# Stack Components

- [Orchestrators](/stacks/stack-components/orchestrators.md): Orchestrating the execution of ML pipelines.
- [Local Orchestrator](/stacks/stack-components/orchestrators/local.md): Orchestrating your pipelines to run locally.
- [Local Docker Orchestrator](/stacks/stack-components/orchestrators/local-docker.md): Orchestrating your pipelines to run in Docker.
- [Kubeflow Orchestrator](/stacks/stack-components/orchestrators/kubeflow.md): Orchestrating your pipelines to run on Kubeflow.
- [Kubernetes Orchestrator](/stacks/stack-components/orchestrators/kubernetes.md): Orchestrating your pipelines to run on Kubernetes clusters.
- [Google Cloud VertexAI Orchestrator](/stacks/stack-components/orchestrators/vertex.md): Orchestrating your pipelines to run on Vertex AI.
- [AWS Sagemaker Orchestrator](/stacks/stack-components/orchestrators/sagemaker.md): Orchestrating your pipelines to run on Amazon Sagemaker.
- [AzureML Orchestrator](/stacks/stack-components/orchestrators/azureml.md): Orchestrating your pipelines to run on AzureML.
- [Databricks Orchestrator](/stacks/stack-components/orchestrators/databricks.md): Orchestrating your pipelines to run on Databricks.
- [Tekton Orchestrator](/stacks/stack-components/orchestrators/tekton.md): Orchestrating your pipelines to run on Tekton.
- [Airflow Orchestrator](/stacks/stack-components/orchestrators/airflow.md): Orchestrating your pipelines to run on Airflow.
- [Skypilot VM Orchestrator](/stacks/stack-components/orchestrators/skypilot-vm.md): Orchestrating your pipelines to run on VMs using SkyPilot.
- [HyperAI Orchestrator](/stacks/stack-components/orchestrators/hyperai.md): Orchestrating your pipelines to run on HyperAI.ai instances.
- [Lightning AI Orchestrator](/stacks/stack-components/orchestrators/lightning.md): Orchestrating your pipelines to run on Lightning AI.
- [Develop a custom orchestrator](/stacks/stack-components/orchestrators/custom.md): Learning how to develop a custom orchestrator.
- [Deployers](/stacks/stack-components/deployers.md): Deploy pipelines as HTTP services for real-time execution
- [Local Deployer](/stacks/stack-components/deployers/local.md): Deploying pipelines on your local machine as background processes.
- [Docker Deployer](/stacks/stack-components/deployers/docker.md): Deploying your pipelines locally with Docker.
- [Kubernetes Deployer](/stacks/stack-components/deployers/kubernetes.md): Deploying your pipelines to Kubernetes clusters.
- [AWS App Runner Deployer](/stacks/stack-components/deployers/aws-app-runner.md): Deploying your pipelines to AWS App Runner.
- [GCP Cloud Run Deployer](/stacks/stack-components/deployers/gcp-cloud-run.md): Deploying your pipelines to GCP Cloud Run.
- [Hugging Face Deployer](/stacks/stack-components/deployers/huggingface.md): Deploying your pipelines to Hugging Face Spaces.
- [Artifact Stores](/stacks/stack-components/artifact-stores.md): Setting up a persistent storage for your artifacts.
- [Local Artifact Store](/stacks/stack-components/artifact-stores/local.md): Storing artifacts on your local filesystem.
- [Amazon Simple Cloud Storage (S3)](/stacks/stack-components/artifact-stores/s3.md): Storing artifacts in an AWS S3 bucket.
- [Google Cloud Storage (GCS)](/stacks/stack-components/artifact-stores/gcp.md): Storing artifacts using GCP Cloud Storage.
- [Azure Blob Storage](/stacks/stack-components/artifact-stores/azure.md): Storing artifacts using Azure Blob Storage
- [Alibaba Cloud OSS](/stacks/stack-components/artifact-stores/alibaba-oss.md): Storing artifacts in Alibaba Cloud Object Storage Service (OSS).
- [MinIO](/stacks/stack-components/artifact-stores/minio.md): Storing artifacts in MinIO object storage.
- [Develop a custom artifact store](/stacks/stack-components/artifact-stores/custom.md): Learning how to develop a custom artifact store.
- [Container Registries](/stacks/stack-components/container-registries.md): Setting up a storage for Docker images.
- [Default Container Registry](/stacks/stack-components/container-registries/default.md): Storing container images locally.
- [DockerHub](/stacks/stack-components/container-registries/dockerhub.md): Storing container images in DockerHub.
- [Amazon Elastic Container Registry (ECR)](/stacks/stack-components/container-registries/aws.md): Storing container images in Amazon ECR.
- [Google Cloud Container Registry](/stacks/stack-components/container-registries/gcp.md): Storing container images in GCP.
- [Azure Container Registry](/stacks/stack-components/container-registries/azure.md): Storing container images in Azure.
- [GitHub Container Registry](/stacks/stack-components/container-registries/github.md): Storing container images in GitHub.
- [Develop a custom container registry](/stacks/stack-components/container-registries/custom.md): Learning how to develop a custom container registry.
- [Log Stores](/stacks/stack-components/log-stores.md): Storing and retrieving logs from your ML pipelines.
- [Artifact Log Store](/stacks/stack-components/log-stores/artifact.md): Storing logs in your artifact store.
- [OpenTelemetry Log Store](/stacks/stack-components/log-stores/otel.md): Exporting logs to any OpenTelemetry-compatible backend.
- [Datadog Log Store](/stacks/stack-components/log-stores/datadog.md): Exporting logs to Datadog's log management platform.
- [Develop a Custom Log Store](/stacks/stack-components/log-stores/custom.md): Learning how to develop a custom log store.
- [Step Operators](/stacks/stack-components/step-operators.md): Executing individual steps in specialized environments.
- [Amazon SageMaker](/stacks/stack-components/step-operators/sagemaker.md): Executing individual steps in SageMaker.
- [AzureML](/stacks/stack-components/step-operators/azureml.md): Executing individual steps in AzureML.
- [Google Cloud VertexAI](/stacks/stack-components/step-operators/vertex.md): Executing individual steps in Vertex AI.
- [Kubernetes](/stacks/stack-components/step-operators/kubernetes.md): Executing individual steps in Kubernetes Pods.
- [Run:AI](/stacks/stack-components/step-operators/runai.md): Executing individual steps on Run:AI clusters with fractional GPU support.
- [Modal](/stacks/stack-components/step-operators/modal.md): Executing individual steps in Modal.
- [Spark](/stacks/stack-components/step-operators/spark-kubernetes.md): Executing individual steps on Spark
- [Develop a Custom Step Operator](/stacks/stack-components/step-operators/custom.md): Learning how to develop a custom step operator.
- [Experiment Trackers](/stacks/stack-components/experiment-trackers.md): Logging and visualizing ML experiments.
- [Comet](/stacks/stack-components/experiment-trackers/comet.md): Logging and visualizing experiments with Comet.
- [MLflow](/stacks/stack-components/experiment-trackers/mlflow.md): Logging and visualizing experiments with MLflow.
- [Neptune](/stacks/stack-components/experiment-trackers/neptune.md): Logging and visualizing experiments with neptune.ai
- [Weights & Biases](/stacks/stack-components/experiment-trackers/wandb.md): Logging and visualizing experiments with Weights & Biases.
- [Google Cloud VertexAI Experiment Tracker](/stacks/stack-components/experiment-trackers/vertexai.md): Logging and visualizing experiments with Vertex AI Experiment Tracker.
- [Develop a custom experiment tracker](/stacks/stack-components/experiment-trackers/custom.md): Learning how to develop a custom experiment tracker.
- [Image Builders](/stacks/stack-components/image-builders.md): Building container images for your ML workflow.
- [Local Image Builder](/stacks/stack-components/image-builders/local.md): Building container images locally.
- [Kaniko Image Builder](/stacks/stack-components/image-builders/kaniko.md): Building container images with Kaniko.
- [AWS Image Builder](/stacks/stack-components/image-builders/aws.md): Building container images with AWS CodeBuild
- [Google Cloud Image Builder](/stacks/stack-components/image-builders/gcp.md): Building container images with Google Cloud Build
- [Develop a Custom Image Builder](/stacks/stack-components/image-builders/custom.md): Learning how to develop a custom image builder.
- [Alerters](/stacks/stack-components/alerters.md): Sending automated alerts to chat services.
- [Discord Alerter](/stacks/stack-components/alerters/discord.md): Sending automated alerts to a Discord channel.
- [Slack Alerter](/stacks/stack-components/alerters/slack.md): Sending automated alerts to a Slack channel.
- [Develop a Custom Alerter](/stacks/stack-components/alerters/custom.md): Learning how to develop a custom alerter.
- [Annotators](/stacks/stack-components/annotators.md): Annotating the data in your workflow.
- [Argilla](/stacks/stack-components/annotators/argilla.md): Annotating data using Argilla.
- [Label Studio](/stacks/stack-components/annotators/label-studio.md): Annotating data using Label Studio.
- [Pigeon](/stacks/stack-components/annotators/pigeon.md): Annotating data using Pigeon.
- [Prodigy](/stacks/stack-components/annotators/prodigy.md): Annotating data using Prodigy.
- [Develop a Custom Annotator](/stacks/stack-components/annotators/custom.md): Learning how to develop a custom annotator.
- [Data Validators](/stacks/stack-components/data-validators.md): How to enhance and maintain the quality of your data and the performance of your models with data profiling and validation
- [Great Expectations](/stacks/stack-components/data-validators/great-expectations.md): How to use Great Expectations to run data quality checks in your pipelines and document the results
- [Deepchecks](/stacks/stack-components/data-validators/deepchecks.md): How to test the data and models used in your pipelines with Deepchecks test suites
- [Evidently](/stacks/stack-components/data-validators/evidently.md): How to keep your data quality in check and guard against data and model drift with Evidently profiling
- [Whylogs](/stacks/stack-components/data-validators/whylogs.md): How to collect and visualize statistics to track changes in your pipelines' data with whylogs/WhyLabs profiling.
- [Develop a custom data validator](/stacks/stack-components/data-validators/custom.md): How to develop a custom data validator
- [Feature Stores](/stacks/stack-components/feature-stores.md): Managing data in feature stores.
- [Feast](/stacks/stack-components/feature-stores/feast.md): Managing data in Feast feature stores.
- [Develop a Custom Feature Store](/stacks/stack-components/feature-stores/custom.md): Learning how to develop a custom feature store.
- [Model Deployers](/stacks/stack-components/model-deployers.md): Deploying your models and serve real-time predictions.
- [MLflow](/stacks/stack-components/model-deployers/mlflow.md): Deploying your models locally with MLflow.
- [Seldon](/stacks/stack-components/model-deployers/seldon.md): Deploying models to Kubernetes with Seldon Core.
- [BentoML](/stacks/stack-components/model-deployers/bentoml.md): Deploying your models locally with BentoML.
- [Hugging Face](/stacks/stack-components/model-deployers/huggingface.md): Deploying models to Huggingface Inference Endpoints with Hugging Face :hugging\_face:.
- [Databricks](/stacks/stack-components/model-deployers/databricks.md): Deploying models to Databricks Inference Endpoints with Databricks
- [vLLM](/stacks/stack-components/model-deployers/vllm.md): Deploying your LLM locally with vLLM.
- [Develop a Custom Model Deployer](/stacks/stack-components/model-deployers/custom.md): Learning how to develop a custom model deployer.
- [Model Registries](/stacks/stack-components/model-registries.md): Tracking and managing ML models.
- [MLflow Model Registry](/stacks/stack-components/model-registries/mlflow.md): Managing MLFlow logged models and artifacts
- [Develop a Custom Model Registry](/stacks/stack-components/model-registries/custom.md): Learning how to develop a custom model registry.