Operations | Monitoring | ITSM | DevOps | Cloud

Pragya Jazwal, Platform Engineering Lead at Paxos, compared standing up an internal developer portal to buying a gym membership during her talk at IDPCON 2025. Purchasing the software is one thing, but convincing a team of busy engineers to change their daily habits is a much bigger monster to tame. Pragya says the platform team at Paxos learned this lesson the hard way.

Security teams are increasingly turning to Amazon Security Lake to consolidate security telemetry across cloud, network, and on-prem environments. Security Lake provides a unified, OCSF-based data repository that powers analytics, threat hunting, and machine learning across AWS services and third-party tools. But to take advantage of Security Lake’s capabilities, organizations must deliver clean, normalized, OCSF-compliant data, and this is where challenges arise.

We just released the Sentry SDK for Unity 4.0.0 , our biggest update yet. This major release brings comprehensive gaming console support, structured logging, user feedback capabilities, and significant improvements to help you build better games across all platforms. Here's what's new.

Have you ever asked yourself, what is the fastest way to turn a harmless Infrastructure as Code change into a production incident and an awkward postmortem? We did, and found that usually, it's from letting it through without any guardrails. Infrastructure guardrails in Infrastructure as Code (IaC) were once a nice-to-have. Today, they’re essential. Without clear boundaries and safety mechanisms, even well-designed IaC workflows can turn small mistakes into fast-moving, high-impact problems.

There’s a moment every engineer knows. An AI suggests a fix, it looks reasonable,maybe even obvious, but production is on the line and you hesitate before clicking execute. There’s a big difference between an AI that can recommend an action and one you’re willing to let take that action. All it takes is one bad call, one kubectl command that makes things worse, and suddenly every automated suggestion is a potential liability instead of a help.

Why strong reviews, accountability, and monitoring matter more in an AI-assisted world Artificial intelligence has become the latest fault line in software development. For some teams, it’s an obvious productivity multiplier. For others, it’s viewed with suspicion. A source of low-quality code, unreviewable pull requests, and latent production risk. One concern we hear frequently goes something like this: It’s an understandable fear; and also the wrong conclusion.