Operations | Monitoring | ITSM | DevOps | Cloud

Chaos Engineering is great, but by itself it can create bottlenecks that limit your reliability journey. FULL TRANSCRIPT: One of the things we've learned while building Gremlin and being the first Chaos Engineering tool to market is with all the greatness that comes with this approach, we've learned some of the downfalls, some of the drawbacks. And one of those is how you scale this practice.

With IT evolving and your own plate of responsibilities not getting any lighter, having a team that can problem-solve on their own is essential. Though it can feel challenging to relinquish control, it's important to make sure that your team is able to be autonomous and learn from challenges they may encounter in their day-to-day.

Exciting Q3 Enhancements for iOS, Android, and Windows To view the schedule for upcoming meetings, Click here. Q3 introduces major enhancements across platforms, emphasizing security and admin experience. Key updates feature improved workflows, phishing protection, and better error handling. The Apple ecosystem benefits from advancements in app management and conditional access, while the iOS and Mac roadmap highlights new capabilities. Windows updates focus on EIM configuration and BitLocker key management notifications, ensuring seamless upgrades and a secure environment for users.

Are you struggling to define reliability targets? Teams nowadays are turning to Service Level Objectives (SLOs), reliability targets that can be used to define how much you can play around with your systems before users are affected too much. While they're a great way of defining reliability targets, they are difficult to manage. That's why we built the SLO Center. One place to define, track, zoom into, and stay on top of all your reliability targets and error budgets - so you can be sure when you can experiment, and when it's best to stay safe.

Replays in Sentry are awesome. With one property in your Sentry config you can start capturing video-like replays of user interactions with your application, but the problem is... you still have to watch them... but not anymore! AI replay summaries take your replays and run the events through an LLM to summarize the events that happened in them. They are broken up into chapters, with the breadcrumb sequences embedded in, so you can quickly get context of whats happening in every replay.

Users are mobile. Apps are elastic. Traffic shifts constantly across clouds, ISPs, and geographies. Monitoring needs to adapt to that reality. You need visibility that moves with your users and your applications, wherever they go, however they connect. The Internet is now your application fabric. And your monitoring strategy should reflect that!