# Thoras Documentation

> Documentation for Thoras, the autonomous control plane for compute efficiency. Predictive Kubernetes autoscaling, self-hosted.

- [What is Thoras?](https://docs.thoras.ai/getting-started/what-is-thoras.md): The autonomous control plane for compute efficiency.
- [Quickstart](https://docs.thoras.ai/getting-started/quickstart.md): Deploy Thoras and see Kubernetes resource recommendations in minutes!
- [System Requirements](https://docs.thoras.ai/installation/system-requirements.md)
- [Advanced Setup](https://docs.thoras.ai/installation/advanced-setup.md)
- [Persistent Storage](https://docs.thoras.ai/installation/persistent-storage.md): Configure the persistent volume Thoras uses to retain historical usage metrics, and optionally point Thoras at an external TimescaleDB.
- [Credentials](https://docs.thoras.ai/installation/credentials.md): How Thoras handles the credentials it needs, and how to supply your own.
- [Private Container Registry](https://docs.thoras.ai/installation/private-registry.md): Pull Thoras container images from your own private registry instead of the public Thoras registry.
- [Upgrading](https://docs.thoras.ai/installation/upgrading.md): How Thoras Helm chart versions map to upgrade effort, and what changed in chart 5.x.
- [Configuring AIScaleTargets](https://docs.thoras.ai/guides/configuring-asts.md)
- [Predictive Vertical Pod Rightsizing](https://docs.thoras.ai/guides/vertical-pod-rightsizing.md): Predictive Vertical Pod Rightsizing is the process of preemptively optimizing the CPU and memory resource requests and limits for Kubernetes pods to ensure they have just enough resources to run efficiently without over or under provisioning. Unlike horizontal scaling, which adjusts the number of po…
- [In-Place Resize Behavior](https://docs.thoras.ai/guides/in-place-resize.md): How Thoras handles in-place pod resizing, what happens when a resize cannot complete, and the safety controls that protect your workloads.
- [Predictive Horizontal Pod Autoscaling](https://docs.thoras.ai/guides/hpa.md)
- [Choosing a Forecast Optimization Strategy](https://docs.thoras.ai/guides/forecast-optimization-strategies.md)
- [OOM Remediation](https://docs.thoras.ai/guides/oom-remediation.md): Automatically recover workloads from out-of-memory kill loops
- [JVM Workload Scaling](https://docs.thoras.ai/guides/jvm-scaling.md): How Thoras optimizes Java-based applications
- [Enabling Autonomous Mode](https://docs.thoras.ai/guides/enabling-autonomous-mode.md): Enable predictive scaling with confidence
- [Pausing Autonomous Scaling](https://docs.thoras.ai/guides/pause-scaling.md): Temporarily halt all autonomous scaling actions cluster-wide
- [Audit Trail](https://docs.thoras.ai/guides/audit-trail.md): See who changed scaling behavior, and what changed, from the api-server logs
- [Stopping Autonomous Scaling](https://docs.thoras.ai/guides/stopping-autoscaling.md): Options for halting Thoras autoscaling, from cluster-wide to per-workload
- [ArgoCD](https://docs.thoras.ai/guides/argo-cd.md): ArgoCD is a declarative, GitOps continuous delivery tool for Kubernetes applications. This guide covers deploying Thoras with ArgoCD and managing Thoras-targeted workloads alongside it.
- [Tuning for Large Clusters](https://docs.thoras.ai/guides/large-clusters.md): Helm chart settings for clusters with 5,000 or more AIScaleTargets.
- [Diagnostics Export](https://docs.thoras.ai/guides/diagnostics.md): Download a diagnostics package for troubleshooting and support
- [Monitoring Thoras](https://docs.thoras.ai/guides/metrics.md): Thoras exposes native Prometheus metrics that offer real-time visibility into the actions and health of the Thoras system. This empowers your teams with deeper insights, transparency, and observability.
- [Cost Estimates](https://docs.thoras.ai/guides/cost-estimates.md): Understand how Thoras calculates potential savings and waste across your Kubernetes cluster based on workload resource usage and node pricing data.
- [AWS Cost Explorer](https://docs.thoras.ai/guides/aws-cost-explorer.md): Collect your cluster's real billed AWS spend so Thoras reports actual cost instead of estimates.
- [Dashboard authentication](https://docs.thoras.ai/guides/dashboard-auth.md): How the Thoras dashboard authenticates users, and how to configure the two built-in modes: generated htpasswd credentials or OIDC login against your identity provider.
- [Default (htpasswd) dashboard auth](https://docs.thoras.ai/guides/dashboard-auth/htpasswd.md): Log into the Thoras dashboard with the generated username and password, or provide your own.
- [Okta OIDC dashboard auth](https://docs.thoras.ai/guides/dashboard-auth/okta.md): Log into the Thoras dashboard via Okta using the chart's built-in oauth2-proxy sidecar in OIDC mode.
- [Azure Entra OIDC dashboard auth](https://docs.thoras.ai/guides/dashboard-auth/entra.md): Log into the Thoras dashboard via Azure Entra ID (formerly Azure AD) using the chart's built-in oauth2-proxy sidecar in OIDC mode.
- [AIScaleTarget](https://docs.thoras.ai/reference/ast-definition.md)
- [Forecasting](https://docs.thoras.ai/reference/forecasting.md)
- [ClusterAIScaleTemplate](https://docs.thoras.ai/reference/cluster-aiscale-template.md): ClusterAIScaleTemplate is a cluster-scoped custom resource that automatically creates and manages AIScaleTargets for matching workloads across multiple namespaces. This feature eliminates the need to manually create individual AIScaleTargets for each workload, enabling fleet-wide scaling policies.
- [Pod Annotations](https://docs.thoras.ai/reference/pod-annotations.md): Reference for the thoras.ai/ annotations Thoras writes to pods, and what they do and don't guarantee.
- [Frequently Asked Questions](https://docs.thoras.ai/faq/introduction.md)
- [Integrations](https://docs.thoras.ai/faq/integrations.md): How Thoras works alongside KEDA, Cluster Autoscaler, and Karpenter
- [Compliance & Security](https://docs.thoras.ai/faq/compliance.md): Learn about Thoras security certifications and data protection practices
- [Support and Deprecation Policy](https://docs.thoras.ai/policies/support-policy.md): Thoras support and deprecation policy: supported versions, compatibility commitments, Kubernetes version support, and breaking change notification.
- [Deprecations](https://docs.thoras.ai/deprecations.md): Active deprecations in Thoras and their removal timelines.


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