Optimize AWS resource performance and availability through proactive monitoring, issue resolution, and data-driven insights, enabling smooth, efficient, and secure cloud operations.
Reduce mean time to resolution (MTTR) by surfacing data to quickly diagnose the root cause of issues.
Unify end-to-end observability and analytics across containers and serverless services, eliminating tedious tagging and event correlation across services.
Monitor and troubleshoot containers and serverless workloads for enhanced resilience and efficiency. For example, you can leverage AI and ML- powered capabilities in CloudWatch to query logs and metrics using natural language, analyze patterns and detect anomalies, and automatically mask sensitive data in your CloudWatch logs.
Effectively monitor and optimize the performance of your generative AI applications by leveraging the power of Amazon Bedrock and Amazon CloudWatch. You can use CloudWatch Container Insights to automatically discover and monitor key health metrics for NVIDIA GPUs in your Amazon EKS clusters, providing visibility into resource utilization, availability, and latency. Analyze CPU, memory, GPU, and network metrics to optimize for efficiency and identify potential bottlenecks or anomalies early on.
You can gain deep insights into the performance of your serverless applications by monitoring key operational metrics such as execution duration, errors, and throttles using CloudWatch dashboards and alarms. Additionally, you can use CloudWatch Logs Insights to analyze log data and distributed tracing to identify potential bottlenecks. Leveraging these CloudWatch features allows you to optimize your serverless architectures for cost and efficiency.
CloudWatch Container Insights provides comprehensive health and performance metrics for AWS Fargate, Amazon ECS, and Amazon EKS, including cluster, node, service, and container-level data. You can also integrate EKS control plane and KubeState metrics to analyze and identify root cause of issues.