Abstract
Full Stack Observability brings together data from multiple operational domains to provide unified visibility, derive real-time insights and recommend actions to improve application performance, application security and resource optimization. The volume and scale of telemetry data from various domains is extremely large. This can eventually strain the platform and result in processing delays. A filtering mechanism at the data source, such as at the network devices, can help propagate only the crucial model driven telemetry data to the platform. This solution would help address the issue of telemetry data volume by efficiently reducing it at the source.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Sankar, Sudha; Barat, Debashree Jena; Palaniappan, Shivani; N, Pranothi; and Goloubew, Dmitry, "FILTERING MODEL DRIVEN TELEMETRY DATA OF NETWORK DEVICES TO OPTIMIZE FULL STACK OBSERVABILITY", Technical Disclosure Commons, (May 08, 2024)
https://www.tdcommons.org/dpubs_series/6986