I'll help you determine which aggregate has the best available capacity for provisioning a 10 GB volume. Let me query your ONTAP systems to check the current aggregate space utilization.

Let me try a different approach to find aggregate space information:
Great! Now I found the aggregate space metrics. Let me query for available space:
Perfect! Now let me also get the space utilization percentages to see which aggregates are least used:

Now let me get the total space to better understand the capacity:

Based on the aggregate capacity analysis from your ONTAP systems, here are the best options for provisioning a 10 GB volume:

🏆 Top Recommendations

1. dataFA_4_p0_i1 (rtp-sa-asa01)
   Available Space: 17.0 TB
   Utilization: 0.01% (virtually empty)
   Location: Cluster: rtp-sa-asa01, Node: RTP-SA-ASA01-02
   ✅ Best Choice - Massive available space, almost no current usage
2. dataFA_2_p0_i1 (rtp-sa-asa02)
   Available Space: 17.0 TB
   Utilization: 0.015% (virtually empty)
   Location: Cluster: rtp-sa-asa02, Node: RTP-SA-ASA02-01
   ✅ Excellent Choice - Large capacity, minimal usage
3. astra_aggr1
   Available Space: 6.5 TB
   Utilization: 1% (very low)
   Location: Cluster: A250-41-42-43, Node: A250-42
   ✅ Good Choice - Large capacity, very low usage
4. astra_aggr3
   Available Space: 4.9 TB
   Utilization: 1% (very low)
   Location: Cluster: A250-41-42-43, Node: A250-43
   ✅ Good Choice - Ample space, very low usage
   ⚠️ Avoid These Aggregates
   harvest_vc_aggr: 97% used (only 206 GB available)
   umeng_aff300_aggr1: 96% used (only 306 GB available)
   astra_aggr2: Has 0 total space (likely offline/restricted)
   testshaaggr: Has 0 total space (likely offline/restricted)
   💡 Recommendation
   Use dataFA_4_p0_i1 on cluster rtp-sa-asa01 - it offers the best combination of:

✅ Massive available capacity (17+ TB)
✅ Virtually unused (0.01% utilization)
✅ High-performance storage (appears to be All-Flash based on naming)
✅ Enterprise-class system (ASA series)
For a 10 GB volume, you have plenty of room for growth and excellent performance on this aggregate.

I'll check for health issues across all your clusters by querying various health-related metrics and alerts.

Based on the active alerts and infrastructure health checks, yes, there are significant health issues across your clusters. Here's a summary of the critical problems:

🚨 Critical Issues Found
Volume Space Issues

• 4 volumes at 100% capacity:
  • vol_cus_issue on umeng-aff300-01-02
  • vol44 and vol7676 on A250-41-42-43
  • ci_al_test on umeng-aff300-05-06
• 15 volumes over 95% capacity including:
  • col_test6 (97%) and umeng_harvest_vol1 (96%) on umeng-aff300-05-06
  • RahulTest components (93-99%) on umeng-aff300-01-02
  • lvm_convert (96%) on Cluster1
    Infrastructure Component Failures
• 2 offline aggregates:
  • testshaaggr on A250-41-42-43
  • astra_aggr2 on A250-41-42-43
• 16 offline volumes across multiple clusters
• 1 failed disk: Disk 1.0.9 on Cluster1 with "init failed" error

Performance Issues

• High NFS latency: Node umeng-aff300-02 showing 16.4ms NFS latency
• SnapMirror lag issues: Multiple relationships with significant lag times (hours to days behind)

Security Concerns

• 753+ expired certificates across all clusters
• 18 certificates expiring within 30 days

🎯 Immediate Actions Needed

• Address 100% full volumes immediately - These will impact application availability
• Investigate offline aggregates on A250-41-42-43 cluster
• Replace failed disk 1.0.9 on Cluster1
• Certificate management - Address expired certificates for security compliance

The A250-41-42-43 cluster appears to have the most serious issues with offline aggregates and volumes. Would you like me to drill down into any specific cluster or issue type for more detailed analysis?

I'll analyze the capacity utilization growth trends for cluster umeng-aff300-01-02 by querying historical data over the past several months.

Let me also get volume space utilization data to get a more complete picture of capacity growth:

Let me also get the total capacity to calculate utilization percentages properly:

Now let me calculate the monthly growth rates and present a comprehensive analysis:

Capacity Utilization Growth Analysis for Cluster umeng-aff300-01-02

Based on the historical data from March 19, 2025 to September 19, 2025, here's your capacity utilization growth analysis:

Overall Capacity Trends
Used Space Growth:

• March 2025: ~8.88 TB used
• September 2025: ~9.12 TB used
• Total Growth: ~0.24 TB (240 GB) over 6 months
• Average Monthly Growth: ~40 GB/month

Total Capacity Changes:

• March 2025: ~23.1 TB total capacity
• September 2025: ~25.6 TB total capacity
• Capacity Added: ~2.5 TB over 6 months

Utilization Percentage Trends
March 2025: 38.4% utilized (8.88 TB / 23.1 TB) September 2025: 35.6% utilized (9.12 TB / 25.6 TB)

Monthly Utilization Changes:

• March → April: Slight increase in usage but capacity additions kept utilization stable
• April → May: Major capacity expansion (~0.4 TB added) reduced utilization percentage
• May → June: Continued capacity growth with modest usage increases
• July → August: Significant capacity expansion (~0.3 TB added)
• August → September: Final major expansion (~1.6 TB added) significantly reduced utilization

Aggregate-Level Analysis
test1 aggregate (umeng-aff300-01):

• Utilization remained stable: ~33.4% → ~33.6%
• Very minimal growth over 6 months

umeng_aff300_aggr2 aggregate (umeng-aff300-02):

• Utilization remained steady: ~84.4% → ~84.4%
• This aggregate is running at high utilization (~84%)

Key Insights

• Low Overall Growth: Your actual data growth is very modest at ~40 GB/month
• Proactive Capacity Management: You've been adding capacity faster than consumption
• Imbalanced Aggregates:
  • test1: Well utilized at ~33%
  • umeng_aff300_aggr2: High utilization at ~84% (monitor closely)
• Utilization Trending Down: Due to capacity additions outpacing growth

Recommendations

1. Monitor umeng_aff300_aggr2: At 84% utilization, consider data balancing or expansion
2. Growth Planning: Current 40 GB/month growth rate is very manageable
3. Capacity Optimization: Consider rebalancing data between aggregates
4. Trend Monitoring: Continue monthly capacity reviews to catch growth spikes early
   Would you like me to analyze specific volume growth patterns or dive deeper into any particular time period?