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From manual downloads to automated artifact management.

If you’ve ever used an online banking application to complete a transaction or gone through a checkout on an e-commerce platform, chances are you’ve utilized or interacted with an OTP-protected application. One-Time Password (OTPs) are at the center of most multi-factor authentication (MFA) systems. OTPs are temporary codes delivered by SMS, email, authenticator apps, push notifications, etc.

When MIT released research showing that 95% of enterprise AI pilots fail to deliver measurable business impact, it made headlines for a reason. After years of heavy investment in artificial intelligence, the vast majority of organizations still haven’t moved beyond pilots that promise much but deliver little. This doesn’t mean AI itself is broken. In most cases, the technology performs as intended.

SSL certificates keep websites and apps secure, but in AWS, Azure, and Google Cloud Platform (GCP), misconfigurations or expirations can still cause services to go offline. Why do these failures happen, and how can you prevent them?

When your Python app starts slowing down, maybe queries are taking longer, memory keeps creeping up, or API calls are lagging—basic server metrics won’t tell you why. You need to see what’s happening inside the application itself. That’s the role of Application Performance Monitoring (APM). It gives you a breakdown of database queries, external API calls, memory usage, error rates, and more, so you can connect the dots between code and performance.

Serverless applications are becoming the go-to architecture for modern developers. Startups and enterprises are building serverless applications because they offer scalability, cost-efficiency, and flexibility. However, these advantages come with unique challenges, especially when it comes to monitoring serverless applications. Traditional server monitoring tools fail to capture short-lived functions, making serverless application monitoring essential for maintaining performance and reliability.