{"schema_version":"1.0","canonical_url":"https://patentable.app/patents/US-11303534","patent":{"patent_number":"US-11303534","title":"Proactively accomodating predicted future serverless workloads using a machine learning prediction model and a feedback control system","assignee":null,"inventors":[],"filing_date":"2019-12-13T00:00:00.000Z","publication_date":"2022-04-12T00:00:00.000Z","cpc_codes":["H04L","G05B","G06N","H04L","H04L","H04L","H04L","H04L"],"num_claims":18,"abstract":"Example implementations relate to a proactive auto-scaling approach. According to an example, a target performance metric for an application running in a serverless framework of a private cloud is received. A machine-learning prediction model is trained to forecast future serverless workloads during a window of time for the application based on historical serverless workload information. The serverless framework is monitored to obtain serverless workload observations for the application. A future serverless workload for the application at a future time is predicted by the trained machine learning prediction model based on workload observations. A feedback control system is then used to output a new number of replicas based on a current value of the performance metric, the target performance metric and the predicted future serverless workload. Finally, the serverless framework is caused to scale and pre-warm a number of replicas supporting the application to the new number."},"analysis":{"summary":null,"layman_explanation":null,"technical_analysis":null,"business_analysis":null,"faqs":null,"topics":[],"tech_cluster":null},"seo":{"title":"Proactively accomodating predicted future serverless workloads using a machine learning prediction model and a feedback control system","description":"Example implementations relate to a proactive auto-scaling approach. According to an example, a target performance metric for an application running in a serverless framework of a private cloud is rec","keywords":[]},"attribution":{"source":"Patentable","source_url":"https://patentable.app","canonical_url":"https://patentable.app/patents/US-11303534","license":"CC-BY-4.0-like","license_terms":"AI-generated analysis on this page (summary, layman_explanation, technical_analysis, business_analysis, faqs) may be reused with attribution and a visible link back to the canonical URL above. Patent abstracts, claims, and bibliographic data are USPTO public domain.","required_link":"https://patentable.app/patents/US-11303534","citation_suggestion":"Patentable. \"Proactively accomodating predicted future serverless workloads using a machine learning prediction model and a feedback control system\" (US-11303534). https://patentable.app/patents/US-11303534","copyright_holder":"Nomic Interactive Technology LLC"},"links":{"html":"https://patentable.app/patents/US-11303534","json":"https://patentable.app/api/llm-context/US-11303534","site":"https://patentable.app","llms_txt":"https://patentable.app/llms.txt"},"generated_at":"2026-05-30T19:15:10.791Z"}