Claude-code-plugins-plus-skills flyio-performance-tuning
install
source · Clone the upstream repo
git clone https://github.com/jeremylongshore/claude-code-plugins-plus-skills
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/jeremylongshore/claude-code-plugins-plus-skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/plugins/saas-packs/flyio-pack/skills/flyio-performance-tuning" ~/.claude/skills/jeremylongshore-claude-code-plugins-plus-skills-flyio-performance-tuning && rm -rf "$T"
manifest:
plugins/saas-packs/flyio-pack/skills/flyio-performance-tuning/SKILL.mdsource content
Fly.io Performance Tuning
Overview
Optimize Fly.io performance: eliminate cold starts, right-size VMs, leverage multi-region for low latency, and tune concurrency settings.
Instructions
Step 1: Eliminate Cold Starts
# fly.toml — suspend instead of stop for faster resume (~100ms vs ~5s) [http_service] auto_stop_machines = "suspend" # Suspend to RAM, not full stop auto_start_machines = true min_machines_running = 1 # Always-warm in primary region # For latency-critical: keep machines running in all regions # min_machines_running applies globally
Step 2: Right-Size VMs
# Check current allocation fly scale show -a my-app # Start small, scale up based on metrics fly scale vm shared-cpu-1x --memory 256 # Start here fly scale vm shared-cpu-1x --memory 512 # If memory-constrained fly scale vm shared-cpu-2x --memory 1024 # If CPU-bound fly scale vm performance-2x --memory 4096 # For compute-heavy workloads
| Workload | VM | Memory | When |
|---|---|---|---|
| Static site / API proxy | shared-cpu-1x | 256mb | Low traffic |
| Node.js API | shared-cpu-1x | 512mb | Most apps |
| Heavy processing | shared-cpu-2x | 1gb | Background jobs |
| Database / ML | performance-2x | 4gb | Compute-intensive |
Step 3: Multi-Region Latency Optimization
# Deploy close to your users fly scale count 1 --region iad # US East fly scale count 1 --region lhr # Europe fly scale count 1 --region nrt # Asia Pacific # Fly automatically routes to nearest region via Anycast # Verify: curl with timing curl -w "DNS: %{time_namelookup}s, Connect: %{time_connect}s, Total: %{time_total}s\n" \ -o /dev/null -s https://my-app.fly.dev/health
Step 4: Connection Pooling for Postgres
// Use connection pooling for Fly Postgres // PgBouncer runs on port 5433 (pooled) vs 5432 (direct) const pooledUrl = process.env.DATABASE_URL?.replace(':5432/', ':5433/'); // Prisma: add pgbouncer=true // DATABASE_URL="postgres://user:pass@my-db.internal:5433/db?pgbouncer=true"
Step 5: Tune Concurrency
[http_service.concurrency] type = "requests" # or "connections" hard_limit = 250 # Max before rejecting soft_limit = 200 # Start scaling at this point
Resources
Next Steps
For cost optimization, see
flyio-cost-tuning.