> ## Documentation Index > Fetch the complete documentation index at: https://docs.monk.io/llms.txt > Use this file to discover all available pages before exploring further. # Scaling Resources > Scale workloads and infrastructure up or down ## Scale Infrastructure ``` add 2 more machines ``` Add VMs to your deployment. → [Scaling](/features/scaling) ## Scale Services ``` scale the API server up ``` Increase replicas for a service (workload autoscaling handles this automatically, but you can manually adjust). ## Scale Database ``` increase the database instance to 16GB RAM ``` Resize database resources. ## Adjust Worker Count ``` increase the worker count to 5 ``` Scale background workers. ## Scale Down ``` remove the extra VMs, traffic is back to normal ``` Remove resources when load decreases. ## Get Recommendations ``` should I scale up for this traffic? ``` Ask Monk for scaling recommendations. ## Cost Impact ``` how much will it cost to add 2 more instances? ``` Estimate cost before scaling. → [Cost Tracking](/features/cost-tracking) ## What Monk Does **Before scaling:** * Shows current setup * Recommends instance types/sizes * Estimates cost impact * Asks for confirmation **During scaling:** * Provisions new resources * Deploys containers * Updates load balancers * Zero downtime Cloud scaling executed by monk ## Automatic Workload Scaling Monk's algorithmic autoscaler handles container scaling automatically: * Scales up when CPU/memory is high * Scales down when load decreases * No manual intervention needed **You manually scale:** * Infrastructure (VMs) * Databases * Service settings ## Next Steps * [Managing Infrastructure](/prompting/managing-infrastructure) - Provision more resources * [Managing Costs](/prompting/managing-costs) - Track scaling costs * [Monitoring & Debugging](/prompting/monitoring-and-debugging) - Watch resource usage