Managing Lambda Labs

Lambda Labs Management

Analyze Lambda Labs GPU instances, availability, filesystems, and pricing.

Phase 1: Discovery

#!/bin/bash
TOKEN="${LAMBDA_API_KEY}"
BASE="https://cloud.lambdalabs.com/api/v1"
AUTH=(-H "Authorization: Bearer ${TOKEN}" -H "Content-Type: application/json")

echo "=== Running Instances ==="
curl -s "${BASE}/instances" "${AUTH[@]}" \
  | jq -r '.data[] | "\(.name // .id[0:12])\t\(.id[0:12])\t\(.status)\t\(.instance_type.name)\t\(.region.name)\t\(.ip)"' \
  | column -t | head -20

echo ""
echo "=== Instance Types & Pricing ==="
curl -s "${BASE}/instance-types" "${AUTH[@]}" \
  | jq -r '.data | to_entries[] | "\(.key)\t\(.value.instance_type.description)\tGPUs:\(.value.instance_type.specs.gpus)\tRAM:\(.value.instance_type.specs.ram)GB\t$\(.value.instance_type.price_cents_per_hour / 100)/hr"' \
  | column -t | head -15

echo ""
echo "=== GPU Availability by Region ==="
curl -s "${BASE}/instance-types" "${AUTH[@]}" \
  | jq -r '.data | to_entries[] | .key as $type | .value.regions_with_capacity_available[]? | "\($type)\t\(.name)\t\(.description)"' \
  | column -t | head -20

echo ""
echo "=== SSH Keys ==="
curl -s "${BASE}/ssh-keys" "${AUTH[@]}" \
  | jq -r '.data[] | "\(.name)\t\(.id[0:12])\t\(.public_key[0:40])..."' \
  | column -t | head -10

Phase 2: Analysis

#!/bin/bash
TOKEN="${LAMBDA_API_KEY}"
BASE="https://cloud.lambdalabs.com/api/v1"
AUTH=(-H "Authorization: Bearer ${TOKEN}" -H "Content-Type: application/json")

echo "=== Instance Details ==="
for INST in $(curl -s "${BASE}/instances" "${AUTH[@]}" | jq -r '.data[].id'); do
  curl -s "${BASE}/instances/${INST}" "${AUTH[@]}" \
    | jq -r '.data | "\(.name // .id[0:12])\t\(.instance_type.name)\t\(.status)\tGPUs:\(.instance_type.specs.gpus)\tVCPUs:\(.instance_type.specs.vcpus)\tRAM:\(.instance_type.specs.ram)GB\tStorage:\(.instance_type.specs.storage_in_gb)GB"' 2>/dev/null
done | column -t | head -15

echo ""
echo "=== Filesystem Attachments ==="
for INST in $(curl -s "${BASE}/instances" "${AUTH[@]}" | jq -r '.data[].id'); do
  NAME=$(curl -s "${BASE}/instances/${INST}" "${AUTH[@]}" | jq -r '.data.name // .data.id[0:12]')
  curl -s "${BASE}/instances/${INST}" "${AUTH[@]}" \
    | jq -r ".data.file_system_names[]? | \"${NAME}\t\(.)\"" 2>/dev/null
done | column -t | head -10

echo ""
echo "=== Filesystems ==="
curl -s "${BASE}/file-systems" "${AUTH[@]}" \
  | jq -r '.data[]? | "\(.name)\t\(.id[0:12])\t\(.region.name)\t\(.mount_point // "N/A")"' \
  | column -t | head -10

echo ""
echo "=== Cost Estimate ==="
INSTANCES=$(curl -s "${BASE}/instances" "${AUTH[@]}")
echo "$INSTANCES" | jq '{
  running_instances: [.data[] | select(.status == "active")] | length,
  total_hourly_cost: [.data[] | select(.status == "active") | .instance_type.price_cents_per_hour] | (add // 0) / 100,
  total_daily_est: (([.data[] | select(.status == "active") | .instance_type.price_cents_per_hour] | (add // 0) / 100) * 24),
  gpu_summary: [.data[] | .instance_type.name] | group_by(.) | map({type: .[0], count: length})
}'

echo ""
echo "=== Availability Summary ==="
curl -s "${BASE}/instance-types" "${AUTH[@]}" \
  | jq '{available_types: [.data | to_entries[] | select(.value.regions_with_capacity_available | length > 0) | .key], unavailable_types: [.data | to_entries[] | select(.value.regions_with_capacity_available | length == 0) | .key]}'

Output Format

LAMBDA LABS ANALYSIS
======================
Instance         Type           GPUs   Region     IP              Status
──────────────────────────────────────────────────────────────────────────
ml-train-1       gpu_8x_a100    8xA100 us-tx-3    192.168.1.10    active
dev-box          gpu_1x_a10     1xA10  us-az-1    192.168.1.11    active

Running: 2 instances | GPUs: A100(8) A10(1)
Hourly Cost: $12.49 | Daily Est: $299.76
SSH Keys: 3 configured | Filesystems: 1 attached
Available Types: gpu_1x_a10, gpu_8x_a100 | Sold Out: gpu_8x_h100

Safety Rules

• Read-only: Only use GET endpoints against the Lambda Labs API
• Never launch or terminate instances without confirmation
• API keys: Never output API key values
• Cost awareness: Always highlight running cost estimates for active instances

Anti-Hallucination Rules

1. NEVER assume resource names — always discover via CLI/API in Phase 1 before referencing in Phase 2.
2. NEVER fabricate metric names or dimensions — verify against the service documentation or --help output.
3. NEVER mix CLI commands between service versions — confirm which version/API you are targeting.
4. ALWAYS use the discovery → verify → analyze chain — every resource referenced must have been discovered first.
5. ALWAYS handle empty results gracefully — an empty response is valid data, not an error to retry.

Counter-Rationalizations