28 Monitoring & observability Tools Every DevOps Engineer Should Know🚀 Reports show that, Teams with strong observability spot issues way faster and bring downtime down by almost half. Enterprise-level Observability tools use AI and machine learning for, - Anomaly Detection - Predictive Maintenance - Root Cause Analysis - Enhanced Visualization and Insights - Security Monitoring, etc. We have put together a curated list o𝗳 28 tools. 𝗧𝗼𝗼𝗹𝘀 𝗟𝗶𝘀𝘁: https://lnkd.in/eET5XiXt Which tools from this list have you tried? #devops #devopstool
L Walter Renner
5mo
Promethius, Data Dog, New Relic!
Exciting release! MobileLLM-Pro demonstrates that high-performance, long-context LLMs can run efficiently on-device with quantized checkpoints, making open-source AI more accessible. Knowledge distillation and branch-train-merge strategies are clever ways to extend capabilities and robustness without massive data or compute requirements. For teams deploying models like this at scale, observability and evaluation are critical. CoAgent can help monitor on-device LLM behavior, validate outputs, and ensure consistent performance across deployments making it easier to scale innovations like MobileLLM-Pro safely and reliably. Curious how others are handling long-context evaluation and performance monitoring on edge devices.