{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/129548"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/129548","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Stateless node rebalancing and stateful building blocks for limitless autoscaling","abstract":"Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2027-05-01","abstract_html":"Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2027-05-01","abstract_has_math":false,"creators":["Varadharajan, Thrivikraman"],"institution":"University of Illinois Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Computer Science","degree_department":null,"school":null,"contributors":["Gupta, Indranil"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2025,"date_issued":"2025-04-20","date_published":"2025-04-20","updated_at":"2026-07-22T22:25:05Z","subjects":["autoscaling microservices","cpu limits","node rebalancing","stateful autoscaling"],"languages":["en","eng"],"rights":["Copyright 2025 Thrivikraman Varadharajan"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/2142/129548","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Gupta, Indranil"]},{"key":"dc:creator","label":"Author","values":["Varadharajan, Thrivikraman"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2025-04-20","2025-05"]},{"key":"dc:type","label":"Dc Type","values":["text","Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Computer Science"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["autoscaling microservices","cpu limits","node rebalancing","stateful autoscaling"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en","eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2025 Thrivikraman Varadharajan"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://hdl.handle.net/2142/129548"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2027-05-01","The student, Thrivikraman Varadharajan, accepted the attached license on 2025-04-19 at 14:53.","The student, Thrivikraman Varadharajan, submitted this Thesis for approval on 2025-04-19 at 15:35.","This Thesis was approved for publication on 2025-04-20 at 16:02.","DSpace SAF Submission Ingestion Package generated from Vireo submission #21847 on 2025-10-19 at 19:15:10","Management of compute resources for cloud-native microservices relies heavily on autoscalers. Most autoscalers are built atop the fundamental mechanism of adjusting CPU limits---restricting the amount of CPU resources a service is allowed to use, and then they innovate scaling policies within those constraints. However, we show that the presence of CPU limits causes resource wastage and complicates autoscaler design. Thus, we advocate for the removal of CPU limits for allocating resources. Our design of Yet Another AutoScaler (YAAS) shows how this \"limitless\" design pathway opens up new challenges and opportunities. The development of YAAS was a collaborative effort, and this thesis focuses on addressing one specific challenge - the increase of CPU utilization beyond the allocation resulting in issues like node congestion and imbalances. To counter this, YAAS intelligently combines node scaling and rebalancing policies to meet SLOs (latency thresholds) with minimal disruptions. Experiments show that YAAS reduces CPU allocations by an average of 28% against limit-less baselines while satisfying SLOs. YAAS is limited to autoscaling stateless services. Although autoscalers for stateful services exist, most are paid solutions that are tailored to specific stateful services and do not provide users with full control. In this context, we present an in-depth study on scaling Redis and Kafka and identify the common building blocks for scaling stateful services."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Stateless node rebalancing and stateful building blocks for limitless autoscaling"]}]}],"canonical_facts":{"dc:contributor":["Gupta, Indranil"],"dc:creator":["Varadharajan, Thrivikraman"],"dc:date":["2025-04-20","2025-05"],"dc:description":["Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2027-05-01","The student, Thrivikraman Varadharajan, accepted the attached license on 2025-04-19 at 14:53.","The student, Thrivikraman Varadharajan, submitted this Thesis for approval on 2025-04-19 at 15:35.","This Thesis was approved for publication on 2025-04-20 at 16:02.","DSpace SAF Submission Ingestion Package generated from Vireo submission #21847 on 2025-10-19 at 19:15:10","Management of compute resources for cloud-native microservices relies heavily on autoscalers. Most autoscalers are built atop the fundamental mechanism of adjusting CPU limits---restricting the amount of CPU resources a service is allowed to use, and then they innovate scaling policies within those constraints. However, we show that the presence of CPU limits causes resource wastage and complicates autoscaler design. Thus, we advocate for the removal of CPU limits for allocating resources. Our design of Yet Another AutoScaler (YAAS) shows how this \"limitless\" design pathway opens up new challenges and opportunities. The development of YAAS was a collaborative effort, and this thesis focuses on addressing one specific challenge - the increase of CPU utilization beyond the allocation resulting in issues like node congestion and imbalances. To counter this, YAAS intelligently combines node scaling and rebalancing policies to meet SLOs (latency thresholds) with minimal disruptions. Experiments show that YAAS reduces CPU allocations by an average of 28% against limit-less baselines while satisfying SLOs. YAAS is limited to autoscaling stateless services. Although autoscalers for stateful services exist, most are paid solutions that are tailored to specific stateful services and do not provide users with full control. In this context, we present an in-depth study on scaling Redis and Kafka and identify the common building blocks for scaling stateful services."],"dc:format":["application/pdf"],"dc:identifier":["https://hdl.handle.net/2142/129548"],"dc:language":["en","eng"],"dc:rights":["Copyright 2025 Thrivikraman Varadharajan"],"dc:subject":["autoscaling microservices","cpu limits","node rebalancing","stateful autoscaling"],"dc:title":["Stateless node rebalancing and stateful building blocks for limitless autoscaling"],"dc:type":["text","Thesis"],"thesis:degree_discipline":["Computer Science"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["M.S."],"thesis:institution_name":["University of Illinois Urbana-Champaign"]},"updated_at":"2026-07-22T22:25:05Z"}