A blog site on our Real life experiences with various phases of DevOps starting from VCS, Build & Release, CI/CD, Cloud, Monitoring, Containerization.
Running a growing e-commerce platform like Opszilla is thrilling. You’re processing thousands of orders daily across the US and Canada, scaling infrastructure, and expanding into new markets. But amidst all that momentum, something starts to break: your data infrastructure and database performance.
At first, it’s subtle—slower queries, lagging reports, a few scaling hiccups. Then the real issue surfaces: you’re still running on MySQL 5.7, a version nearing its end-of-life in October 2023.
In today’s fast-paced digital landscape, IT operations teams are under immense pressure. The explosion of cloud services, hybrid infrastructures, and ever-growing user demands have made traditional monitoring and management tools insufficient. Enter AIOps Artificial Intelligence for IT Operations a transformative approach that’s reshaping how organizations manage, automate, and optimize their IT environments. Continue reading “Unlocking the Power of AIOps: Transforming IT Operations using Artificial Intelligence.”
Last December, a single DNS misconfiguration at a major streaming platform caused a global outage that cost $23 million in lost revenue and affected 180 million users during the World Cup final. The root cause? Their legacy DNS server couldn’t handle the traffic spike, taking 47 minutes to resolve the issue.
Meanwhile, their competitor running CoreDNS experienced the same traffic surge but stayed online, gaining 2.3 million new subscribers that day.
This isn’t just another “infrastructure matters” story. This is about the invisible foundation of the internet that separates digital empires from digital disasters.
Continue reading “The $23 Million DNS Disaster: Why CoreDNS is the Internet’s New Superhero”
Artificial Intelligence is the engine driving transformation across industries such as healthcare, finance, manufacturing, retail, and public services. As AI systems become more integral to decision-making and operations, the demand for high-quality, diverse, and ethically sourced data has reached unprecedented levels.
Yet, traditional data collection methods are riddled with challenges: privacy concerns, biased datasets, legal compliance, and scalability hurdles. This is where synthetic data comes into the picture, a transformative innovation that is rapidly becoming the backbone of scalable and ethical AI development.
Continue reading “Synthetic Data: The Backbone of Scalable and Ethical AI Development”
Proactive monitoring for reliable cloud systems
In any modern cloud-based architecture, monitoring and alerting play a critical role in maintaining reliability, performance, and security.
It’s not enough to just have logs-you need a way to act on those logs when something goes wrong. That’s where CloudWatch alarms come.
Imagine a situation where your application starts throwing 5xx errors, and you don’t know until a customer reports it. By the time you act, you’ve already lost trust.
Alarms prevent this reactive chaos by enabling proactive monitoring—you get notified the moment an issue surfaces, allowing you to respond before users even notice.
You might miss spikes in 4xx/5xx errors that indicate growing problems.
You’re always proactive instead of reactive.
Your team lacks visibility into critical system behavior.
Diagnosing issues becomes more difficult without early signals.
Due to all the reasons above, that’s why I decided to implement AWS CloudWatch Alarms using Metric Filters—a cost-effective, powerful way to monitor logs and trigger alerts based on specific patterns.
