Python API and CPU Monitoring Script

🔢 Python Data Types (With Real Use) ✔ int → CPU usage (80) ✔ str → log message ("Error occurred") ✔ list → multiple servers ✔ dict → API response Cloud Support = Data handling Python makes it easy. #Python #TechSkills

🚨 Python Program: Find Errors in Logs ```python log = [ "INFO: Server started", "ERROR: Database failed", "WARNING: High CPU" ] for line in log: if "ERROR" in line: print(line) ``` 💡 Real Cloud Support use case: ✔ Identify issues quickly ✔ Automate troubleshooting #Python #CloudSupport #Automation

0.401 vs 0.928 table accuracy. the only difference? which PDF parser you pick opendataloader-pdf just hit 0.928. same PDFs. same tables. 2.3x more accurate. runs locally. no GPU. no cloud. 60+ pages per second on CPU. the part nobody talks about: built-in prompt injection filtering. turns out PDFs can hide invisible text (zero-size fonts, transparent layers) designed to hijack your LLM. most parsers pass that straight through to your model. 17K+ github stars. python, node, java SDKs. langchain integration in 3 lines. if youre debugging RAG quality and havent looked at your parser, youre optimizing the wrong layer. link in comments

Just finished building an AWS Resource Health Monitor in Python! This automation bot: - Monitors EC2 instances for idle CPU and missing tags - Stores timestamped health reports in S3 - Auto-remediates issues with least privilege IAM permissions - Schedules itself to run daily with EventBridge Built with Python, boto3, and real AWS infrastructure from scratch. Check it out on GitHub 👇:  https://lnkd.in/eKmp7gWd #AWS #Python #CloudComputing #DevOps #boto3 #CloudPractitioner

[Azure Updates] [Launched] Generally Available: Microsoft Agent Framework 1.0. Microsoft Agent Framework is now version 1.0 for both .NET and Python, with stable APIs and a long-term support commitment. Agent Framework 1.0 supports multi-agent orchestration, multi-provider model support, and cross-runtime interoperability via A2A an #azure #azureupdates https://lnkd.in/esqS8KXe

📜 Python Automation: Log Error Counter ```python count = 0 with open("log.txt") as f: for line in f: if "ERROR" in line: count += 1 print("Total Errors:", count) ``` 💡 Real Cloud Support task: ✔ Quick issue detection #Python #LogAnalysis

A stylized SVG illustration that visualizes the full project in a dark, technical aesthetic. It shows the three-stage pipeline on the left (CSV → Python → LDIF), the AWS VPC with the EC2 server and directory tree on the right, the CloudShell terminal with real command syntax, and key metrics summarized at the bottom. ❤️

My multi-agent A2A agent demo/article was accepted on the Google Community channel on Medium!! This paper covers a complete solution that uses the ADK, A2A, Python Backend, and a complete multi-agent architecture. The entire agent system was deployed to a GKE cluster. The Google Cloud Community Channel on Medium is here: https://lnkd.in/e5EvcQzU My article/demo is here: https://lnkd.in/eFP8VZaJ #GDE #ADK #A2A #Python #GKE #GoogleCloud

Developers Deploy Python MCP Servers on Azure Kubernetes Service for Scalable AI Orchestration 📌 Developers now run Python MCP servers on Azure Kubernetes Service, letting AI agents autonomously manage clusters without human oversight. This opens the door to cross-cloud AI orchestration, decoupling tools like Google’s Gemini CLI from vendor lock-in. With auto-scaling, secure auth, and Python 3.13 support, it’s a game-changer for scalable, zero-trust AI infrastructure. 🔗 Read more: https://lnkd.in/dBX8Az3G #Python #Mcp #Azureaks #Aiorchestration #Googlegemini

I realized I was performing the same checks daily: server health, connectivity, logs, and basic validations. While none of these tasks were complex, they accumulated over time, making it easy to overlook something during busy shifts. To address this, I began automating small tasks using simple Python and Bash scripts. These scripts run checks, validate outputs, and flag issues early. The results were significant: • Reduced manual effort • Faster checks • Increased consistency This experience highlighted an important lesson: automation isn't solely about saving time; it's also about minimizing human error. Now, whenever I find myself repeating a task multiple times, I ask myself: can this be automated #automation #datacenter #python #devops #infrastructure