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World Congress 2025 • Aug 20, 2025 • Session details

In-depth .NET Azure Functions: Flex plan, Isolated mode and performance

Stanislav Lebedenko

The Azure Functions in-process model is ending by .NET 10. Master the new Kubernetes-backed Flex Consumption plan to optimize cold starts and scale event-driven architectures efficiently.

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#1 about 3 min

Transitioning to the Azure Functions flex consumption plan

Microsoft is replacing the legacy in-process model with a Kubernetes-backed isolated worker model.

#2 about 2 min

Understanding the underlying architecture with Project Legion

Awareness of Azure container apps and Kubernetes pods helps troubleshoot deployment and scaling failures.

#3 about 1 min

Optimizing container sizes for platform portability

Smaller container footprints allow developers to package and deploy functions on any on-premise Kubernetes instance.

#4 about 3 min

Navigating isolated worker support and shared platform nuances

The flex consumption tier shares its infrastructure with Azure container apps and strictly requires the isolated worker model for .NET 8.

#5 about 4 min

Managing virtual network integrations and HTTP trigger timeouts

Limited IP address ranges and strict timeout rules cause unexpected network and processing failures during sudden traffic spikes.

#6 about 3 min

Analyzing memory sizes and scaling behavior in flex consumption

Smaller half-gigabyte instances achieve significantly faster parallel scaling compared to larger memory configurations.

#7 about 4 min

Comparing performance between flex and classic consumption plans

The legacy consumption tier running on older hardware struggles with CPU overload during rapid request spikes unlike the updated flex infrastructure.

#8 about 2 min

Embracing the isolated process model for future optimizations

Adopting the standard .NET application structure enables better feature alignment and prepares projects for upcoming framework updates.

#9 about 3 min

Maximizing scale speeds with minimal memory allocations

Provisioning half-gigabyte instances provides the fastest deployment response for handling sudden massive traffic surges.

#10 about 3 min

Evaluating native AOT and ReadyToRun compilation strategies

While native AOT lacks proper support, ReadyToRun offers negligible cold start improvements that are overshadowed by platform-level optimizations.

#11 about 3 min

Tuning application dependencies and host concurrency settings

Removing unnecessary packages and adjusting host.json concurrency thresholds balances processing performance with infrastructure costs.

#12 about 2 min

Automating performance testing and containerizing Azure Functions

External load testing tools provide more reliable metrics than built-in optimizers when preparing function code for Kubernetes migration.

#13 about 2 min

Monitoring SDK updates and mitigating platform limits

Tracking GitHub issues helps avoid broken package releases while combining hosting plans circumvents restrictive subscription compute caps.

Matching moments

2:05 min

Azure functions hosting plans and migration challenges

Stas Lebedenko Stas Lebedenko · World Congress 2026 Europe

2:59 min

Adopting the .NET isolated worker model for functions

Stas Lebedenko Stas Lebedenko · World Congress 2026 Europe

2:35 min

Transitioning from pure code functions to serverless containers

Daniel Oh Daniel Oh +1 · World Congress 2024

2:54 min

Comparing serverless functions against traditional monolithic architectures

Developersteve · LIVE

3:11 min

Running microservices on Azure Container Apps

Matthias Falkenberg +1 · World Congress 2022

2:16 min

Resolving resource scaling challenges with dynamic serverless deployments

Daniel Oh Daniel Oh +1 · World Congress 2024

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