🦸‍♀️ Level Up Your Observability Universe: New Powers Unlocked in the LM Envision Platform
Hey LM Community! We’re kicking off the year strong for our first-half launch announcement: LogicMonitor has officially launched a wave of 2025 innovations—and they’re packed with features to help you run smarter workloads, get faster insights, and move closer to autonomous IT operations. 🚀 You can check our formal announcement here, but here’s a quick breakdown of what’s new in this H1 innovation drop: 🔍 Smarter AI Observability AI Workload Monitoring: Expanded support for Amazon Q Business and Nvidia GPUs so you can optimize AI apps with full visibility from a single pane of glass. Hybrid Kubernetes Observability: New support for EKS and AKS gives you deep insights into AI workloads in containerized, cloud-native environments. Cost Optimization Dashboards: Real-time cost data + recommendations help you balance performance and sustainability across compute-intensive workloads. 🧠Edwin AI Gets a Power-Up Up to 90% Alert Noise Reduction: Prioritize what matters, filter out the rest. Faster Root Cause Analysis: Instance-level correlation surfaces the most relevant past incidents to troubleshoot faster. AI-Generated Recommendations: Skip the manual work with suggested fixes. Third-Party Integrations: Works out-of-the-box with PagerDuty, Dynatrace, ConnectWise, and more. 📄 Smarter Logs, Lower Costs Instant Log Access & AI Correlation: No more waiting or writing complex queries. Efficient Storage: Get the insights without blowing the budget. Faster Troubleshooting: Resolve incidents quicker and boost service reliability. 🔴 Coming Up: Product Power Hour – April 24 We’ll have product leaders and trainers onboard to walk through live demos of these updates during our Product Power Hour—don’t miss your chance to see the latest in: The 3 pillars of observability AI innovations in action What’s new with Logs 👉 Register link for Product Power Hour! Got questions or something you’re hoping to see in the demo? Drop them in the thread below 👇
