Ayush @TheAyushOps

@fromcodetocloud One of the underrated thing in software engineering.

@vguleria19 Thanks for the clarification!

React.js vs Next.js - what’s the difference?

🔥 The strongest DevOps engineers don't just fix production incidents. They ask: "Why did this happen?" Then: Incident → Root cause → Fix → Automation → Prevention If someone manually fixes the same problem every month, that's not reliability. That's a recurring task waiting to be automated. The goal of DevOps isn't to become better at firefighting. It's to create systems that need less firefighting.

Horizontal scaling is useless if your database is still a single point of failure. Don't build a 10-lane highway that leads directly into a 1-lane tunnel.

We are moving from the era of “How do I code this?” to “How do I prompt this?” Clear thinking is becoming the ultimate tech stack.

@itskamrankhan Let’s connect

If you are in tech, let's connect!

People who actually work in AI… What do you think the next 5–15 years will really look like? Not the hype. Not the “AI will take all jobs” headlines. I’m talking about what you’re seeing from the inside: 🤖 Will AI agents replace entire workflows? 💻 Will software engineers still write most of the code? 🧠 Will AI become a teammate rather than a tool? 🏢 How will companies actually restructure around AI? 🚀 What skills will matter most? If you work in AI/ML, I’d genuinely love to hear your prediction. Where do you think?

Good morning, everyone! ☀️ And btw… Happy Engineers’ Day! 🤞 But wait… 👀 Are you REALLY an engineer? 😂 I’m a Software Engineer 🫠 My engineering toolkit: 💻 Code 🐛 Bugs ☕ Coffee 🔥 Production issues ☁️ Cloud ⚙️ Automation 📜 Scripts 😵 It works on my machine What’s yours? 😂👇

🤖 Putting an LLM behind an API doesn't make a production AI system. You also need to think about: Prompt management Model selection RAG Latency Token cost Guardrails Evaluation Observability Data privacy Fallbacks The model is only one component. Production AI is an engineering system around the model. That's where DevOps and AI engineering start to overlap.

🧠 The best system design isn't the one with the most technologies. You don't need: Kafka + Redis + Kubernetes + Elasticsearch + 12 microservices for every application. Every component adds: -> Operational complexity -> Monitoring -> Failure modes -> Cost -> Security requirements Start simple. Add complexity only when the requirements justify it. Architecture should solve problems - not create new ones.

🧠 "Add more logs" isn't an observability strategy. A production log should help answer: What happened?
When?
Where?
Why?
Which request?
Which service?
What was the impact? Structured logging + correlation IDs + consistent fields are far more useful than thousands of random print() statements. More logs ≠ better observability.

🤖 AI can generate Terraform, Kubernetes YAML and CI/CD pipelines in seconds. But generated code can still be: ❌ Insecure
❌ Expensive
❌ Over-engineered
❌ Incorrect
❌ Impossible to maintain AI increases the speed of implementation. Engineering judgment determines whether the implementation is actually good. The bottleneck is moving from typing → validating.

If you are in tech, let’s connect.

@m0rezk @X Hi, let’s connect!

Any Ruby dev here?

Your AI coding tool reached its limit. It resets in 5 hours. What do you do until then?

AWS is quietly changing how engineers build, deploy, modernize, and operate applications. This week alone, we saw major updates across AI, Lambda, .NET modernization, Outposts, developer security, and real-time video intelligence. 🧵 Here are 8 AWS updates worth knowing: 👇 1/8 - AI on Amazon Bedrock 🤖 OpenAI GPT-6 Astra is now generally available on Amazon Bedrock. Key highlights include: • 1M-token input context • Advanced reasoning • Autonomous browsing • Bedrock API integration This could simplify how enterprises integrate advanced AI capabilities into existing AWS workloads. 2/8 - Amazon Quick gets smarter Amazon Quick is adding always-on agents that can continue running scheduled tasks even when devices are offline. It also brings improvements around: • Agent usage • Daily briefings • MDM • Purview DLP • Enterprise desktop controls The direction is clear: AI agents are moving from assistants to persistent workers. 3/8 - Kiro expands to universities 🎓 AWS is expanding free Kiro access to 132 universities across 18 countries. Eligible students get: • 1 year of free access • 1,000 monthly credits • Kiro Web This significantly expands access to AI-assisted software development for students. 4/8 - AWS Transform for .NET AWS Transform for .NET modernization is now generally available through the CLI. That matters for engineering teams because modernization workflows can now become more scriptable and automation-friendly. It can also generate unit tests for migrated code. 5/8 - New AWS Outposts generation AWS announced second-generation single-rack Outposts. The 42U rack supports up to: • 2,688 vCPUs • 100 TB of EBS storage Useful for organizations that need AWS infrastructure in space-constrained on-prem environments. 6/8 - Lambda gets longer execution AWS Lambda Managed Instances now support function timeouts of up to 90 minutes. AWS is also bringing Graviton5-powered instances to improve price-performance for longer-running workloads. This makes Lambda-based architectures more interesting for workloads that previously pushed against execution limits. 7/8 - Builder ID security improvements 🔐 AWS Builder ID is getting stronger account recovery and authentication options. Updates include: • Recovery emails for password resets • MFA support for third-party sign-ins • Improved account recovery Small security improvements can make a big difference when developer identities are involved. 8/8 - Real-time AI video intelligence 🎥 AWS Elemental Inference can now generate contextual metadata from live video in real time. It can identify things like: • Objects • Categories • Brand-suitability signals The interesting part? Teams can add AI-powered video intelligence without building and maintaining their own ML infrastructure. The bigger picture: AWS isn’t just adding new services. The bigger trend is AI + automation + managed infrastructure becoming deeply integrated into everyday engineering workflows. Which of these AWS updates do you think will have the biggest impact on cloud engineers? 👇

🏗️ Terraform becomes powerful when you stop treating it as a CLI tool and start treating infrastructure as software. Use: Git → Review → Plan → Approval → Apply Now infrastructure gets: • Version control • Code review • Auditability • Repeatability • Collaboration The goal isn't just automated infrastructure. It's predictable infrastructure. #Terraform #DevOps