Data Science & Developer Roadmaps with Chat & Free Learning Resources

MLOps Roadmap

Below you’ll find the MLOps Roadmap - a step-by-step guide on how to become a MLOps Engineer. This roadmap covers topics like Cloud Computing, Model Deployment, Automation, Monitoring and important tooling. 

Also check the Machine Learning and Data Engineering Roadmaps for additional skills and tooling.

All boxes are clickable and provide you with AI-powered explanations and free learning resources. You can also chat with our 🤖 bot when you have any question about the topics on this roadmap.

MLOps EngineerCloud ComputingAWS / GCP / AzureCloud Native ML servicesData Engineering FundamentalsML FundamentalsData PipelinesData Lakes & WarehousesData Ingestion ArchitectureMLOps PrinciplesMLOps BasicsML Lifecycle ManagementCollaboration ToolsContinuous Integration/Continuous Deployment (CI/CD)Continuous Training (CT)Continuous Monitoring (CM) of ML modelsModel VersioningModel PackagingReproducibility in MLExperiment TrackingMLflowDVC (Data Version Control)Weights & Biases (W&B)Model Serving TechniquesModel Deployment & ServingServing FrameworksAPI managementA/B Testing and Canary DeploymentsShadow DeploymentsTensorFlow ServingTorchServeKFServingAPI GatewaysRate LimitingPipeline AutomationAutomation & OrchestrationWorkflow OrchestrationKubeflow PipelinesTFX (TensorFlow Extended)Apache Airflow for ML PipelinesModel Drift Monitoring & ObservabilityModel ExplainabilityMonitoring Model Performance Over TimeAlerts and Automated RetrainingStatistical Techniques for Drift DetectionInterpretabilityFairness Metrics and AuditingSHAPLIMELogging & AnalyticsReal-time vs Batch ServingAuthenticationHybrid and Multi-cloud DeploymentsAdvanced DeploymentStrategiesServerless MLMultiple Cloud ProvidersModel Sync Across CloudsAWS LambdaGoogle Cloud Model RegistryTooling and EcosystemFeature StoresDataOps IntegrationManaging Model RegistriesVersion Control for ModelsManaging and Serving FeaturesFeature Engineering PipelinesFeature Versioning Data & ML Pipelines IntegrationAutomated Data Quality ChecksData Lineage TrackingKeep exploring!Model RegistryEmerging Trends in MLOpsFeature StoresDataOps Integration