Synapse Serverless varchar(8000): Fixing Strings for Spark and Power BI
Why Synapse serverless SQL infers strings as varchar(8000), why Spark-created lake tables behave differently, and where Power BI string contracts belong.
57 articles
Why Synapse serverless SQL infers strings as varchar(8000), why Spark-created lake tables behave differently, and where Power BI string contracts belong.
AI applications often have variable load patterns with periods of high demand followed by quiet periods. Container Apps scales to zero during idle times…
Configure appropriate timeout settings for AI operations and implement retry logic for transient failures. Consider using premium plans for…
Use consumption-based billing to pay only for actual inference time. Implement caching for repeated queries and batch similar requests to amortize cold…
Use spot instances for non-critical workloads, implement request batching for throughput optimization, and configure appropriate scale-to-zero policies.…
Understanding serverless ai is essential for production AI systems. Here's what you need to know.
Event-driven AI enables responsive, intelligent systems. Start with simple event handlers and evolve to complex orchestration as needed.
Serverless fine-tuning removes the infrastructure barrier to custom model development. Start experimenting with your domain-specific use cases today.
Serverless model serving eliminates infrastructure management while providing cost-effective, scalable ML inference. This guide covers implementing…
A comprehensive guide to building serverless AI solutions using Azure Functions and Azure Cognitive Services.
Jobs in Container Apps provide flexible batch processing capabilities. Tomorrow, I will cover Dapr 1.11 updates.
Container Apps provides a powerful, serverless container platform. Tomorrow, I will cover Jobs in Container Apps in more detail.
Cache-aside, write-through, write-behind and refresh-ahead with Azure Cache for Redis in .NET 7 isolated Azure Functions, and when each one is the wrong choice.
The promise of serverless has largely been fulfilled: Pay only for what you use No server management Automatic scaling Faster time to market Most…
Container Apps sits between App Service and AKS: Simpler than AKS : No cluster management, no node pools More flexible than App Service : Any container, any…
The isolated worker process model separates your function code from the Azure Functions host: Version independence : Use any .NET version, including .NET 7…
Azure SQL bindings simplify serverless database applications significantly.
Create a new Function App with Node.js 18: Update your configuration: Azure Functions v4 introduces a new programming model: Use the built in fetch without…
Build 2022 brings several enhancements: Stable APIs using Azure Functions Enterprise edge support Improved authentication options Split environment…
Unlike AKS where you manage the cluster, Container Apps abstracts away the infrastructure. You focus on your containers while Azure handles scaling, load…
Serverless SQL charges based on data processed. Optimization reduces both cost and query time.
A closer look at the Azure Container Apps preview API: how revisions, KEDA scale rules and per-app Dapr components behave, and where the preview falls short.
Serverless in 2021 proved it's not just for simple APIs. Complex, stateful, event-driven applications are running successfully in production. The technology…
Azure Container Apps provides a sweet spot between serverless functions and full Kubernetes - the power of containers without the operational complexity of…
In-Process: Functions run in the same process as the Functions host Isolated Worker: Functions run in a separate worker process
Synapse Serverless SQL Pool is the query engine that turned Azure Data Lake into an ad-hoc analytics platform—you write T-SQL, point it at files in ADLS…
Virtual nodes in AKS enable pods to run on Azure Container Instances rather than on VM-based node pool nodes—useful for burst workloads that spike…
Serverless is perfect for dev/test environments, infrequently used applications, and workloads with predictable quiet periods. For consistent…
Create a scheduled function: Common CRON patterns: Implement patterns for tasks that may exceed timeout: Ensure single instance execution: Configure…
Queue-triggered Azure Functions are the pattern I recommend most often for decoupling work that doesn't need to happen synchronously. The model is simple…
The Azure Functions Premium plan is the hosting option I reach for as soon as two of these three conditions are true: the function needs to connect to a…
Feature Consumption Premium Scaling 0 to 200 instances 1 to 100 instances Cold starts Yes No (pre warmed) Max timeout 10 min (default 5) 60 min (default 30)…
Azure Container Apps combines the simplicity of serverless with the power of containers. With built in Dapr integration, KEDA scaling, and revision…
Durable Entities are addressable units of state that process operations one at a time. Think of them as lightweight actors - each entity has a unique…
The magic happens through the Durable Task Framework, which handles state persistence, checkpointing, and replay automatically.
We had a Cosmos DB Serverless conversation at the end of 2020 and I'm returning to it because the experience of using it in actual development over two…
ACI is the container service I reach for when I need a container running in under two minutes and I don't want to explain what a node pool is. Per-second…
How auth really works in the Azure Static Web Apps preview: five managed providers, invitation-based roles, routes.json rules and hard limits.
The new Logic App (Preview) resource runs workflows on the Azure Functions runtime: what changes, what's missing, and how I'd pilot it before GA.
How to work out whether Azure Cosmos DB serverless (preview) beats 400 RU/s of provisioned throughput, with the break-even maths and a way to measure it.
What the .NET 5 isolated worker preview for Azure Functions looks like in January 2021, what it costs you today, and when to stay on .NET Core 3.1.
Cosmos DB Serverless: NoSQL without the commitment.
Functions has supported "any language" via the worker model for a while, but custom handlers are the cleaner option when your runtime isn't on the supported…
Logic Apps is the first thing I build in when a client says "we need to integrate with Salesforce, then push to SAP, then notify the team in Teams."…
The first Azure Function project I shipped used static everything. Static config, static SQL helpers, static logger. It worked—until I tried to write a unit…
Cold starts on Consumption plan kill credibility. I've watched a perfectly good HTTP-triggered function get blamed for "the API being slow" because the…
Static Web Apps with the integrated Functions backend is the deployment story I keep recommending for small SaaS dashboards and internal tools. Static…
Bindings let you focus on business logic, not plumbing.
Event Grid enables reactive, event-driven architectures at scale.
Function chaining, fan-out/fan-in, human interaction, and eternal orchestrations — Durable Functions exposes a small set of patterns that cover most…
A second Synapse-preview note, on what I think is the genuinely new idea in the platform: serverless SQL. Point T-SQL at parquet, CSV, or JSON in your data…
.NET on Functions is the default story Microsoft tells, but in practice the serverless workload that lands on my desk most often is a Python data scientist…
For "I need to run this container for an hour to crunch some data," ACI is the right answer roughly nine times out of ten. AKS is overkill, App Service for…
Using Durable Functions 2.x entities to hold per-SKU stock counts: when to signal and when to call, how reads work, and where an entity is the wrong tool.
How Durable Functions orchestrators replay from history, the determinism rules that follow, and how to build retries and compensation into a C# workflow.
When to pick Event Grid over Service Bus or Event Hubs, and how to publish, handle, filter and dead-letter events so failed deliveries aren't silently lost.
A practical Azure Functions v3 and .NET Core 3.1 setup: pinned packages, dependency injection, Polly retries, deployment, and the plan limits that bite.