This workflow follows the Google Sheets → Telegram recipe pattern — see all workflows that pair these two integrations.
The workflow JSON
Copy or download the full n8n JSON below. Paste it into a new n8n workflow, add your credentials, activate. Full import guide →
{
"name": "Daily Report",
"nodes": [
{
"parameters": {
"rule": {
"interval": [
{
"field": "cronExpression",
"expression": "0 8 * * *"
}
]
}
},
"type": "n8n-nodes-base.scheduleTrigger",
"typeVersion": 1.3,
"position": [
-240,
224
],
"id": "ab57d0e3-3bfe-4114-984d-6cf7517c4c5d",
"name": "Schedule Trigger"
},
{
"parameters": {
"operation": "executeQuery",
"query": "SELECT\n afd_state,\n COUNT(*) as count\nFROM logs\nWHERE classified_at > NOW() - INTERVAL '24 hours'\nGROUP BY afd_state\nORDER BY count DESC;",
"options": {}
},
"type": "n8n-nodes-base.postgres",
"typeVersion": 2.6,
"position": [
-16,
224
],
"id": "ba98beee-a213-4425-a182-9f1af3cec453",
"name": "Stats Volume",
"credentials": {
"postgres": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"jsCode": "// R\u00e9cup\u00e9rer les donn\u00e9es de chaque n\u0153ud\nlet volumeData = [], mttrData = {}, patternsData = [];\n\ntry { volumeData = $('Stats Volume').all().map(i => i.json); } catch(e) {}\ntry { mttrData = $('Stats MTTR+Faux Positifs').first().json; } catch(e) {}\ntry { patternsData = $('Top 5 Patterns').all().map(i => i.json); } catch(e) {}\n\n// Volume par \u00e9tat\nconst volume = { INFO: 0, WARNING: 0, ERROR: 0, ERROR_CASCADE: 0, CRITICAL: 0, RECOVERY: 0 };\nfor (const row of volumeData) {\n if (row.afd_state) volume[row.afd_state] = parseInt(row.count) || 0;\n}\n\nconst totalLogs = Object.values(volume).reduce((a, b) => a + b, 0);\n\n// Top patterns\nconst topPatterns = patternsData.length > 0\n ? patternsData\n .slice(0, 5)\n .map((p, i) => `${i + 1}. ${(p.message || 'N/A').substring(0, 60)} (${p.occurrences || 0}x)`)\n .join('\\n')\n : 'Aucun pattern critique d\u00e9tect\u00e9';\n\nconst statsJson = JSON.stringify({\n total_logs: totalLogs,\n volume,\n mttr_minutes: mttrData.mttr_minutes || 'N/A',\n false_positive_rate: mttrData.false_positive_rate || 0,\n top_patterns: patternsData.slice(0, 3).map(p => p.message || '')\n});\n\nconst today = new Date().toLocaleDateString('fr-FR', {\n weekday: 'long', year: 'numeric', month: 'long', day: 'numeric'\n});\n\nreturn [{\n json: {\n volume,\n totalLogs,\n mttr_minutes: mttrData.mttr_minutes || 'N/A',\n false_positive_rate: mttrData.false_positive_rate || 0,\n topPatterns,\n statsJson,\n today\n }\n}];"
},
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
224,
224
],
"id": "737cbc37-3646-4c6e-b9b5-67553808a0ee",
"name": "Merge des r\u00e9sultats"
},
{
"parameters": {
"jsCode": "\nconst data = $input.first().json;\nconst today = new Date().toLocaleDateString('fr-FR', {\n weekday: 'long', year: 'numeric', month: 'long', day: 'numeric'\n});\n\nconst rawStats = $('Merge des r\u00e9sultats').first().json;\n\nconst whatsappMarkdown = `\ud83d\udcc8 *Rapport LogSentinel \u2014 ${today}*\n\n*Volume 24h :*\n\u2022 INFO : ${rawStats.volume.INFO || 0}\n\u2022 WARNING : ${rawStats.volume.WARNING || 0} \u26a0\ufe0f\n\u2022 ERROR : ${rawStats.volume.ERROR || 0} \ud83d\udd34\n\u2022 CRITICAL : ${rawStats.volume.CRITICAL || 0} \ud83d\udd25\n\n*Performance :*\n\u2022 MTTR moyen : ${rawStats.mttr_minutes} min\n\u2022 Faux positifs : ${rawStats.false_positive_rate}%\n\n*Top patterns :*\n${rawStats.topPatterns}\n\n*Analyse IA :*\n${data.summary}\n\n*Recommandation :*\n${data.recommendation}`;\n \nconst htmlEmail = `\n<h2>Rapport Quotidien LogSentinel</h2>\n\n<p><b>Date:</b> ${today}</p>\n<p><b>Statut Global:</b> ${data.status}</p>\n\n<h3>Volume R\u00e9parti (24h)</h3>\n<ul>\n <li><b>INFO:</b> ${rawStats.volume.INFO || 0}</li>\n <li><b>WARNING:</b> ${rawStats.volume.WARNING || 0}</li>\n <li><b>ERROR:</b> ${rawStats.volume.ERROR || 0}</li>\n <li><b>CRITICAL:</b> ${rawStats.volume.CRITICAL || 0}</li>\n</ul>\n\n<h3>Indicateurs de Performance</h3>\n<ul>\n <li><b>MTTR Moyen:</b> ${rawStats.mttr_minutes} min</li>\n <li><b>Taux Faux Positifs:</b> ${rawStats.false_positive_rate}%</li>\n</ul>\n\n<h3>Top Patterns Critiques</h3>\n<pre>${rawStats.topPatterns}</pre>\n\n<h3>Synth\u00e8se Op\u00e9rationnelle</h3>\n<p>${data.summary}</p>\n\n<h3>Recommandation</h3>\n<p>${data.recommendation}</p>\n`;\n\n// 3. Output both variables for downstream nodes\nreturn [{\n json: {\n whatsappMarkdown,\n htmlEmail\n }\n}];"
},
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
1152,
224
],
"id": "cbaa75de-25f5-425e-a6e1-079a2344fced",
"name": "Synth\u00e8se LLM Groq"
},
{
"parameters": {
"operation": "executeQuery",
"query": "SELECT\n ROUND(AVG(mttr_seconds)/60, 1) AS mttr_minutes,\n ROUND(\n SUM(CASE WHEN command_used = 'FALSE_POSITIVE' THEN 1 ELSE 0 END)::numeric\n / NULLIF(COUNT(*), 0) * 100, 1\n ) AS false_positive_rate\nFROM feedback_corrections\nWHERE corrected_at > NOW() - INTERVAL '24 hours';",
"options": {}
},
"type": "n8n-nodes-base.postgres",
"typeVersion": 2.6,
"position": [
0,
0
],
"id": "3faa7b17-e1fb-4612-b38d-eab26a1a9620",
"name": "Stats MTTR+Faux Positifs",
"credentials": {
"postgres": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"operation": "executeQuery",
"query": "SELECT message, COUNT(*) as occurrences\nFROM logs\nWHERE afd_state IN ('ERROR', 'CRITICAL', 'ERROR_CASCADE')\nAND classified_at > NOW() - INTERVAL '24 hours'\nGROUP BY message\nORDER BY occurrences DESC\nLIMIT 5;",
"options": {}
},
"type": "n8n-nodes-base.postgres",
"typeVersion": 2.6,
"position": [
0,
464
],
"id": "eb0cef70-1b43-42a4-b2b0-ac129f5c0fc4",
"name": "Top 5 Patterns",
"credentials": {
"postgres": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"fromEmail": "={{$env.SMTP_FROM}}",
"toEmail": "={{$env.SMTP_TO}}",
"subject": "[LogSentinel] Rapport quotidien\n",
"html": "={{ $json.htmlEmail}}",
"options": {}
},
"type": "n8n-nodes-base.emailSend",
"typeVersion": 2.1,
"position": [
1456,
384
],
"id": "5ff8b4d7-df91-4000-8fbe-a093d2e48600",
"name": "Email Rapport",
"credentials": {
"smtp": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"method": "POST",
"url": "=https://api.twilio.com/2010-04-01/Accounts/{{$env.TWILIO_ACCOUNT_SID}}/Messages.json",
"authentication": "genericCredentialType",
"genericAuthType": "httpBasicAuth",
"sendBody": true,
"contentType": "form-urlencoded",
"bodyParameters": {
"parameters": [
{
"name": "From",
"value": "={{$env.TWILIO_WHATSAPP_FROM}}"
},
{
"name": "To",
"value": "={{$env.TWILIO_WHATSAPP_ADMIN}}"
},
{
"name": "Body",
"value": "={{$json.whatsappMarkdown}}"
}
]
},
"options": {}
},
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 4.4,
"position": [
1440,
48
],
"id": "9f4c8fcf-480f-4f90-a729-484ae398bdd9",
"name": "Twilio WhatsApp Alert",
"credentials": {
"httpBasicAuth": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"method": "POST",
"url": "={{$env.GROQ_API_URL}}",
"authentication": "genericCredentialType",
"genericAuthType": "httpBearerAuth",
"sendBody": true,
"specifyBody": "json",
"jsonBody": "={{ $json.groq_body }}",
"options": {}
},
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 4.4,
"position": [
688,
224
],
"id": "991d8827-5df6-4a27-8ab6-d16a26e54565",
"name": "Groq API Call",
"credentials": {
"httpBearerAuth": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"jsCode": "const stats = $input.first().json;\n\nlet severity = 'HEALTHY';\n\nif ((stats.volume?.CRITICAL || 0) > 0) {\n severity = 'CRITICAL';\n} else if (\n (stats.volume?.WARNING || 0) > 5 ||\n (stats.volume?.ERROR || 0) > 10\n) {\n severity = 'WARNING';\n}\n\nconst metrics = {\n severity,\n total_logs: stats.totalLogs,\n\n volume: {\n INFO: stats.volume?.INFO || 0,\n WARNING: stats.volume?.WARNING || 0,\n ERROR: stats.volume?.ERROR || 0,\n ERROR_CASCADE: stats.volume?.ERROR_CASCADE || 0,\n CRITICAL: stats.volume?.CRITICAL || 0,\n RECOVERY: stats.volume?.RECOVERY || 0\n },\n\n mttr_minutes: stats.mttr_minutes || 'N/A',\n\n false_positive_rate: stats.false_positive_rate || 0,\n\n top_patterns: stats.topPatterns || 'Aucun pattern'\n};\n\nconst userPrompt = `\nAnalyse les statistiques suivantes des derni\u00e8res 24h:\n\n${JSON.stringify(metrics, null, 2)}\n\nRetourne UNIQUEMENT un JSON valide:\n{\n \"summary\": \"\",\n \"recommendation\": \"\",\n \"status\": \"HEALTHY|WARNING|CRITICAL\"\n}\n`;\n\nreturn [\n {\n json: {\n metrics,\n severity,\n today : stats.today,\n groq_body: {\n model: $env.GROQ_MODEL,\n messages: [\n {\n role: \"system\",\n content:\n \"Tu es un ing\u00e9nieur SRE senior sp\u00e9cialis\u00e9 en observabilit\u00e9.\"\n },\n {\n role: \"user\",\n content: userPrompt\n }\n ],\n temperature: 0.2\n }\n }\n }\n];"
},
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
448,
224
],
"id": "f418f53e-4c11-4636-87b4-55e221632364",
"name": "Build Prompt"
},
{
"parameters": {
"jsCode": "const groq = $input.first().json;\n\n// 1. Extract raw content\nlet content = groq.choices?.[0]?.message?.content || \"\";\n\n// 2. Remove code blocks if present\ncontent = content\n .replace(/```json/g, \"\")\n .replace(/```/g, \"\")\n .trim();\n\n// 3. Try to extract JSON object inside text\nconst jsonMatch = content.match(/\\{[\\s\\S]*\\}/);\n\nlet parsed;\n\ntry {\n if (jsonMatch) {\n parsed = JSON.parse(jsonMatch[0]);\n } else {\n throw new Error(\"No JSON found\");\n }\n} catch (e) {\n\n // fallback safe output\n parsed = {\n summary: \"Le syst\u00e8me est globalement stable.\",\n recommendation: \"Aucune action urgente requise.\",\n status: \"HEALTHY\"\n };\n}\n\n// 4. Normalize fields (safety layer)\nconst result = {\n summary: parsed.summary || \"R\u00e9sum\u00e9 indisponible.\",\n recommendation: parsed.recommendation || \"Aucune recommandation.\",\n status: parsed.status || \"HEALTHY\"\n};\n\nreturn [\n {\n json: {\n ...groq,\n ...result\n }\n }\n];"
},
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
928,
224
],
"id": "b198d821-61d6-4544-9844-fa8a0d243b53",
"name": "Parse AI Response"
}
],
"connections": {
"Schedule Trigger": {
"main": [
[
{
"node": "Stats MTTR+Faux Positifs",
"type": "main",
"index": 0
},
{
"node": "Stats Volume",
"type": "main",
"index": 0
},
{
"node": "Top 5 Patterns",
"type": "main",
"index": 0
}
]
]
},
"Stats Volume": {
"main": [
[
{
"node": "Merge des r\u00e9sultats",
"type": "main",
"index": 0
}
]
]
},
"Merge des r\u00e9sultats": {
"main": [
[
{
"node": "Build Prompt",
"type": "main",
"index": 0
}
]
]
},
"Synth\u00e8se LLM Groq": {
"main": [
[
{
"node": "Twilio WhatsApp Alert",
"type": "main",
"index": 0
},
{
"node": "Email Rapport",
"type": "main",
"index": 0
}
]
]
},
"Stats MTTR+Faux Positifs": {
"main": [
[
{
"node": "Merge des r\u00e9sultats",
"type": "main",
"index": 0
}
]
]
},
"Top 5 Patterns": {
"main": [
[
{
"node": "Merge des r\u00e9sultats",
"type": "main",
"index": 0
}
]
]
},
"Twilio WhatsApp Alert": {
"main": [
[]
]
},
"Groq API Call": {
"main": [
[
{
"node": "Parse AI Response",
"type": "main",
"index": 0
}
]
]
},
"Build Prompt": {
"main": [
[
{
"node": "Groq API Call",
"type": "main",
"index": 0
}
]
]
},
"Parse AI Response": {
"main": [
[
{
"node": "Synth\u00e8se LLM Groq",
"type": "main",
"index": 0
}
]
]
}
},
"active": false,
"settings": {
"executionOrder": "v1",
"binaryMode": "separate"
},
"versionId": "a5f1c4d7-d68a-4fc0-b184-5638c8dc3842",
"meta": {
"templateCredsSetupCompleted": true
},
"id": "HZFt6AhXjiDTBP3V",
"tags": []
}
Credentials you'll need
Each integration node will prompt for credentials when you import. We strip credential IDs before publishing — you'll add your own.
googleSheetsOAuth2ApitelegramApi
Pro
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About this workflow
Daily Report. Uses googleSheets, telegram. Scheduled trigger; 5 nodes.
Source: https://github.com/datvv/Telegram-Attendance-System/blob/db05dad2015ab1d5134f473269bb10e764334e8e/workflows/daily_report.json — original creator credit. Request a take-down →
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