amg-check-pg-flex
Fleet-wide PostgreSQL Flexible Server health check — scans CPU, memory, storage, IOPS, disk bandwidth, and connection metrics across all servers, then deep-dives into abnormal servers with resource logs and correlation analysis. Tracks known issues across sessions via persistent report. Uses AMG-MCP pulse check for Tier 1 triage, then batched Azure Monitor queries for Tier 2 investigation. On first run, auto-discovers datasource UID and prompts for subscription ID.
Skill body
Runtime Context
- Current UTC time: !
date -u +%Y-%m-%dT%H:%M:%SZ - Config: !
cat memory/amg-check-pg-flex/config.md 2>/dev/null || echo "NOT_CONFIGURED" - Prior report: !
[ -f memory/amg-check-pg-flex/report.md ] && echo "exists ($(grep -c '^### BUG-' memory/amg-check-pg-flex/report.md) bugs documented)" || echo "not found" - Arguments: time-range=$0, subscription-override=$1
Known Issues: Before presenting findings, cross-reference results against
memory/amg-check-pg-flex/report.md.
AMG PostgreSQL Flexible Server Health Check
Critical Constraints
- No subagents for MCP. The Agent tool cannot access MCP tools — all MCP calls must be made from the main context.
- Scan every resource. No sampling or early stopping.
- Time format: ISO 8601 UTC with explicit
from/to— NEVER usetimespan(it causes errors). - Parallelism cap: 30 concurrent MCP calls per batch. Reduce to 4-5 if rate-limited.
- Result too large: Save to temp file and parse outside the context window. Prefer
node -e "..."if installed; otherwise fall back topython -c "...",jq, orpwsh -Command "...". Bash permission for the chosen interpreter will be prompted on first use.
Progress Tracking
Update checkboxes as you complete each phase:
- Phase 1a: Datasource validated
- Phase 1b: Servers discovered (N=?)
- Phase 1c: Non-ready servers investigated (if any)
- Phase 2: Pulse check completed (N scanned, N findings)
- Phase 3: Deep metrics for abnormal servers
- Phase 4: Resource logs for abnormal servers
- Report presented
- Known issues updated in
memory/amg-check-pg-flex/report.md
Configuration
If Config shows NOT_CONFIGURED: Run First-Run Setup at the bottom of this file, then return here.
If Config is populated: Extract the datasource UID and subscription ID from the pre-loaded Runtime Context above and use them for all queries. Use $1 as the subscription override if provided.
- Datasource UID: from
## Azure Monitor Datasource>UID - Subscription ID: from
## Subscription(or$1if provided) - Resource Type:
microsoft.dbforpostgresql/flexibleservers(lowercase) - ARM ID template:
/subscriptions/{SUB}/resourceGroups/{RG}/providers/Microsoft.DBforPostgreSQL/flexibleServers/{name}
Time Range
Default: 7 days for metrics, 24 hours for logs. Override with $0 (e.g., 3d). Keep log queries to 1-2 days to avoid timeouts.
Workflow
Phase 1a: Validate Datasource
Call amgmcp_datasource_list (no parameters). Find entry with type == "grafana-azure-monitor-datasource".
- Matches configured UID → proceed.
- Different UID → update
memory/amg-check-pg-flex/config.md, warn user, use new UID. - Not found → abort with error.
Phase 1b: Discover All PostgreSQL Flexible Servers
azureMonitorDatasourceUid: {DATASOURCE_UID}
query: |
resources
| where type == 'microsoft.dbforpostgresql/flexibleservers'
| where subscriptionId == '{SUBSCRIPTION_ID}'
| project name, resourceGroup, location, properties.state, sku.name, sku.tier
| order by location asc, name asc
If multiple subscriptions are configured, query each separately and merge results. Derive region summary by counting servers per location. Flag servers not in “Ready” state. Stop if zero servers found.
Phase 1c: Activity Log for Non-Ready Servers
If any servers are not in “Ready” state, query the activity log for up to 3 of them:
azureMonitorDatasourceUid: {DATASOURCE_UID}
scope: /subscriptions/{SUB}/resourceGroups/{RG}/providers/Microsoft.DBforPostgreSQL/flexibleServers/{name}
startTime: now-3d
endTime: now
select: eventTimestamp,operationName,status,caller,subStatus
If the response exceeds 500 KB, retry with startTime: now-6h. Summarize: operations performed, caller type (service principal vs human), success/in-progress status, likely cause.
Phase 2: Tier 1 — Fleet-Wide Pulse Check
azureMonitorDatasourceUid: {DATASOURCE_UID}
pastDays: 7
scenarios: pg_flex
Scans all servers across 5 scenarios: pg_flex_cpu, pg_flex_memory, pg_flex_storage, pg_flex_disk_iops, pg_flex_disk_bandwidth.
Before moving to Phase 3, verify:
scanSummary.totalResourcesScannedmatches Phase 1 server count.- All 5 scenarios show
status: "completed"inscenarioResults. - If
errorsnon-empty, retry affected scenarios individually (e.g.,scenarios: pg_flex_cpu). - If >10% servers missing, fall back to batched
amgmcp_query_resource_metricfor unscanned servers.
Severity thresholds (findings array):
| Severity | CPU | Memory | Storage | Disk IOPS | Disk BW |
|---|---|---|---|---|---|
| Critical | >90% | >90% | >85% | >90% | >90% |
| Warning | >80% | >80% | >75% | >80% | >80% |
Phase 3: Tier 2 — Deep Metrics for Abnormal Servers
Read reference/phase3-deep-dive.md before starting Phase 3. It contains:
- Core metrics table (always query) and secondary metrics table (query on anomaly)
- Batch strategy: up to 50 comma-separated resource IDs per call, up to 5 parallel metric calls
- Correlation analysis patterns (use ultrathink)
Phase 4: Resource Logs for Abnormal Servers
Read reference/phase4-resource-logs.md before starting Phase 4. It contains:
- 5 KQL query templates: error distribution, top errors, warning messages, log volume, session duration
- Time filter rules (always required to avoid timeouts)
Output
Present the report using the structure in reference/output-format.md.
Classification:
| Severity | Criteria |
|---|---|
| CRITICAL | is_db_alive sustained 0, OR CPU max >90%, OR Memory max >90%, OR Storage >85% |
| WARNING | CPU avg >80%, Memory avg >85%, sustained >60% for 6h+, spike >30pp in 1h, Storage >70%, connections_failed >0, deadlocks >0, disk IOPS/BW >80%, transactionIDs >1B, longest query >300s, replication delay >30s |
| HEALTHY | All metrics within normal ranges |
Update Known Issues
After presenting findings, update memory/amg-check-pg-flex/report.md:
- Read the current file.
- Rebuild the Resource Inventory table at the end: every server, full ARM ID, region, SKU, state. Group by region, sorted alphabetically.
- Update existing bug status from today’s telemetry (resolved / improving / worsening / still active).
- Add new bugs with: severity, server name, region, metric evidence, log evidence, root cause, recommended action.
- Update the “Updated” date header.
Only add genuine issues: sustained high utilization, crash patterns, connection storms, persistent errors. Skip transient single-hour spikes or expected maintenance windows.
Error Handling
See reference/error-handling.md for the full recovery table.
Analysis Guidance
- Known patterns, signals, root causes: reference/analysis-patterns.md
- Optional deep-dive KQL queries: reference/deep-dive-queries.md
First-Run Setup
Run only when Config shows NOT_CONFIGURED. After completing, return to the Workflow above.
1. Discover Datasource UID: Call amgmcp_datasource_list. Filter type == "grafana-azure-monitor-datasource". Prefer uid == "azure-monitor-oob" if multiple match. Abort if zero match.
2. Discover Subscription ID: Run this Resource Graph query to list all subscriptions with PostgreSQL Flexible Servers, then present the results as a table and ask the user which subscription(s) to use:
resources
| where type == 'microsoft.dbforpostgresql/flexibleservers'
| join kind=inner (
resourcecontainers
| where type == 'microsoft.resources/subscriptions'
| project subscriptionId, subscriptionName=name
) on subscriptionId
| summarize ServerCount=count() by subscriptionId, subscriptionName
| order by ServerCount desc
Present the results as a table with columns: Subscription Name, Subscription ID, Server Count. Then ask the user: “Which subscription ID(s) should I configure for this health check?”
3. Write config: Write memory/amg-check-pg-flex/config.md:
# amg-check-pg-flex Configuration
User-specific values for the PostgreSQL Flexible Server health check skill.
This file is auto-generated on first run and can be edited manually.
## Azure Monitor Datasource
- **UID**: {discovered_uid}
- **Name**: {discovered_name}
## Subscription
- {subscription_id}
4. Confirm: Show the resolved config and ask for confirmation before proceeding.