Thoras is a self-hosted, ML-powered platform that optimizes your Kubernetes
workloads. Unlike traditional autoscalers that only react after the fact,
Thoras predicts usage trends and allocates resources in advance, so you’re
always one step ahead. The power of predictive autoscaling enables teams to:
Thoras continuously analyzes usage data, seasonality patterns, and real-time
telemetry to produce workload demand forecasts. These forecasts are updated at
configurable intervals, allowing Thoras to anticipate horizontal or vertical
scaling needs with high precision. With predictions, Thoras right-sizes pods and
replica counts ahead of time, improving service reliability, saving costs, and
saving engineering time.
Thoras is built to run on Kubernetes, for Kubernetes. Thoras integrates
directly with your clusters to manage and optimize workloads, giving you
predictive scaling and workload intelligence without adding complexity.
Thoras was created by Site Reliability Engineers who have experienced firsthand
the limitations of Kubernetes’ native autoscaling tools. The system is designed
to solve practical, day-to-day scaling and optimization challenges faced by
platform engineering teams. Thoras equips engineers with predictive, autonomous
scaling that improves reliability, reduces waste, and eliminates the need for
constant manual tuning.