Kubernetes Alerting That Wonât Burn You Out
A practical guide to Kubernetes alertingâcut the noise, catch what matters, and avoid those unnecessary 3AM wake-up calls.
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@anjali shared a link, 1Â year, 1Â month ago
Customer Marketing Manager, Last9
Essential Python Monitoring Techniques You Need to Know
Learn the key techniques to monitor Python performance, catch bottlenecks early, and keep your applications fast and reliable at scale.
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@anjali shared a link, 1Â year, 1Â month ago
Customer Marketing Manager, Last9
The Complete Guide to Node.js Logging Libraries in 2025
Discover the most effective Node.js logging libraries, their implementation patterns, and how to choose the right one for your specific project needs.
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@laura_garcia shared a post, 1Â year, 1Â month ago
Software Developer, RELIANOID
đ¨ Important Azure Update: Basic SKU Public IPs to be Retired by 30 September 2025
If your infrastructure still relies on Basic SKU public IP addresses, now is the time to act. đ Key Date: â All Basic SKU IPs deprecated by 30 September 2025 đ Why upgrade to Standard SKU? â Advanced compatibility with Azure Firewall, NAT Gateway, and Standard Load Balancer đ Stronger security defau..
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@laura_garcia shared a post, 1Â year, 1Â month ago
Software Developer, RELIANOID
đ New Guide Available: Best Practices for Installing RELIANOID Enterprise Edition from ISO
RELIANOID Enterprise Edition is not just a load balancer â it's a next-generation solution built for high-volume, sensitive traffic with unmatched customization and security. Weâve just published a complete guide covering: đ§ Resource Requirements â from 2-core minimal to high-performance setups đ De..
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@readdive shared a post, 1Â year, 1Â month ago
Founder, Read Dive
How Data-Driven Marketers Can Benefit from DevOps Automation
DevOps Automation
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@arunsanna shared a post, 1Â year, 1Â month ago
Enterprise Architect
Beyond Prompts: The Professional Developer's Guide to Gen-AI & Human Collaboration
Effectively using AI coding assistants (sometimes called "Vibe Coding") means treating them like professional collaborators, not magic boxes. Success requires active guidance and integrating AI into disciplined software engineering practices.
Key takeaways:
Plan Thoroughly: Work with the AI to create a detailed project plan before coding.
Build Incrementally: Implement the plan section by section, verifying, testing, and committing (using Git) each piece before moving on.
Use Git Religiously: Version control is crucial for managing AI changes and recovering from errors (don't be afraid to git reset).
Prioritize High-Level Tests: Focus on integration tests that simulate user flows to catch regressions AI might introduce.
Debug Smartly: Feed error messages directly to the AI; reset to a clean state before applying fixes to avoid accumulating "crust."
Customize Your AI: Use instruction files and provide local documentation for better accuracy.
Structure Code Well: Modularity helps both humans and AI understand the codebase.
Stay Flexible: Experiment with different tools (like Cursor, Windsurf) and models (GPT, Claude, Gemini), and use various inputs (screenshots, voice).
Human Oversight is Essential: Always review, test, and understand AI-generated code for quality, security, and maintainability.
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@faun shared a link, 1Â year, 1Â month ago
FAUN.dev()
Systematically Terraforming a Brownfield of Cloud Infrastructure
Terraformstepped into a fintech frenzy and wrangled that infrastructure beast into submission. With its wizardry, the once-chaotic tax gateway evolved into a slick IaC setup. As changes came in hot and fast, the system scaled gracefully instead of exploding into chaos. Terraform sidestepped those th.. read more Â
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@faun shared a link, 1Â year, 1Â month ago
FAUN.dev()
Anatomy of a Database Operation
Ever wonder about the backstage chaos when you whisperSELECTorINSERTinPostgres? Picture the Postgres server process like "Happy Mrs Chicken" from Peppa Pigâperched on port 5432, ready for action. Crave speed? Dive intoPgBouncer. This little trickster pools connections, dodging the traffic jam of end.. read more Â
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@faun shared a link, 1Â year, 1Â month ago
FAUN.dev()
Battle of the AI Code Assistants: Who Writes the Best Python Integration Code?
Plandex AIjust snagged gold with a Python integration that isn't just rich in featuresâit's a fortress of security, exhaustive in testing, and glued to best practices. Over in the design corner,Claude Codestands tall, armed with killer documentation and resource management that could charm a library.. read more Â
Instead of just handing you endless lists of problems or passive videos to watch, Levelop uses an active, AI-guided approach to help you build the right mental models for tough technical interviews.
Here is how it works:
Two Specialized AI Mentors: * Orion (Coding AI): Instead of just telling you that your code is wrong, Orion steps in when your code fails, maps out where your knowledge gap is, and guides you to fix it yourself.
Aurora (System Design AI): Rather than making you watch a 40-minute video, Aurora has a live conversation with you to explain foundational system design concepts before you even start drawing on the canvas.
Sprint-Based Practice: You practice in structured loops called "sprints," which combine both Data Structures & Algorithms (DSA) and system design problems.
Actionable Feedback Loop: At the end of every sprint, you receive a detailed report. It scores your technical skills, gives you a behavioral profile, and ranks the exact weaknesses you need to focus on during your next sprint.
In short, it is a smart, interactive practice arena that focuses on actively fixing your specific weaknesses rather than just tracking how many hours you spend studying.
