A blog site on our Real life experiences with various phases of DevOps starting from VCS, Build & Release, CI/CD, Cloud, Monitoring, Containerization.
Continue reading “From Messy Logs to Structured Analytics using AWS S3, Lambda, and Athena”
In today’s mix of local systems and cloud focus, moving tasks to AWS from internal servers or different clouds is key to staying up to date. But without proper tools, shifting them gets messy fast – so AWS MGN steps in to smooth things out. Continue reading “Complete Guide to Server Migration Using AWS Application Migration Service”
IT operations have reached a breaking point. Traditional monitoring tools can’t keep up with the complexity of cloud-native environments, microservices, and continuous delivery pipelines. Incidents are more expensive than ever with downtime costing enterprises between $300,000 and $1M per hour (Gartner).
Yet, AWS customers adopting GenAI-powered AIOps have seen a 60% reduction in mean time to resolution, 95% fewer out-of-hours incidents, and 99.9% availability across critical workloads. Meanwhile, DevOps and SRE teams are drowning in alert storms, spending more time reacting to noise than resolving real issues.
This is where AIOps (Artificial Intelligence for IT Operations) comes in. By combining advanced machine learning with automation, AIOps doesn’t just monitor (it predicts, correlates, and resolves). The promise is clear: faster Mean Time to resolution (MTTR), lower operational costs, and a more reliable digital backbone for the business. Continue reading “AWS AIOps: The Future of Intelligent and Autonomous IT Operations”
October 2025 is still tough in cloud computing, as Amazon Web Services and Microsoft Azure two major cloud providers experience a massive outage, affecting a multimillion userbase, and who knows how many systems worldwide. Not only do these massive outages expose the fickle and brittle nature of the increasingly well-connected global cloud infrastructures, they also reiterate the cloud’s complexity and demand for solid development and infrastructure oversight. In this article, we break down both outage incidents including the timing, the technical cause of the incidents, overview of the service impact, and much-needed lessons for cloud architects and DevOps dots. Continue reading “Complete Case Study On The AWS and Azure Outages Of October 2025”
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.
