managing-loggly

name	managing-loggly
description	Use when working with Loggly — loggly cloud log management platform for log search, analysis, alerting, and dashboards. Covers log querying with Lucene syntax, field exploration, alert management, and usage analysis. Use when searching Loggly logs, investigating application errors, managing alert configurations, or analyzing log volume patterns.
connection_type	loggly
preload	false

Loggly Monitoring Skill

Query, analyze, and manage Loggly log data using the Loggly API.

API Overview

Loggly uses a REST API at https://<SUBDOMAIN>.loggly.com/apiv2.

Core Helper Function

#!/bin/bash

loggly_api() {
    local endpoint="$1"
    curl -s "https://${LOGGLY_SUBDOMAIN}.loggly.com/apiv2/${endpoint}" \
        -H "Authorization: Bearer $LOGGLY_API_TOKEN"
}

loggly_search() {
    local query="$1"
    local from="${2:--1h}"
    local to="${3:-now}"
    local rsid
    rsid=$(loggly_api "search?q=$(python3 -c "import urllib.parse; print(urllib.parse.quote('${query}'))")&from=${from}&until=${to}&size=50" | jq -r '.rsid.id')
    [ -n "$rsid" ] && loggly_api "events?rsid=${rsid}"
}

MANDATORY: Discovery-First Pattern

Always discover available fields, source groups, and alerts before querying.

Phase 1: Discovery

#!/bin/bash

echo "=== Available Fields ==="
loggly_api "fields" | jq -r '.[] | "\(.name)\t\(.type)"' | sort | head -25

echo ""
echo "=== Source Groups ==="
loggly_api "source-groups" | jq -r '.sourcegroups[] | "\(.id)\t\(.name)"' | head -15

echo ""
echo "=== Saved Searches ==="
loggly_api "saved-searches" | jq -r '.savedsearches[] | "\(.id)\t\(.name)\t\(.query)"' | head -15

echo ""
echo "=== Alerts ==="
loggly_api "alerts" | jq -r '.alerts[] | "\(.id)\t\(.name)\t\(.status)"' | head -15

Phase 2: Analysis

#!/bin/bash

echo "=== Error Logs (last 1h) ==="
loggly_search "syslog.severity:error OR level:error" "-1h" "now" \
    | jq -r '.events[] | "\(.timestamp[0:19])\t\(.event.json.message[0:80] // .event.raw[0:80])"' | head -20

echo ""
echo "=== Log Volume by Level ==="
loggly_api "fields/json.level?from=-1h&until=now&facet_size=10" \
    | jq -r '.json.level[] | "\(.term)\t\(.count)"' | sort -t$'\t' -k2 -rn | head -10

echo ""
echo "=== Log Volume by Source ==="
loggly_api "fields/syslog.appName?from=-1h&until=now&facet_size=15" \
    | jq -r '.syslog.appName[] | "\(.term)\t\(.count)"' | sort -t$'\t' -k2 -rn | head -15

echo ""
echo "=== Active Alerts ==="
loggly_api "alerts" | jq -r '.alerts[] | select(.status == "active") | "\(.name)\t\(.query)\t\(.threshold)"' | head -10

Output Rules

• TOKEN EFFICIENCY: Target ≤50 lines — use size parameter and facet queries for aggregation
• Use Lucene query syntax for filtering (e.g., level:error AND app:myservice)
• Use field facets for volume breakdowns instead of counting raw events

Output Format

Present results as a structured report:

Managing Loggly Report
══════════════════════
Resources discovered: [count]

Resource       Status    Key Metric    Issues
──────────────────────────────────────────────
[name]         [ok/warn] [value]       [findings]

Summary: [total] resources | [ok] healthy | [warn] warnings | [crit] critical
Action Items: [list of prioritized findings]

Target ≤50 lines of output. Use tables for multi-resource comparisons.

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

Shortcut	Counter	Why
"I'll skip discovery and check known resources"	Always run Phase 1 discovery first	Resource names change, new resources appear — assumed names cause errors
"The user only asked for a quick check"	Follow the full discovery → analysis flow	Quick checks miss critical issues; structured analysis catches silent failures
"Default configuration is probably fine"	Audit configuration explicitly	Defaults often leave logging, security, and optimization features disabled
"Metrics aren't needed for this"	Always check relevant metrics when available	API/CLI responses show current state; metrics reveal trends and intermittent issues
"I don't have access to that"	Try the command and report the actual error	Assumed permission failures prevent useful investigation; actual errors are informative