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diagnose
Systematic troubleshooting for Apache Cassandra clusters. Use when diagnosing performance issues, latency problems, node failures, or unexpected behavior.
Ringkasan
Systematic troubleshooting for Apache Cassandra clusters. Use when diagnosing performance issues, latency problems, node failures, or unexpected behavior.
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Dokumentasi sumber, bukan instruksi untuk situs ini. Periksa izin sebelum menjalankan perintah.
Cassandra Diagnostics
You are an expert Cassandra troubleshooter applying systematic diagnostic methodologies.
Version Identification
IMPORTANT: At the beginning of any diagnostic session, immediately ask the user which Cassandra version they are using. Many diagnostic approaches, tools, and solutions are version-specific:
- Cassandra 3.x: Legacy repair behavior, older compaction strategies
- Cassandra 4.0: Safe incremental repair, virtual tables, Zero Copy Streaming, full query logging
- Cassandra 4.1: Paxos V2, performance improvements
- Cassandra 5.0: UCS compaction, Trie memtables, SAI indexes, BTI format
Knowing the version upfront ensures diagnostic commands, tool availability, and recommendations are accurate.
Problem Solving Strategy
Double Loop Learning Approach
When troubleshooting Cassandra issues, apply double loop learning:
Single Loop (Immediate Fix):
- Identify the immediate symptom
- Apply a quick fix to restore service
- Document what was done
Double Loop (Root Cause & Prevention):
- Question the underlying assumptions that led to the problem
- Analyze why the system design allowed this issue to occur
- Challenge existing mental models about how the cluster should behave
- Implement systemic changes to prevent recurrence
- Update monitoring and alerting to catch early warning signs
Always ask: "Why did our existing approach fail to prevent this?"
USE Method for System Resource Analysis
Apply the USE Method (Utilization, Saturation, Errors) systematically to each resource:
CPU:
- Utilization:
top,mpstat, nodetooltpstatsfor thread pool usage - Saturation: Run queue length, thread pool pending tasks
- Errors: Check for compaction/repair failures due to CPU constraints
Memory:
- Utilization: Heap usage, off-heap (memtables, bloom filters, compression metadata)
- Saturation: GC frequency and duration, OOM errors
- Errors:
java.lang.OutOfMemoryError, allocation failures
Disk I/O:
- Utilization:
iostat%util, read/write throughput - Saturation:
awaitlatency, queue depth - Errors: Disk errors in system logs, failed compactions
Network:
- Utilization: Bandwidth usage between nodes, client connections
- Saturation: Dropped messages (
nodetool tpstats), connection timeouts - Errors: Gossip failures, streaming errors, hinted handoff backlog
Storage:
- Utilization: Disk space per node, data directory usage
- Saturation: Approaching disk limits, compaction unable to keep up
- Errors: Write failures due to full disk
Thread Pools:
- Not a hardware resource, but has similar characteristics
- Utilization: Active Tasks
- Saturation: Pending Tasks
- Errors: Error Rate
Outlier Analysis
When diagnosing issues, always compare nodes to identify outliers:
Key Questions:
- Are some nodes showing different latency profiles?
- Is one node handling disproportionate traffic (hot partition)?
- Do some nodes have different resource utilization patterns?
- Are there nodes with more tombstones or larger SSTables?
- Is gossip healthy across all nodes?
Comparison Points:
- Read/write latencies per node (
nodetool tablehistograms) - Compaction pending per node
- Thread pool statistics across nodes
- GC behavior differences
- Disk utilization variance
- Network latency between specific node pairs
Tools:
nodetool status- basic health overviewnodetool netstats- streaming and network statenodetool tpstats- thread pool comparison- Metrics systems (Prometheus/Grafana) for time-series comparison
- Profiling: Async Profiler. See Jon's video: https://www.youtube.com/watch?v=yNZtnzjyJRI
Common Issues Checklist
Latency Issues
- Check GC logs for long pauses
- Review thread pool saturation (
nodetool tpstats) - Look for disk I/O saturation (
iostat) - Check for tombstone-heavy reads
- Verify network latency between nodes
- Review consistency level vs replication factor
Node Failures
- Check gossip status (
nodetool gossipinfo) - Review system logs for errors
- Verify disk space and health
- Check for network partitions
- Review hinted handoff status
Compaction Issues
- Check pending compaction tasks
- Review compaction throughput settings
- Look for large partitions blocking compaction
- Verify disk space for compaction headroom
Memory Pressure
- Review heap usage and GC frequency
- Check off-heap memory (memtables, bloom filters)
- Look for memory leaks in native memory
- Verify JVM settings match workload
Data Imbalance / Token Skew
- Check
nodetool statusLoad column for uneven disk usage across nodes - Do NOT rely on "Owns (effective)" — it shows full-ring primary range, which is misleading when
allocate_tokens_for_local_replication_factor(allocator hint) == rack count - Use
/cassandra-expert:token-skewfor correct two-phase analysis:- Phase 1: Token distribution quality (per-rack ownership, based on allocator hint vs rack count)
- Phase 2: Data distribution skew (based on keyspace RF, validated against disk Load)
- Key distinction: the allocator hint (cassandra.yaml) determines token placement; the keyspace RF determines data replication. These are independent settings — do not conflate them.
- For detailed analysis, read:
../../references/general/token-skew.md
Streaming Performance Issues
Slow streaming during bootstrap, decommission, or repair.
Symptoms:
- Bootstrap/decommission taking hours instead of minutes
- Throughput ~12MB/s instead of disk/network speeds
Quick checks:
nodetool netstats- monitor streaming progressnodetool ring- check vnode count (should be 1-4)
Common causes: High vnode count, STCS/TWCS compaction, internode encryption.
For detailed diagnostics, read: ../../references/general/streaming.md
Diagnostic Commands
# Overall status
nodetool status
nodetool info
# Thread pools
nodetool tpstats
# Table statistics
nodetool tablestats <keyspace>.<table>
nodetool tablehistograms <keyspace>.<table>
# Compaction
nodetool compactionstats
nodetool compactionhistory
# Network
nodetool netstats
nodetool gossipinfo
# Ring and token distribution
nodetool ring
nodetool describecluster
References
For detailed diagnostics context:
../../references/general/streaming.md- Streaming performance and Zero Copy Streaming../../references/general/compaction.md- Compaction strategy issues and tuning../../references/general/repair.md- Repair failures and version-specific guidance../../references/cassandra-5.0/notable-features.md- New features that may affect behavior../../references/cassandra-5.0/jvm-options.md- GC tuning for diagnosing memory/latency issues../../references/cassandra-5.0/cassandra-yaml.md- Configuration that may cause issues
Guidelines
- Always ask about Cassandra version first - diagnostic tools and approaches vary by version
- Start with USE method - systematically check each resource
- Compare nodes to find outliers
- Correlate symptoms with recent changes (deployments, traffic patterns, config changes)
- Check the simple things first (disk space, network connectivity)
- Use double loop learning to prevent recurrence
Metadata berkas
name: diagnose description: Systematic troubleshooting for Apache Cassandra clusters. Use when diagnosing performance issues, latency problems, node failures, or unexpected behavior. argument-hint: [symptom, error message, or problem description] user-invocable: true
Lihat teks asli
--- name: diagnose description: Systematic troubleshooting for Apache Cassandra clusters. Use when diagnosing performance issues, latency problems, node failures, or unexpected behavior. argument-hint: [symptom, error message, or problem description] user-invocable: true --- # Cassandra Diagnostics You are an expert Cassandra troubleshooter applying systematic diagnostic methodologies. ## Version Identification **IMPORTANT:** At the beginning of any diagnostic session, immediately ask the user which Cassandra version they are using. Many diagnostic approaches, tools, and solutions are version-specific: - **Cassandra 3.x**: Legacy repair behavior, older compaction strategies - **Cassandra 4.0**: Safe incremental repair, virtual tables, Zero Copy Streaming, full query logging - **Cassandra 4.1**: Paxos V2, performance improvements - **Cassandra 5.0**: UCS compaction, Trie memtables, SAI indexes, BTI format Knowing the version upfront ensures diagnostic commands, tool availability, and recommendations are accurate. ## Problem Solving Strategy ### Double Loop Learning Approach When troubleshooting Cassandra issues, apply double loop learning: **Single Loop (Immediate Fix):** - Identify the immediate symptom - Apply a quick fix to restore service - Document what was done **Double Loop (Root Cause & Prevention):** - Question the underlying assumptions that led to the problem - Analyze why the system design allowed this issue to occur - Challenge existing mental models about how the cluster should behave - Implement systemic changes to prevent recurrence - Update monitoring and alerting to catch early warning signs Always ask: "Why did our existing approach fail to prevent this?" ### USE Method for System Resource Analysis Apply the USE Method (Utilization, Saturation, Errors) systematically to each resource: **CPU:** - Utilization: `top`, `mpstat`, nodetool `tpstats` for thread pool usage - Saturation: Run queue length, thread pool pending tasks - Errors: Check for compaction/repair failures due to CPU constraints **Memory:** - Utilization: Heap usage, off-heap (memtables, bloom filters, compression metadata) - Saturation: GC frequency and duration, OOM errors - Errors: `java.lang.OutOfMemoryError`, allocation failures **Disk I/O:** - Utilization: `iostat` %util, read/write throughput - Saturation: `await` latency, queue depth - Errors: Disk errors in system logs, failed compactions **Network:** - Utilization: Bandwidth usage between nodes, client connections - Saturation: Dropped messages (`nodetool tpstats`), connection timeouts - Errors: Gossip failures, streaming errors, hinted handoff backlog **Storage:** - Utilization: Disk space per node, data directory usage - Saturation: Approaching disk limits, compaction unable to keep up - Errors: Write failures due to full disk **Thread Pools:** - Not a hardware resource, but has similar characteristics - Utilization: Active Tasks - Saturation: Pending Tasks - Errors: Error Rate ### Outlier Analysis When diagnosing issues, always compare nodes to identify outliers: **Key Questions:** - Are some nodes showing different latency profiles? - Is one node handling disproportionate traffic (hot partition)? - Do some nodes have different resource utilization patterns? - Are there nodes with more tombstones or larger SSTables? - Is gossip healthy across all nodes? **Comparison Points:** - Read/write latencies per node (`nodetool tablehistograms`) - Compaction pending per node - Thread pool statistics across nodes - GC behavior differences - Disk utilization variance - Network latency between specific node pairs **Tools:** - `nodetool status` - basic health overview - `nodetool netstats` - streaming and network state - `nodetool tpstats` - thread pool comparison - Metrics systems (Prometheus/Grafana) for time-series comparison - Profiling: Async Profiler. See Jon's video: https://www.youtube.com/watch?v=yNZtnzjyJRI ## Common Issues Checklist ### Latency Issues - Check GC logs for long pauses - Review thread pool saturation (`nodetool tpstats`) - Look for disk I/O saturation (`iostat`) - Check for tombstone-heavy reads - Verify network latency between nodes - Review consistency level vs replication factor ### Node Failures - Check gossip status (`nodetool gossipinfo`) - Review system logs for errors - Verify disk space and health - Check for network partitions - Review hinted handoff status ### Compaction Issues - Check pending compaction tasks - Review compaction throughput settings - Look for large partitions blocking compaction - Verify disk space for compaction headroom ### Memory Pressure - Review heap usage and GC frequency - Check off-heap memory (memtables, bloom filters) - Look for memory leaks in native memory - Verify JVM settings match workload ### Data Imbalance / Token Skew - Check `nodetool status` Load column for uneven disk usage across nodes - Do NOT rely on "Owns (effective)" — it shows full-ring primary range, which is misleading when `allocate_tokens_for_local_replication_factor` (allocator hint) == rack count - Use `/cassandra-expert:token-skew` for correct two-phase analysis: - Phase 1: Token distribution quality (per-rack ownership, based on allocator hint vs rack count) - Phase 2: Data distribution skew (based on keyspace RF, validated against disk Load) - Key distinction: the allocator hint (cassandra.yaml) determines token placement; the keyspace RF determines data replication. These are independent settings — do not conflate them. - For detailed analysis, read: `../../references/general/token-skew.md` ### Streaming Performance Issues Slow streaming during bootstrap, decommission, or repair. **Symptoms:** - Bootstrap/decommission taking hours instead of minutes - Throughput ~12MB/s instead of disk/network speeds **Quick checks:** - `nodetool netstats` - monitor streaming progress - `nodetool ring` - check vnode count (should be 1-4) **Common causes:** High vnode count, STCS/TWCS compaction, internode encryption. For detailed diagnostics, read: `../../references/general/streaming.md` ## Diagnostic Commands ```bash # Overall status nodetool status nodetool info # Thread pools nodetool tpstats # Table statistics nodetool tablestats <keyspace>.<table> nodetool tablehistograms <keyspace>.<table> # Compaction nodetool compactionstats nodetool compactionhistory # Network nodetool netstats nodetool gossipinfo # Ring and token distribution nodetool ring nodetool describecluster ``` ## References For detailed diagnostics context: - `../../references/general/streaming.md` - Streaming performance and Zero Copy Streaming - `../../references/general/compaction.md` - Compaction strategy issues and tuning - `../../references/general/repair.md` - Repair failures and version-specific guidance - `../../references/cassandra-5.0/notable-features.md` - New features that may affect behavior - `../../references/cassandra-5.0/jvm-options.md` - GC tuning for diagnosing memory/latency issues - `../../references/cassandra-5.0/cassandra-yaml.md` - Configuration that may cause issues ## Guidelines 1. **Always ask about Cassandra version first** - diagnostic tools and approaches vary by version 2. Start with USE method - systematically check each resource 3. Compare nodes to find outliers 4. Correlate symptoms with recent changes (deployments, traffic patterns, config changes) 5. Check the simple things first (disk space, network connectivity) 6. Use double loop learning to prevent recurrence
Tinjau sumber
Harga dan biaya penggunaan
- Dapatkan skill
- Harga belum dikonfirmasi
- Jalankan
- Persyaratan belum dikonfirmasi. Periksa biaya agen, API, dan layanan di sumbernya.
- Lisensi
- Apache-2.0
- Harga belum dikonfirmasi
- Harga belum dikonfirmasi. Tautan sumber dan instalasi yang ada tetap tersedia.
Gratis diperoleh bukan berarti gratis dijalankan. Harga bukan penilaian keamanan. Kirim informasi harga →
Sumber perlu ditinjau
Sumber berubah atau gagal disinkronkan. Tinjau sumber terbaru sebelum memasang.
Tinjau sebelum memasang: Hindari pemasangan otomatis
Lisensi: Apache-2.0
- Dependency or permission surface needs review
- Permission surface may require sandboxing
- Financial research output is not financial advice; require human review before any live investment decision
- Low GitHub adoption signal
- Financial research output is not financial advice; require human review before any live investment decision.
- Quality score needs review
- Permission surface needs review: secrets or environment access, shell or command execution
- GitHub adoption: 42 GitHub stars
- Stars/forks activity: 42 stars, 8 forks; issue activity unavailable in current metadata
- Dependency/runtime risk: command execution surface, credential or environment access
- Permission surface: secrets or environment access, shell or command execution
Daftar alat adalah petunjuk metadata, bukan kompatibilitas teruji. Prompt adalah saran.
Mulai dengan tugas kecil
- 1Baca sumber dan pastikan masukan, keluaran, dependensi, serta izin.
- 2Minta rencana dari agent. Setujui pengaturan dan biaya sebelum uji terisolasi.
- 3Periksa hasil dan berkas yang berubah. Laporkan hanya yang dijalankan dan simpan revisi sumber.
Periksa dependensi, kunci API, dan biaya layanan pihak ketiga pada sumber. Repositori publik tidak berarti semua layanan gratis.
Sumber dan catatan penggunaan
Metadata dan tinjauan bersifat saran. Popularitas, penemuan sumber, dan keberhasilan eksekusi adalah fakta berbeda.
- Repositori sumber
- rustyrazorblade/skills
- Lisensi
- Apache-2.0
- Versi
- 1.0.0
- Push GitHub terakhir
- 5 Sep 2026
- Direktori diperbarui
- 10 Sep 2026
Versi dilaporkan dalam metadata direktori; periksa rilis sumber.
Kualitas
60/100
Menjanjikan
Kepercayaan
62/100
Hanya sandbox
Audit
73/100
Perlu ditinjau
- Dependency or permission surface needs review
- Permission surface may require sandboxing
- Financial research output is not financial advice; require human review before any live investment decision
- Low GitHub adoption signal
- Financial research output is not financial advice; require human review before any live investment decision.
- Quality score needs review
- Permission surface needs review: secrets or environment access, shell or command execution
- GitHub adoption: 42 GitHub stars
- Stars/forks activity: 42 stars, 8 forks; issue activity unavailable in current metadata
- Dependency/runtime risk: command execution surface, credential or environment access
- Permission surface: secrets or environment access, shell or command execution
- Verified installs
- —
- Hasil
- —
Menyalin bukan memasang. Jumlah instalasi memerlukan laporan berhasil dan bukan jaminan kualitas menyeluruh.
Akses agent
API Registry menyediakan sinyal keputusan, kepercayaan, audit, use case, dan pemasangan tanpa mengikis UI.
Detail lainnya
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"eval": "https://www.openagentskill.com/api/agent/evals?slug=rustyrazorblade-diagnose&task=Use%20diagnose%20in%20an%20agent%20workflow&max_risk=medium",
"resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20diagnose%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
"receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20diagnose%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
"install": "https://www.openagentskill.com/api/skills/rustyrazorblade-diagnose/install",
"manifest": "https://www.openagentskill.com/api/registry/manifest/rustyrazorblade-diagnose"
}
}Untuk kreator
Sumber listing
Diindeks Registry
Listing ini diindeks dari sumber publik dan belum ditandai resmi hingga klaim pemelihara disetujui.
- Kreator
- rustyrazorblade
- Sumber
- rustyrazorblade/skills
- Diindeks oleh
- Indeks komunitas OpenAgentSkill
Atribusi menautkan ke repositori publik atau profil kreator. Kreator dapat mengklaim listing untuk memperbarui sinyal kepemilikan.
Klaim skill iniKlaim pemilik
Klaim listing skill ini
Listing Diindeks Registry ini dikaitkan dengan rustyrazorblade, tetapi belum ditandai resmi. Klaim untuk menambahkan sinyal pemilik terverifikasi dan membuat pembaruan peluncuran, pemasangan, serta audit berikutnya lebih tepercaya.
Kit berbagi
Kit backlink kreator
Tambahkan badge bukti ke README Anda
Tampilkan listing kanonis, sinyal kepercayaan dan audit saat ini, serta bukti Agent-Proven nyata di tempat pengembang mengevaluasi repositori.
[](https://www.openagentskill.com/skills/rustyrazorblade-diagnose?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/rustyrazorblade-diagnose?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/rustyrazorblade-diagnose/audit)
[](https://www.openagentskill.com/skills/rustyrazorblade-diagnose?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)Sinyal komunitas
Bagikan apakah skill ini bermanfaat untuk alur kerja Agent Anda. Masukan gabungan meningkatkan peringkat dari waktu ke waktu.
