Archive for the ‘N8N’ Category

AI Workflow Automation N8N 2.33.7 – new features and bug fixes

Sonntag, August 9th, 2026

GEEKOM AI Mini PC IT13 Max – gebaut für einen lokalen KI Server der N8N Workflows Hermes Claude Code Kimi Ollama LM Studio und mehr verwaltet

Sonntag, August 2nd, 2026

AI Workflow Automation N8N – the new AI Assistant is an agent that lives inside and builds workflows from plain language

Dienstag, Juli 28th, 2026

AI Workflow Automation N8N – setup for the Microsoft Agent 365 trigger so workflows can use directly Word Excel Teams and even eMail

Mittwoch, Juli 22nd, 2026

AI Workflow Automation N8N – create YouTube translations easily #6

Montag, Juli 20th, 2026

AI Workflow Automation N8N – how to build your own AI powered YouTube localization assistant using Ollama and N8N this ’step-by-step‘ tutorial shows you how to create a custom AI agent that automatically handles video title and description translations #5

Freitag, Juli 17th, 2026

AI Workflow Automation N8N – mit dieser Plattform können Teams bei Mercedes-Benz weltweit KI gestützte Workflows selbst erstellen

Mittwoch, Juli 15th, 2026

AI Workflow Automation N8N – Working with Documents RAG #3

Dienstag, Juli 14th, 2026

Deutsche Telekom & N8N – erweitern ihre Partnerschaft denn N8N ist eines der am schnellsten wachsenden Unternehmen Europas im Bereich KI und Agenten Orchestrierung

Montag, Juli 13th, 2026

n8n 2.29.9 ‚Assistant‘ – now has a built in AI agent that builds your workflows for you

Samstag, Juli 11th, 2026

AI Workflow Automation N8N – Complete Local Setup Guide #1

Freitag, Juli 10th, 2026

The name n8n is short for „nodemation“ (a blend of node-based programming and automation). The 8 represents the exact number of letters between the two „n“s in nodemation: n-[eight letters]-n = n8n

Sonntag, Juni 21st, 2026

AI Workflow Automation N8N 2.21.7 – RAG Text Splitters or Document Chunking

Sonntag, Juni 21st, 2026

AI Workflow Automation N8N 2.21.7 – analyzing Oracle AWR is highly effective for automating system monitoring parsing errors and getting incident reports

Donnerstag, Juni 18th, 2026

You are an expert Oracle Database Administrator and Performance Tuning specialist. Your task is to analyze the provided Oracle AWR (Automatic Workload Repository) report text and provide a concise, high-level summary using a Traffic Light Metric system.

Please strictly follow this structure for your output:

### 1. Executive Summary & Findings Count
* **Total Critical Findings:** [Count]
* **Total Warning Findings:** [Count]
* **Total Info/Advisory Findings:** [Count]
* *A 2-3 sentence overview of the database health during this snapshot interval.*

### 2. Traffic Light Analysis
Categorize your findings using the following definitions:
🔴 CRITICAL (Red): Severe bottlenecks, high CPU/IO waits, latch contention, or symptoms causing immediate application degradation.
🟡 WARNING (Yellow): Areas nearing capacity, sub-optimal configurations, or moderate wait events that need monitoring.
🟢 HEALTHY / INFO (Green): System components performing well, or general inventory data.

Format this section as a Markdown table:
| Status | Category (e.g., CPU, IO, Wait Events, SQL) | Finding Description | Impact & Metric (e.g., % DB Time) | Recommendation |
| :— | :— | :— | :— | :— |
| 🔴 CRITICAL | | | | |
| 🟡 WARNING | | | | |

### 3. Key Areas to Investigate
Focus specifically on the top anomalies found in these sections of the report:
– Load Profile (DB Time vs Elapsed Time)
– Top 10 Foreground Wait Events
– CPU/Memory (SGA/PGA) utilization
– Top SQL by DB Time / Shared Memory

Keep the analysis highly technical, concise, and actionable. Avoid generic advice; refer directly to the metrics, percentages, and event names found in the provided report text.

AI Workflow Automation N8N 2.21.7 – how to generate beautiful PDF reports

Sonntag, Juni 14th, 2026