Cisco Modeling Labs Day-One Setup Simplified with Python GUI

Python's elegance and vast ecosystem often lead teams to overlook its inherent limitations when facing genuinely CPU-bound workloads in production. The Global Interpreter Lock (GIL) ensures that parallel execution across multiple CPU cores within a single Python process remains an illusion, regardless of threading. While `asyncio` transforms I/O concurrency, it provides no magical solution for compute-intensive operations. An `await` merely yields control during an I/O wait, allowing other tasks to run; it does not distribute CPU work across cores. Relying on `asyncio` for substantial CPU-bound processing within a single Python process is a common architectural misstep that inevitably leads to poor scaling and unpredictable latency. For scenarios demanding true parallelism, genuine multiprocessing solutions, offloading work to dedicated queues and microservices, or even evaluating alternative runtimes and languages designed for native concurrency, become not just optimisations but fundamental architectural considerations. These approaches provide the isolation and execution model needed to fully utilise modern multi-core hardware. Before committing to a Python-only solution for CPU-heavy services, engineers should meticulously benchmark concurrent CPU utilisation and throughput under realistic load conditions. If you're building or scaling an engineering team, reach out at hr@kivenconsulting.com or kivenconsulting.com #KivenConsulting #SoftwareEngineering #IndiaTech #TechLeadership

"This is not a traditional coding error. It is an architectural design decision baked into Anthropic’s official MCP SDKs across every supported programming language, including Python, TypeScript, Java, and Rust. Any developer building on the Anthropic MCP foundation unknowingly inherits this exposure." https://lnkd.in/ejgYzrEj).

I enjoyed covering AUTOCOR exam blueprint topic 1.4 which tests an engineer's ability to construct a network automation solution with Python. Although Python is unlikely to be the go-to tool for NetDevOps engineers who have Ansible and Terraform at their disposal for most automation workloads, there may still be a requirement to use Python when legacy systems which don't support modern APIs are deployed. There are lots of packages and libraries that can be installed and imported with Python, which do most of the heavy lifting. Today I have been using netmiko to configure devices in my Cisco Modelling Labs environment, and it's been nice to see how much of the content I can remember more easily this second time through, like what parameters must be included with ConnectHandler to connect to a device, and how to send config files from within the python program. Now I have reviewed how to create network automation solutions using Ansible, Terraform, and Python, I have a better understanding of the differences between them, where I think each could be used in a network automation solution, and also the similarities between each. I think a better understanding of data serialization and being able to interpret structured data slightly better has certainly helped me to pick up more knowledge this time round. #Terraform #Ansible #Python #Cisco

In today’s networking world, Python and Ansible are transforming how engineers manage infrastructure reducing errors, saving time, and scaling operations effortlessly. Python gives you the power to control your network with logic and flexibility, while Ansible makes deployment simple, structured, and repeatable. Together, they eliminate repetitive CLI work and turn complex tasks into clean, automated workflows. We have designed a customized course content on Network Automation. Let's connect on WhatsApp for more details - https://wa.link/2s5dlx #networking #cisco #networkengineer #python #ansible #automation Deepanshu Abhijit Nitish Chirag Ravi Anisha Ankit Rinki Pooja Kumari

Still configuring networks manually? That’s time-consuming, error-prone and increasingly outdated. Python is quickly becoming a must-have skill for network engineers, not to turn you into a developer, but to help you: ⚡ Automate repetitive tasks ⚡ Reduce outages caused by human error ⚡ Manage multi-vendor environments more efficiently The good news? You don’t need to be a programmer to get started. Our 5-day Network Automation with Python course is built for engineers who want practical, hands-on skills they can use immediately. If automation is on your roadmap this year comment or message me if you want the details.

Still configuring networks manually? That’s time-consuming, error-prone and increasingly outdated. Python is quickly becoming a must-have skill for network engineers, not to turn you into a developer, but to help you: ⚡ Automate repetitive tasks ⚡ Reduce outages caused by human error ⚡ Manage multi-vendor environments more efficiently The good news? You don’t need to be a programmer to get started. Our 5-day Network Automation with Python course is built for engineers who want practical, hands-on skills they can use immediately. If automation is on your roadmap this year comment or message me if you want the details.

Still configuring networks manually? That’s time-consuming, error-prone and increasingly outdated. Python is quickly becoming a must-have skill for network engineers, not to turn you into a developer, but to help you: ⚡ Automate repetitive tasks ⚡ Reduce outages caused by human error ⚡ Manage multi-vendor environments more efficiently The good news? You don’t need to be a programmer to get started. Our 5-day Network Automation with Python course is built for engineers who want practical, hands-on skills they can use immediately. If automation is on your roadmap this year comment or message me if you want the details.

The OX Security Research team has identified a critical, systemic vulnerability within the Model Context Protocol (MCP), which serves as the industry standard for AI agent communication developed by Anthropic. This vulnerability allows for Arbitrary Command Execution (RCE) on any system utilizing a susceptible MCP implementation, providing attackers with direct access to sensitive user data, internal databases, API keys, and chat histories. Importantly, this issue is not merely a coding error; it stems from an architectural design decision embedded in Anthropic’s official MCP SDKs across all supported programming languages, including Python, TypeScript, Java, and Rust. Consequently, any developer building on the Anthropic MCP framework unknowingly inherits this risk. https://lnkd.in/dV2KG8Cz

A severe architectural vulnerability in Anthropic’s Model Context Protocol (MCP) allows arbitrary command execution (RCE) by design, affecting its official SDKs in Python, TypeScript, Java, and Rust. The flaw impacts over 150 million downloads, thousands of exposed servers, and up to 200,000 instances across AI tools like LangChain and LiteLLM, enabling attackers to steal data, API keys, and execute commands via prompt injection or registry poisoning. Researchers from OX Security disclosed 10 CVEs, with real exploits already demonstrated on production systems, yet Anthropic called the behavior “expected” and left fixes to developers. Experts urge immediate mitigations such as sandboxing, blocking public access, and using official registries until a protocol-level patch is issued https://lnkd.in/drnBtsPj

🚀 System Monitoring & Alert Pipeline I recently built a production-style system monitoring and alert pipeline using Python. This system automatically: • Monitors CPU, memory, and disk usage • Detects issues and scans logs for errors • Sends email alerts when thresholds are exceeded • Generates system health reports • Runs automatically using cron scheduling This project helped me strengthen my skills in automation, system reliability, and production scripting — all essential for Data Engineering and DevOps environments. #Python #DataEngineering #Automation #DevOps #LearningInPublic #TechPortfolio https://lnkd.in/enVvnqDv