Cloud computing and AI/machine learning (ML) are two powerful technologies that are even more impactful when used together. Cloud computing provides the infrastructure and resources needed to support AI/ML applications; while AI/ML enhances cloud computing by providing intelligent automation and decision-making capabilities.

CloudWatch can be a great start for monitoring your AWS environments, but it has some limitations in terms of granularity, customization, alerting, and integration with third-party tools. In this article, learn all the ways that Kentik can supercharge your AWS performance monitoring.

Using Grafana Cloud to manage and monitor even your most sensitive data from your AWS services just got easier. If your organization’s workloads are hosted in AWS and you are using a Grafana Cloud instance that’s also hosted in AWS, you can now use AWS PrivateLink to establish a secure connection between your virtual private cloud (VPC) network and Grafana Cloud for all your data.

This is the third blog in our series on Kafka, where we continue to explore the nuances of deploying Kafka for scale. In our previous blogs, Essential Metrics for Kafka Performance Monitoring and Auto-Instrumenting OpenTelemetry for Kafka, we laid the foundation for understanding Kafka’s performance and monitoring aspects. Now, as we explore further into the Kafka ecosystem, we’re here to tackle the common challenges that can arise during deployment and scaling.