DevOps + AI
AI-Powered Predictive Autoscaling & Cost Optimization for Cloud Infrastructure
Current Load
67%
Predicted 15m
82%
Scaling Plan
Traditional autoscaling reacts after the spike hits. Teams over-provision to be safe, pay for idle resources, and still risk downtime during bursts.
Thresholds and schedules need constant tweaks across services, environments, and seasons.
Scale kicks in after latency climbs. Cold starts and API rate limits slow recovery.
Over-provisioning becomes the norm. Cloud bills grow faster than the product.
AutoScalerAI forecasts demand before it hits production. It proactively adjusts capacity, keeps latency low, and minimizes cost.
Uses time-series models to forecast traffic and scale ahead of spikes.
Balances spot/on‑demand, rightsizes nodes, and reduces idle waste.
Pre-warms services and caches, shifts load before hotspots appear.
Applies infra changes via Terraform/Ansible. Updates HPAs and ASGs.
Integrates with your existing stack – no vendor lock‑in.
A simple pipeline that ingests metrics, predicts demand, decides scaling actions, automates infrastructure, and visualizes outcomes.
Collects metrics from Prometheus, CloudWatch, logs, and custom events.
Time-series models (Prophet, LSTM) forecast traffic and resource needs.
Policy rules and risk budgets select safe, cost-efficient actions.
Executes changes via Terraform, Ansible, HPAs, and cloud APIs.
Dashboards (Grafana) and notifications (Slack bot) close the loop.
How AutoScalerAI operates across your platform.
Prometheus, CloudWatch
Prophet, LSTM
Policies & SLO budgets
Terraform, Ansible
Grafana, Slack Bot
Outcome-focused results for engineering teams and the business.
Scale before incidents. Keep latency stable during traffic bursts.
Rightsize capacity, leverage spot, and remove idle overhead.
Policy-driven decisions aligned with SLOs and risk budgets.
Less manual toil. More time for product and reliability work.
Integrates with popular DevOps tools out of the box.
Where AutoScalerAI delivers impact.
Sales spikes, flash deals, seasonality.
Event premieres, concurrent viewers.
Market opens, volatility bursts.
Growth on-boarding, daily diurnal patterns.
Open to contributions, partnerships, and discussions.