104 articles
Item-level CI/CD in Microsoft Fabric is a settled capability. The unsolved problem is source of truth and tenant governance as code — the workspaces, capacity, domains, tenant settings, connections, and roles that Git integration does not manage. A blueprint for tenant-as-code.
This is how most AI deployments start. Here's how to fix it. Traditional apps: request comes in, response goes out. Monitor latency, errors, throughput. Done.
For an app with 100 users. Push to main. App deploys. Done. Don't add any of this on day one.
Spent 3 years with Azure DevOps. Last year switched to GitHub. Here's my honest comparison.
IaC is a skill that compounds. These practices become second nature and save countless hours of debugging and recovery.
Kubernetes cost optimization is continuous. Review these metrics weekly and adjust based on actual usage patterns.
While linters catch syntax issues, AI reviewers understand context, identify logical errors, suggest architectural improvements, and explain complex code…
LLM outputs vary between runs and model versions. Testing must focus on behavioral properties rather than exact string matching, while still catching…
LLMs present distinct operational challenges: non-deterministic outputs, prompt sensitivity, context window management, and the difficulty of defining…
Claude 3.5 Sonnet has become my go-to model for automated code review workflows. Its exceptional ability to understand context across large codebases makes…
Comprehensive observability enables continuous improvement of AI applications.
Robust AI testing combines deterministic checks with AI-powered evaluation.
Observability transforms AI agents from black boxes into understandable systems. Combine metrics, logs, and traces to gain complete visibility into agent…
Implementing CI/CD for Microsoft Fabric ensures reliable, repeatable deployments of analytics artifacts. This guide covers building end-to-end deployment…
Microsoft Fabric's Git integration brings modern version control practices to analytics. This guide covers setting up and using Git with Fabric workspaces.
Deploying AI features to production requires careful risk management. Gradual rollouts help identify issues early while minimizing blast radius.
Feature flags provide fine-grained control over AI features, enabling safe deployments, quick rollbacks, and targeted releases. This guide covers…
Production search indexes require operational discipline. From index versioning to blue-green deploys, these are the ops patterns I use to avoid downtime…
Platform engineering is the pragmatic answer to scale: provide golden paths, self-service APIs and guardrails so teams move quickly without repeating…
Deployment Pipelines provide controlled, auditable content promotion across environments. Tomorrow, I will cover Fabric Monitoring.
Git integration in Fabric is something I've been waiting for since the first preview. Power BI's lack of proper version control has been a persistent…
Deployment Environments enables platform engineering teams to provide governed self-service infrastructure to developers. Tomorrow, I will cover Azure…
Dev Box simplifies developer onboarding and ensures consistent development environments. Tomorrow, I will cover Azure Deployment Environments.
Commit messages: {chr(10).join(f'- {c}' for c in commits)} response = await self.client.chatcompletion( model="gpt-4", messages=[{"role": "user", "content"…
Containerization and Kubernetes: Lessons Learned in 2022
Observability in 2022 moved beyond simple monitoring to true understanding of system behavior. OpenTelemetry became the standard for instrumentation. SLOs…
IaC maturity is a journey, not a destination. Start where you are, establish good practices early, and continuously improve. The goal is infrastructure that…
Platform engineering is the practice of building and maintaining internal developer platforms (IDPs) that enable self-service capabilities for development…
The four key metrics gained mainstream adoption: Security integrated earlier in the pipeline: IaC practices became more sophisticated: Three pillars…
Lift and shift migrations VMs in the cloud Traditional architectures Using managed services Basic automation Some containerization Microservices…
Feature Azure DevOps GitHub Actions YAML Config azure pipelines.yml .github/workflows/ .yml Hosted Runners Microsoft hosted GitHub hosted Self hosted Yes…
Azure DevOps provides a comprehensive platform for enterprise DevOps with robust security and governance features.
Azure DevOps provides enterprise-grade DevOps capabilities with deep Azure integration.
Proper artifact management enables efficient multi-job pipelines and deployment workflows.
Custom actions enable sophisticated automation tailored to your specific workflows.
Composite actions bridge the gap between simple step sequences and full custom actions.
GitHub now offers larger hosted runners for more demanding workloads. Enforce workflows across all repositories in an organization.
GitHub Universe 2022 promises significant advances in developer experience and platform capabilities.
DACPACs provide reliable, repeatable database deployments for enterprise applications.
Database Projects bring modern DevOps practices to database development.
Inside the debug container: Ephemeral containers enable live debugging of production pods without disruption, making troubleshooting faster and safer.
Handle node failures gracefully: Configure node shutdown behavior: Control traffic routing for services: Track batch job progress: Stricter API validation:…
Azure Deployment Environments addresses these challenges with templated, self-service infrastructure.
ALM Toolkit is essential for Power BI DevOps: Visual schema comparison Controlled deployments Integration with CI/CD Environment management ALM Toolkit on…
Deployment Pipelines bring enterprise ALM to Power BI: Controlled content promotion Environment specific configurations Audit trail of deployments…
The Power BI REST API enables: Automated content deployment Scheduled refresh management Administrative automation Custom tooling and integrations REST API…
Proper ALM ensures Power Platform solutions are reliable, maintainable, and can be safely deployed across environments.
Bicep in 2022 is production-ready and the best choice for Azure infrastructure as code.
GitHub Advanced Security transforms security from a gate to a continuous process integrated into your development workflow.
Azure DevOps in 2022 offers a mature, flexible platform for any DevOps workflow.
The future is developers who can move fast within safe guardrails. Self-service infrastructure makes that possible.
IDPs in 2021 became the way to scale DevOps practices. They encode organizational knowledge into platforms that enable consistent, secure, and fast software…
Platform engineering is about creating golden paths - paved roads that make it easy for developers to do the right thing. It's infrastructure as a product…
DataOps in 2021 matured from concept to standard practice. Teams that adopted these practices delivered faster and more reliably than those stuck in manual…
FinOps in 2021 grew from a niche practice to an organizational capability. The tools exist; success requires culture change and executive support.
1. Declarative : Desired state is expressed declaratively 2. Versioned and Immutable : Git stores the canonical desired state 3. Pulled Automatically :…
IaC maturity in 2021 meant treating infrastructure code with the same rigor as application code. The tools support it; the discipline makes it work.
Most enterprises settled on managed Kubernetes. Azure Kubernetes Service (AKS) became the default choice for Azure shops: Flux and ArgoCD emerged as the…
Azure Developer CLI represents a significant shift toward developer productivity. By providing high-level commands and proven templates, it reduces the…
Azure Service Connector eliminates the boilerplate of connecting services while implementing security best practices. It's a significant productivity boost…
Application Insights provides the deep observability needed for modern applications. Combined with Azure Monitor's broader capabilities, it enables…
Azure Load Testing makes performance validation accessible and integrated into modern DevOps workflows. By catching performance regressions early, you can…
Chaos engineering is the practice of experimenting on a system to build confidence in its ability to withstand turbulent conditions. Netflix pioneered this…
Power BI Deployment Pipelines transform how organizations manage their analytics lifecycle. By bringing CI/CD practices to BI, teams can deliver insights…
Databricks Repos in production use means the code running in your prod workspace is explicitly linked to a specific Git commit—not "whatever notebooks…
Databricks Git integration (Repos) connects the workspace directly to GitHub, GitLab, Azure DevOps, or Bitbucket, replacing the manual pattern of…
The Databricks CLI is the command-line interface for Databricks workspace operations—running jobs, managing clusters, deploying libraries, uploading…
AKS cluster upgrades are the operational task that feels straightforward until you do them in production and discover the nuances—node cordoning order, pod…
MLOps transforms ML from an experimental practice to a reliable engineering discipline. Azure ML provides the tools to implement these practices at scale.
DSC works with three key components: Configurations : PowerShell scripts defining desired state Resources : Building blocks for configurations (files,…
Set up Update Management for your VMs: Onboard VMs to Update Management: Schedule update deployments: Create maintenance scripts: Query update compliance…
Set up Azure Automation: Create a runbook for VM management: Create a Python runbook for resource cleanup: Create schedules for automated execution: Create…
Service Health tracks three types of events: Service Issues : Active problems affecting Azure services Planned Maintenance : Upcoming maintenance that might…
Resource Health reports four possible states: Available : Resource is healthy and operating normally Unavailable : Resource is not healthy due to Azure or…
Azure resources produce several types of diagnostic data: Platform Metrics : Numerical performance data Resource Logs : Detailed operational logs (formerly…
There are two ways to publish custom metrics: Application Insights SDK : For application level metrics Azure Monitor REST API : For any metric source Use…
Azure Monitor collects two types of metrics: Platform Metrics : Automatically collected from Azure resources Custom Metrics : Application specific metrics…
ARM Template Specs provide a governed, versioned approach to managing infrastructure templates. With native RBAC integration and first class Azure resource…
Terraform with the AzureRM provider is the infrastructure-as-code choice I recommend to teams that need multi-cloud portability or already have Terraform…
GitHub Actions workflows for Azure deployment have become my default for any project that lives on GitHub and targets Azure. The Azure/login action with…
Azure Pipelines supports four template types: 1. Stage templates Reusable stages 2. Job templates Reusable jobs 3. Step templates Reusable steps 4. Variable…
Configure in Azure DevOps UI or via YAML: Azure DevOps YAML pipelines provide powerful, version controlled CI/CD capabilities. By leveraging templates,…
Traditional configuration approaches using appsettings.json or environment variables have limitations: No central management Requires redeployment for…
Azure Monitor supports several alert types: Metric alerts Based on metric values crossing thresholds Log alerts Based on Log Analytics query results…
I've written a lot of ARM templates in the past three years, and I've also inherited a lot of ARM templates written by people who were having a bad day. The…
GitHub Actions went from "interesting alternative to Azure DevOps Pipelines" to "my default CI/CD choice for most new Azure projects" in about twelve…
Run the task: 1. Use Premium SKU for production with geo replication and security features 2. Enable content trust for image signing 3. Implement lifecycle…
"Why is the staging environment talking to the production database?" is a sentence I never want to hear again, and yet—when configuration lives in…
Automated tests are the bulk of my testing pyramid, but there's a tier you can't replace: the human running through a workflow looking for the thing nobody…
Every consultancy I've worked at has the same problem: developers need a sandbox, finance needs to not get a heart attack, and three months later there are…
Deploy JMeter on Azure VMs for distributed testing: Run JMeter in containers for quick, scalable tests: Metric Description Target Response Time (avg)…
Application Insights is essential for production observability.
Templates transform pipeline chaos into maintainable, standardized CI/CD.
Azure DevOps Pipelines was the obvious answer for years. GitHub Actions in 2020 changed that calculus — for any project where the source already lives on…
Blueprints ensure every environment starts from a known, compliant state.
Every cloud team eventually accumulates a folder full of "scripts I run monthly" — clean up old resource groups, rotate certificates, scale down dev…
Alerts should be actionable. If you can't do anything about it, it's noise.
The Azure DevOps Classic editor is comfortable, and I've watched many teams resist moving away from it for that exact reason. Until they need to branch a…
After several years of writing ARM templates, picking up Terraform felt like getting glasses for the first time. The same infrastructure-as-code idea, but…
Azure Container Registry provides a secure, scalable foundation for container-based deployments on Azure.
First thing I do on any new Azure-hosted application I'm asked to look at: open Application Insights and see what's actually happening. Half the time, "the…
"How do we deploy a new version without downtime?" That's the conversation that got me writing this post. AKS gives you the primitives, but the choice…
Classic CI/CD pipelines as a clickable thing in a UI: I keep migrating clients off them. Half the time the original person who built the pipeline has left…