ProphetStor’s Federator.ai leverages multi-layer operational data, including the metrics from applications, Kubernetes, cloud service providers, and underlying infrastructure that Datadog collects. The data is adapted, and then processed by the ProphetStor’s patented and Deep Learning based Data Correlation and Impact Prediction Engine (DCIE) to create intelligent operation plans. When used for Kubernetes platforms, the Federator.ai creates Application-aware, Just-in-Time, and Fitted resource allocation operational plans for Kubernetes Pod Autoscaling. Additionally, Federator.ai enables workload prediction optimization of application and cloud service usage, making it easier and more efficient to deploy containerized applications.
Datadog’s monitoring and security platform helps users collect and analyze infrastructure metrics, distributed traces, and logs, so teams can scale their environments with confidence. Datadog also makes it easy to monitor applications running on Kubernetes with solutions such as Datadog Agent, and Cluster Agent. Furthermore, Datadog published a free open-source software called Watermark Pod Autoscaler (WPA) to extend the features of the HPA, and give users more control over autoscaling their clusters.
With the integration of the Federator.ai and Datadog’s autoscaling solution, ProphetStor brings proactive resource management to the Kubernetes platforms without changing the application/service/cloud agents of Datadog. The integrated solution combines the advantages offered by both products, enables application-aware acceleration with much-improved utilization and operation automation for the existing users, all without the need to change the code or operation of the application. Performance enhancement of up to 90% reduction in latency is achievable in some applications such as Kafka.
“Containers and orchestration are becoming a standard practice for organizations seeking to operate efficiently. However, as workloads become more dynamic and complex, effective resource management can become unwieldy,” said Ilan Rabinovitch, VP of Product and Community, Datadog. “ProphetStor has combined Federator.ai’s machine learning capabilities with Datadog’s full stack monitoring data to simplify management of Kubernetes at scale.”
“ProphetStor is delighted to work together with Datadog for the integration of Federator.ai with Datadog’s autoscaling solution. Datadog has a monitoring and security platform that covers the full stack, from application to cloud services. Federator.ai offers AI-based application-awareness, multi-layer correlation, and causality analysis that complements the Datadog solution to address the challenges of the scaling and orchestration in container workloads managed by Kubernetes platforms. With additional actionable insights through Federator.ai, our customers can enjoy smoother operation and higher efficiency that are essential in the cloud and 5G services,” added Eric Chen, CEO of ProphetStor Data Services, Inc.