Delivery ends at go-live. Operations start there. Labs Virtual provides named-contact managed services, DataOps, DevOps, and SRE for Microsoft Fabric, Azure, and the surrounding data stack.
Managed Services
You get one person who understands your platform completely — not a ticketing queue or a rotating helpdesk. That contact handles incidents, monitors cost, coordinates with Microsoft, and keeps your data operations running.
One dedicated specialist who knows your architecture, your vendors, and your escalation contacts — not a generic support pool.
Response and resolution SLAs matched to your operational tier. Critical platform incidents get a response within the hour.
Direct escalation to Microsoft, Databricks, Datadog, and other platform vendors — with context already provided. No repeat explanations.
Platform Support
Incidents, architecture questions, cost reviews, security patches, access governance — handled by the same team that designed the platform. Not outsourced to a separate support vendor who needs to be briefed from scratch every time.
Explore Microsoft Support →DataOps
Pipeline failures are business failures. DataOps with Labs Virtual means continuous monitoring of your data pipelines, quality gates on every ingestion layer, and a defined incident response path when things break.
24/7 monitoring of Data Factory, Fabric Pipelines, and Databricks jobs. SLA-backed alerting before failures hit downstream consumers.
Automated quality checks at ingestion, transformation, and serving layers. Quarantine bad data before it reaches dashboards and reports.
Defined runbooks for common failure patterns. On-call coverage matched to your SLA tier. Root cause analysis and preventive fixes as standard.
DevOps
Every platform needs repeatable, auditable deployment. Labs Virtual structures your environments, automates deployments, and ensures your data infrastructure is versioned, testable, and recoverable.
Terraform and Azure Bicep for every resource. No manually provisioned infrastructure that nobody remembers configuring.
GitHub Actions and Azure DevOps pipelines for notebook deployments, schema migrations, pipeline updates, and Power BI report publishing.
Dev, test, and production environments with proper isolation, workspace separation, and promotion gates. Hotfixes tracked, not guessed.
MLOps
Trained models have a half-life. Labs Virtual manages the full MLOps lifecycle — from model packaging and deployment through to drift detection, retraining triggers, and explainability logging.
Azure ML, Databricks MLflow, and Fabric Real-Time Intelligence for model endpoints. Versioned, monitored, rollback-ready.
Automated data and concept drift monitoring with configurable thresholds. Early warning before model degradation reaches business impact.
Scheduled and trigger-based retraining with automated evaluation gates. A model only promotes to production if it improves on the current baseline.
SRE & Reliability
Reliability is designed, not hoped for. Labs Virtual defines and tracks SLOs for your platform, builds the observability stack, and manages the on-call process — so incidents are handled before they become outages.
Service level objectives set per platform component. Error budgets tracked weekly. Burn rate alerts prevent SLO exhaustion before it happens.
Azure Monitor, Log Analytics, and Datadog wired to your platform. Dashboards, alerts, and traces — not guessing from raw logs.
Defined on-call rotation, documented runbooks for all critical failure scenarios, and post-incident reviews that actually improve the system.
Ecosystem Map
Labs Virtual operates across the modern data stack. Every zone below is a category of platform work we handle under managed operations.
Whether you need a fully managed service or just a reliable on-call contact for your existing platform, we scope based on what you actually need — not a fixed package.