Flyio performance tuning
'Optimize Fly.io application performance with auto-stop/start tuning,From its SKILL.md
npx -y skills add jeremylongshore/claude-code-plugins-plus-skills --skill flyio-performance-tuningAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
What its file declares
Copied from the file, not written here
The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.
SKILL.md
3.0 KB, 722 tokens by cl100k_base, as published. Nobody here has run it
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:[email protected]: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.
What ships with it
Read from the repository
Just SKILL.md. No reference files, no scripts.