Ashok V

IT Professional

[CryptoWala @cryptowalax]

A 20-year-old Delhi techie, Aryan Nishad, has launched https://t.co/rlW7xL7nnF, a platform where citizens can anonymously report bribe demands.

Users can log the amount, location, department and the service involved. These reports build a public database that exposes bribery patterns across government offices in India.

The site even helps people turn their reports into formal complaints for anti-corruption authorities.

The response has been huge, 25 lakh requests in just 10 hours.

Anupam Mittal called it a potential game-changer for governance and accountability.

One simple website is giving common citizens the power to document corruption and make it visible.

Note: These are crowdsourced allegations, not confirmed proof against any official.

#Delhi #Techie #Bribes #Corruption #PublicDatabase #India

[Ashok V @ashokvelpula]

Recap for the newbies

[Ashok V @ashokvelpula]

Finally the #houseofdragon is here all set for the new season.

[Sthitaprajna 🪷 @besthita]

https://t.co/TAj4DSwtCs

[Akhilesh Mishra @livingdevops]

Before you learn Kubernetes, understand why to learn Kubernetes. Or should you?

25 years back, if you wanted to run an application, you bought a $50,000 physical server. You did the cabling. Installed an OS. Configured everything. Then run your app.

Need another app? Buy another $50,000 machine.

Only banks and big companies could afford this. It was expensive and painful.

Then came virtualization. You could take 10 physical servers and split them into 50 or 100 virtual machines. Better, but you still had to buy and maintain all that hardware.

Around 2005, Amazon had a brilliant idea. They had data centers worldwide but weren't using full capacity. So they decided to rent it out.

For startups, this changed everything. Launch without buying a single server. Pay only for what you use. Scale when you grow.

Netflix was one of the first to jump on this.

But this solved only the server problem.
But "How do people build applications?" was still broken.

In the early days, companies built one big application that did everything. Netflix had user accounts, video player, recommendations, and payments all in one codebase.

Simple to build. Easy to deploy. But it didn't scale well.

In 2008, Netflix had a major outage. They realized if they were getting downtime with just US users, how would they scale worldwide?

So they broke their monolith into hundreds of smaller services. User accounts, separate. Video player, separate. Recommendations, separate.

They called it microservices.

Other companies started copying this approach. Even when they didn't really need it.

But microservices created a massive headache. Every service needed different dependencies. Python version 2.7 for one service. Python 3.6 for another. Different libraries. Different configs.

Setting up a new developer's machine took days. Install this database version. That Python version. These specific libraries. Configure environment variables.

And then came the most frustrating phrase in software development: "But it works on my machine."

A developer would test their code locally. Everything worked perfectly. They'd deploy to staging. Boom. Application crashed. Why? Different OS version. Missing dependency. Wrong configuration.

Teams spent hours debugging environment issues instead of building features.

Then Docker came along in 2012.

Google had been using containers for years with their Borg system. But only top Google engineers could use it, too complex for normal developers.

Docker made containers accessible to everyone. Package your app with all dependencies in one container. The exact Python version. The exact libraries. The exact configuration.

Run it on your laptop. Works. Run it on staging. Works. Run it in production. Still works.

No more "works on my machine" problems. No more spending days setting up environments.

By 2014, millions of developers were running Docker containers.

But running one container is easy. Running 10,000 containers? That's a nightmare.

Microservices meant managing 50+ services manually. Services kept crashing with no auto-restart. Scaling was difficult. Services couldn't find each other when IPs changed.

People used custom shell scripts. It was error-prone and painful. Everyone struggled with the same problems. Auto-restart, auto-scaling, service discovery, load balancing.

AWS launched ECS to help. But managing 100+ microservices at scale was still a pain.

This is exactly what Kubernetes solved.

Google saw an opportunity. They were already running millions of containers using Borg. In 2014, they rebuilt it as Kubernetes and open-sourced it.

But here's the smart move. They also launched GKE, a managed service that made running Kubernetes so easy that companies started choosing Google Cloud just for it.

AWS and Azure panicked. They quickly built EKS and AKS. People jumped ship, moving from running k8s clusters on-prem to managed kubernetes on the cloud.

12 years later, Kubernetes runs 90% of production infrastructure. Netflix, Uber, OpenAI, Medium, they all run on it.

Now advanced Kubernetes skills pay big bucks.

Why did Kubernetes win?
Perfect timing.
Docker has made containers popular. Netflix made microservices popular. Millions of people needed a solution to manage these complex microservices at scale.

Kubernetes solved that exact problem.

It handles everything. Deploying services, auto-healing when things crash, auto-scaling based on traffic, service discovery, health monitoring, and load balancing.

Then AI happened. And Kubernetes became even more critical.

AI startups need to run thousands of ML training jobs simultaneously. They need GPU scheduling. They need to scale inference workloads based on demand.

Companies like OpenAI, Hugging Face, and Anthropic run their AI infrastructure on Kubernetes. Training models, running inference APIs, orchestrating AI agents, all on K8s.

The AI boom made Kubernetes essential. Not just for traditional web apps, but for all AI/ML workloads.

Understanding this story is more important than memorizing kubectl commands.

Now go learn Kubernetes already.
Don't take people who write "Kubernetes is dead" articles are just doing it for views/clicks. They might have never used k8s.

[Stocks World @anandchokshi19]

Rule of thumb for investment in fundamentally solid stocks:

1. If price drops 10%, just hold
2. If price drops 20%, add 10%
3. If price drops 30%, add 30%
4. If price drops 40%, add 30%
5. If price drops 50%, add 50%
6. If price goes up 10%, just hold
7. If price goes up 20%, still hold
8. If price goes up 30%, sell 10%
9. If price goes up 40%, sell 20%
10. If price goes up 50%, sell 30%
11. If price goes up 60%, sell 40%
12. If price goes up 100%, sell all

[Ashok V @ashokvelpula]

@DealsDhamaka Congratulations Vineeth

[Ashok V @ashokvelpula]

“The best leaders I’ve worked with don’t have all the answers.
They ask the best questions.”
#tech #leadership

[Ashok V @ashokvelpula]

Prediction: AI Revolution
By 2028, Fortune 500s will have a Chief Agent Officer (CAO).
Deloitte reports 60% of enterprises are already prototyping with agent frameworks.
Agree or disagree?

[Ashok V @ashokvelpula]

@RenaultIndia I own Renault Triber RXZ bought in 2019 please help to elaborate on the E5/10/20 Ethanol mixing of petrol ,is Renault engine compatible with fuel mixture. What is manufacturer liability incase engine is affected?

[Ashok V @ashokvelpula]

Agentic AI isn’t just hype—it’s measurable. Based on a recent Stanford HAI report shows multi-agent frameworks improve task success rates by 37% compared to single-agent LLMs.
The science is clear: Agents scale intelligence.

[Checkmarx @Checkmarx]

Organizations are racing to deploy faster than ever. But AI, multi-cloud, and complex supply chains are widening the security gap.

We asked 1,500 security leaders how they’re adapting, and here’s what they said:

💻 AI writes up to 60% of code in some orgs
⚠️ 81% knowingly ship vulnerable code
🔓 98% suffered a breach in the last year

The Future of Application Security report is here. More than a wake-up call, it’s a playbook for resilience in the AI era. https://t.co/6b8fA7aNX2

[Ashok V @ashokvelpula]

@airtelindia @Airtel_Presence @jagograhakjago @TRAI @jagograhakjago Raosed the concern with Airtel Appellate authority in email for resolution so far no responses.

[Ashok V @ashokvelpula]

Hello @Airtel_Presence @airtelindia @airte i have raised a request for wifi cancellation due to freq disruptions no cuscare is able guide the process or accepting keeps pushing me to wait for resolution I don't need resolution pls help to cancel wifi contn so I can choose others

[Ashok V @ashokvelpula]

@airtelindia @Airtel_Presence @airtelindia @Airtel_Presence what is this resolution as a customer I don’t want to safe custody your equipment why are you pushing this on us…can we not move on if we want to another provider?? @jagograhakjago

[Ashok V @ashokvelpula]

Hey, @grok, who was the most famous person to visit my profile? It doesn't need to be a mutual, don't tag them, just say who it was

[Ashok V @ashokvelpula]

@chiragbarjatya Thank you for the informative breakdown!!

[Ashok V @ashokvelpula]

@flipkartsupport @Flipkart grocery order placed on 1jun its been more than 2 weeks no status of the delivery still shows as yet to deliver. Spoke to multiple cuts care agents none could solve or help place refund such a waste of time talking to customer care. Very upset.