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Lessons learned from the early performance evaluation of Intel optane DC persistent memory in DBMS., , , , and . DaMoN, page 14:1-14:3. ACM, (2020)MLOS in Action: Bridging the Gap Between Experimentation and Auto-Tuning in the Cloud., , , , , and . Proc. VLDB Endow., 17 (12): 4269-4272 (August 2024)Vertically Autoscaling Monolithic Applications with CaaSPER: Scalable Container-as-a-Service Performance Enhanced Resizing Algorithm for the Cloud., , , , , , , , , and . SIGMOD Conference Companion, page 241-254. ACM, (2024)VASIM: Vertical Autoscaling Simulator Toolkit., , , , , and . ICDE, page 5413-5416. IEEE, (2024)MLOS: An Infrastructure for Automated Software Performance Engineering., , , , , , , , , and 2 other author(s). DEEM@SIGMOD, page 3:1-3:5. ACM, (2020)From WiscKey to Bourbon: A Learned Index for Log-Structured Merge Trees., , , , , , and . OSDI, page 155-171. USENIX Association, (2020)Towards Building Autonomous Data Services on Azure., , , , , , , , , and 28 other author(s). SIGMOD Conference Companion, page 217-224. ACM, (2023)Cloudy with high chance of DBMS: a 10-year prediction for Enterprise-Grade ML., , , , , , , , , and 12 other author(s). CIDR, www.cidrdb.org, (2020)