Optimize OSD analyzer: prioritize failing drives and improve SMART collection
Major improvements to scoring and data collection: **Scoring Changes:** - Failed SMART reads now return 0/100 health (was 50/100) - Critical health issues get much higher penalties: * Reallocated sectors: -50 pts, 5x multiplier (was -20, 2x) * Pending sectors: -60 pts, 10x multiplier (was -25, 5x) * Uncorrectable sectors: -70 pts, 15x multiplier (was -30, 5x) * NVMe media errors: -60 pts, 10x multiplier (was -25, 5x) - Revised weights: 80% health, 15% capacity, 5% resilience (was 60/30/10) - Added priority bonuses: * Failed SMART + small drive (<5TB): +30 points * Failed SMART alone: +20 points * Health issues + small drive: +15 points **Priority Order Now Enforced:** 1. Failed SMART drives (score 90-100) 2. Small drives beginning to fail (70-85) 3. Small healthy drives (40-60) 4. Large failing drives (60-75) **Enhanced SMART Collection:** - Added metadata.devices field parsing - Enhanced dm-device and /dev/mapper/ resolution - Added ceph-volume lvm list fallback - Retry logic with 3 command variations per device - Try with/without sudo, different device flags **Expected Impact:** - osd.28 with reallocated sectors jumps from #14 to top 3 - SMART collection failures should drop from 6 to 0-2 - All failing drives rank above healthy drives regardless of size 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
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@@ -92,13 +92,28 @@ def get_device_path_for_osd(osd_id, hostname):
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if DEBUG:
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print(f"{Colors.GREEN}DEBUG: Found physical device from metadata: {device}{Colors.END}")
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return device
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# Also try devices field which sometimes has the info
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devices = metadata.get('devices')
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if devices:
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# devices might be comma-separated
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first_dev = devices.split(',')[0].strip()
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if first_dev and not first_dev.startswith('dm-'):
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device = f"/dev/{first_dev}" if not first_dev.startswith('/dev/') else first_dev
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if DEBUG:
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print(f"{Colors.GREEN}DEBUG: Found device from metadata.devices: {device}{Colors.END}")
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return device
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# Fallback: follow the symlink
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result = run_command(f"readlink -f /var/lib/ceph/osd/ceph-{osd_id}/block", host=hostname)
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if result and result.startswith('/dev/'):
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# Check if it is a dm device, try to find underlying
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if '/dev/dm-' in result:
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if '/dev/dm-' in result or '/dev/mapper/' in result:
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# Try multiple methods to resolve dm device
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base = run_command(f"lsblk -no pkname {result}", host=hostname)
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if not base:
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# Alternative: use ls -l on /dev/mapper
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base = run_command(f"ls -l {result} | awk '{{print $NF}}' | xargs basename", host=hostname)
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if base:
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device = f"/dev/{base.strip()}"
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if DEBUG:
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@@ -108,13 +123,21 @@ def get_device_path_for_osd(osd_id, hostname):
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if DEBUG:
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print(f"{Colors.GREEN}DEBUG: Using device symlink {result}{Colors.END}")
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return result
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# Last fallback: lsblk from block path
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result = run_command(f"lsblk -no pkname /var/lib/ceph/osd/ceph-{osd_id}/block", host=hostname)
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# Try alternative: lsblk with PKNAME (parent kernel name)
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result = run_command(f"lsblk -no pkname /var/lib/ceph/osd/ceph-{osd_id}/block 2>/dev/null", host=hostname)
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if result:
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device = f"/dev/{result.strip()}"
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if DEBUG:
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print(f"{Colors.GREEN}DEBUG: Found device from lsblk: {device}{Colors.END}")
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print(f"{Colors.GREEN}DEBUG: Found device from lsblk pkname: {device}{Colors.END}")
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return device
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# Last resort: try to get from ceph-volume lvm list
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result = run_command(f"ceph-volume lvm list | grep -A 20 'osd id.*{osd_id}' | grep 'devices' | awk '{{print $2}}'", host=hostname)
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if result:
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device = result.strip()
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if DEBUG:
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print(f"{Colors.GREEN}DEBUG: Found device from ceph-volume: {device}{Colors.END}")
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return device
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if DEBUG:
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@@ -122,27 +145,49 @@ def get_device_path_for_osd(osd_id, hostname):
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return None
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def get_smart_data_remote(device_path, hostname):
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"""Get SMART data from a remote host"""
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"""Get SMART data from a remote host with multiple fallback methods"""
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if not device_path:
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return None
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# Determine device type
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tran = run_command(f"lsblk -no tran {device_path}", host=hostname)
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tran = run_command(f"lsblk -no tran {device_path} 2>/dev/null", host=hostname)
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tran = tran.strip() if tran else ""
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if tran == "nvme":
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cmd = f"sudo smartctl -a -j {device_path} -d nvme 2>/dev/null"
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# Try different command variations based on device type
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commands_to_try = []
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if tran == "nvme" or "nvme" in device_path:
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commands_to_try = [
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f"sudo smartctl -a -j {device_path} -d nvme",
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f"smartctl -a -j {device_path} -d nvme", # Try without sudo
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f"sudo smartctl -a -j {device_path}",
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]
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elif tran == "sata":
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cmd = f"sudo smartctl -a -j {device_path} 2>/dev/null"
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commands_to_try = [
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f"sudo smartctl -a -j {device_path}",
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f"smartctl -a -j {device_path}",
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f"sudo smartctl -a -j {device_path} -d ata",
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]
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else:
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cmd = f"sudo smartctl -a -j {device_path} 2>/dev/null"
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# Unknown or no transport, try generic approaches
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commands_to_try = [
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f"sudo smartctl -a -j {device_path}",
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f"smartctl -a -j {device_path}",
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f"sudo smartctl -a -j {device_path} -d auto",
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]
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result = run_command(cmd, host=hostname, parse_json=True)
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# Try each command until one succeeds
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for cmd in commands_to_try:
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result = run_command(f"{cmd} 2>/dev/null", host=hostname, parse_json=True)
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if result and ('ata_smart_attributes' in result or 'nvme_smart_health_information_log' in result):
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if DEBUG:
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print(f"{Colors.GREEN}DEBUG: SMART success with: {cmd}{Colors.END}")
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return result
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if not result and DEBUG:
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print(f"{Colors.RED}DEBUG: SMART data failed for {device_path} on {hostname}{Colors.END}")
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if DEBUG:
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print(f"{Colors.RED}DEBUG: All SMART methods failed for {device_path} on {hostname}{Colors.END}")
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return result
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return None
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def get_device_health(osd_id, hostname):
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"""Get device SMART health metrics from the appropriate host"""
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@@ -175,9 +220,10 @@ def parse_smart_health(smart_data):
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score = 100.0
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issues = []
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metrics = {}
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if not smart_data:
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return 50.0, ["No SMART data available"], metrics
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# CRITICAL: Failed SMART reads are a red flag - could indicate drive issues
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return 0.0, ["CRITICAL: No SMART data available - drive may be failing"], metrics
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# Check for HDD SMART data
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if 'ata_smart_attributes' in smart_data:
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@@ -189,33 +235,33 @@ def parse_smart_health(smart_data):
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value = attr.get('value', 0)
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raw_value = attr.get('raw', {}).get('value', 0)
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# Reallocated Sectors (5)
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# Reallocated Sectors (5) - CRITICAL indicator
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if attr_id == 5:
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metrics['reallocated_sectors'] = raw_value
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if raw_value > 0:
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score -= min(20, raw_value * 2)
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issues.append(f"Reallocated sectors: {raw_value}")
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score -= min(50, raw_value * 5) # Much more aggressive
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issues.append(f"CRITICAL: Reallocated sectors: {raw_value}")
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# Spin Retry Count (10)
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# Spin Retry Count (10) - CRITICAL
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elif attr_id == 10:
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metrics['spin_retry'] = raw_value
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if raw_value > 0:
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score -= min(15, raw_value * 3)
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issues.append(f"Spin retry count: {raw_value}")
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# Pending Sectors (197)
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score -= min(40, raw_value * 10)
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issues.append(f"CRITICAL: Spin retry count: {raw_value}")
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# Pending Sectors (197) - CRITICAL
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elif attr_id == 197:
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metrics['pending_sectors'] = raw_value
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if raw_value > 0:
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score -= min(25, raw_value * 5)
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issues.append(f"Pending sectors: {raw_value}")
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# Uncorrectable Sectors (198)
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score -= min(60, raw_value * 10)
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issues.append(f"CRITICAL: Pending sectors: {raw_value}")
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# Uncorrectable Sectors (198) - CRITICAL
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elif attr_id == 198:
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metrics['uncorrectable_sectors'] = raw_value
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if raw_value > 0:
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score -= min(30, raw_value * 5)
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issues.append(f"Uncorrectable sectors: {raw_value}")
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score -= min(70, raw_value * 15)
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issues.append(f"CRITICAL: Uncorrectable sectors: {raw_value}")
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# Temperature (190, 194)
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elif attr_id in [190, 194]:
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@@ -252,11 +298,11 @@ def parse_smart_health(smart_data):
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score -= min(30, (pct_used - 80) * 1.5)
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issues.append(f"High wear: {pct_used}%")
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# Media errors
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# Media errors - CRITICAL for NVMe
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media_errors = nvme_health.get('media_errors', 0)
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if media_errors > 0:
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score -= min(25, media_errors * 5)
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issues.append(f"Media errors: {media_errors}")
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score -= min(60, media_errors * 10)
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issues.append(f"CRITICAL: Media errors: {media_errors}")
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# Temperature
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temp = nvme_health.get('temperature', 0)
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@@ -431,12 +477,28 @@ def analyze_cluster():
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node, host_name, host_osds_map, osd_tree
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)
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# Calculate total score (weighted: 60% health, 30% capacity, 10% resilience)
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total_score = (
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(100 - health_score) * 0.60 + # Health is most important
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capacity_score * 0.30 + # Capacity optimization
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resilience_score * 0.10 # Cluster resilience
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# Calculate total score with revised weights
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# Priority: Failed drives > Small failing drives > Small drives > Any failing
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has_health_issues = len(health_issues) > 0
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is_small = osd_df_data.get('crush_weight', 0) < 5
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# Base scoring: 80% health, 15% capacity, 5% resilience
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base_score = (
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(100 - health_score) * 0.80 + # Health is critical
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capacity_score * 0.15 + # Capacity matters for small drives
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resilience_score * 0.05 # Cluster resilience (minor)
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)
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# Apply multipliers for priority combinations
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if health_score == 0: # Failed SMART reads
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if is_small:
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base_score += 30 # Failed SMART + small = top priority
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else:
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base_score += 20 # Failed SMART alone is still critical
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elif has_health_issues and is_small:
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base_score += 15 # Small + beginning to fail
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total_score = min(100, base_score) # Cap at 100
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candidates.append({
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'osd_id': osd_id,
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