• Solution Leads responsible for reliability, scaling, and performance

• Engineers preparing for AZ-204 or AZ-305

• Anyone managing Azure Event Hub, Service Bus, Cosmos DB, or Storage triggers at scale

  
  

Azure Functions appear simple, but production failures are almost never caused by code—they stem from hidden platform behaviors, misconfigured bindings, and incorrect assumptions about how serverless triggers operate.
This episode demystifies those layers and gives you the operational clarity to run Functions reliably at scale.

If you're building enterprise-grade serverless applications, this is a must-listen.

🚀 Who This Podcast Is For

This session is crafted for:

• Azure Developers building Functions in C#, .NET, Python, or Node

• Cloud Architects designing event-driven or serverless systems

• Solution Leads responsible for reliability, scaling, and performance

  
  

🛠️ Key Technical Themes Covered

Azure Functions Triggers & Bindings (Event Hub, Service Bus, Cosmos DB, Storage)

• Durable and non-durable serverless patterns

• host.json tuning for scale-out reliability

• Poison message handling & message ordering

• Event-driven architecture in Azure

• Real-world telemetry, monitoring & diagnostics in Application Insights

🎧 Why This Episode MattersAzure Functions appear simple, but production failures are almost never caused by code—they stem from hidden platform behaviors, misconfigured bindings, and incorrect assumptions about how serverless triggers operate.
This episode demystifies those layers and gives you the operational clarity to run Functions reliably at scale.

Are you confused about how your Azure Function runs or where the data comes from? In this episode, Bhanu from Azure Counsel takes you from zero to hero by breaking down the core pillars of Azure Functions — Triggers, Input Bindings, Output Bindings, and the runtime — through real-world examples, production pitfalls, and architectural insights.

If you’ve ever wondered:

• “Why did my Function run when I didn’t call it?”

• “Where did this data suddenly come from?”

• “Why didn’t my output reach Blob Storage or Cosmos DB?”

This episode is your end-to-end blueprint for mastering Azure Functions development.

🎯 What You’ll Learn:

• How Azure Functions execute behind the scenes

• The 4 core pillars: Triggers, Runtime, Input Bindings, Output Bindings

• Deep dives into Timer, HTTP, Blob, Event Grid, Cosmos DB, Service Bus, Event Hub, and SignalR triggers

• How triggers connect to event sources like Event Hub, Service Bus, and Cosmos DB

• How bindings simplify integration while revealing critical production risks

• Common mistakes developers make assuming binding durability

• Practical fixes: retries, monitoring, and correlation best practices

💡 For Azure Developers & Architects:
Whether you’re preparing for Microsoft AZ-204, building serverless APIs, or deploying event-driven architectures, this session covers everything you need to understand triggers and bindings in production environments.

👨‍💻 Who This Episode Is For:

• Azure Developers building event-driven or API-based solutions

• .NET, Python, Node.js, and C# developers deploying to Azure Functions

• Cloud Architects designing serverless, event-based microservices

• DevOps professionals optimizing monitoring, retries, and scaling in production

• Anyone learning Azure Cloud Application Development or Serverless Computing

🧭 Key Takeaways:

• Understand Trigger–Binding orchestration inside Azure Functions

• Avoid silent failures from transient issues or misconfigured bindings

• Implement retry policies, correlation IDs, and diagnostics for production observability

• Learn scaling behaviors of each trigger type in Azure Functions v4

• Discover integration with Event Grid, Service Bus, and Event Hub

🔧 Technical Focus Areas:

• Azure Functions in C#, Python, and Node.js

• Function App deployment, monitoring, and logging best practices

• Integration with Azure Service Bus, Event Hub, and Cosmos DB

• Azure serverless development & cloud-native architecture

• Durable Function design patterns for enterprise-grade systems

🎥 Watch the full visual tutorial on YouTube: https://www.youtube.com/@azurecounsel

Choosing the wrong Azure Functions hosting plan can quietly drain your time, budget, and performance — without you even realizing it. In this episode, Bhanu from Azure Counsel breaks down the hidden truths behind Azure Functions hosting plans — and why both beginners and architects often get this decision wrong.

You’ll learn how each plan — Consumption, Premium, Dedicated, Flex Consumption, and Container Apps — behaves under pressure, and how small differences in scaling, isolation, and cold starts can decide whether your app thrives or struggles.

🎯 In this episode, you’ll discover:

• What really happens when your Function App runs on the wrong hosting plan

• The three hidden forces that control Function App performance and scalability

• What Microsoft doesn’t tell you about cold starts, warm instances, and automatic scaling

• The truth about Flex Consumption Plan — and when it beats both Consumption and Premium

• The trade-offs between Premium, Dedicated, and Container App plans

• How to choose the right plan for long-running jobs, VNET integration, and compliance

• Microsoft’s latest update on Flex vs. Consumption — and what it means for your next deployment

💡 Why This Matters
Most developers assume Azure Functions “just scale automatically.”
The reality? Every hosting plan behaves differently under pressure — with unique limits on timeouts, performance, and networking. Pick the wrong one, and you’ll face:

• Long cold starts that slow down your users

• Hidden timeout errors in production workflows

• No access to private VNETs or secured endpoints

• Cost surprises that rival a full VM deployment

This episode gives you a decision framework for choosing the right hosting plan — one that saves you hours of debugging and keeps your Functions fast, resilient, and cost-efficient.

👂 Perfect For:

• Cloud architects designing serverless backends

• Developers frustrated by Azure Function cold starts or scaling issues

• DevOps teams migrating from App Services or VMs to serverless

• Anyone running production workloads on Azure Functions who wants performance clarity

🧠 What You’ll Take Away
You’ll walk away with a mental model to instantly understand which plan fits your use case — and how to adjust scaling, timeout, and cost trade-offs for real-world workloads.

🧭 Next Episode Preview:
In the next Azure Counsel episode, we’ll go deeper into Azure Function triggers and bindings — the real engine behind event-driven architecture. You’ll learn how to connect your code to queues, events, and data sources for scalable automation.

🎥 Watch the full tutorial with visuals and demos on YouTube:
👉 https://www.youtube.com/@azurecounsel