Elasticity and Auto-Scaling for Cloud-Based Search Services
DOI:
https://doi.org/10.32628/CSEIT251112361Keywords:
Auto-scaling Mechanisms, Distributed Search Systems, Performance Optimization, Cloud Infrastructure, Fault ToleranceAbstract
Modern search services face increasing challenges in managing unpredictable workloads while maintaining optimal performance and cost-effectiveness. The rapid growth in enterprise search queries has necessitated sophisticated auto-scaling mechanisms and elastic infrastructure solutions. This content explores the evolution of search service architecture, focusing on workload characteristics, performance optimization, and implementation strategies. The transformation from traditional static provisioning to intelligent auto-scaling has revolutionized search service capabilities, significantly improving query processing efficiency and system reliability. Advanced scaling patterns have enabled remarkable improvements in resource utilization and cost optimization, while maintaining high availability during peak loads. The implementation of microservice patterns and distributed system architectures has enhanced system resilience and scalability. The integration of machine learning for predictive scaling and anomaly detection has further refined the ability to handle dynamic workloads efficiently. Through real-world case studies of Elasticsearch and Solr Cloud deployments, the practical applications and benefits of these architectural improvements are demonstrated, showcasing the effectiveness of modern search system implementations in addressing contemporary challenges.
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References
Alexandra Mendes, "Top Scalability Patterns for Distributed Systems Guide," 2024. Available: https://www.imaginarycloud.com/blog/scalability-patterns-for-distributed-systems-guide
Maria-Eugenia Iacob, "Quantitative Analysis of Enterprise Architectures," 2006, Available: https://www.researchgate.net/publication/226236887_Quantitative_Analysis_of_Enterprise_Architectures
Confluent, "Building a Scalable Search Architecture," 2019. Available: https://www.confluent.io/blog/building-a-scalable-search-architecture/
Praveen M Dhulavvagol, et al., "Performance Analysis of Distributed Processing System using Shard Selection Techniques on Elasticsearch," 2020. Available: https://www.sciencedirect.com/science/article/pii/S1877050920308395
Karan Shetty, "Predictive autoscaling – enhanced forecasting for cloud workloads," 2022. Available: https://spot.io/blog/predictive-autoscaling-enhanced-forecasting-for-cloud-workloads/
Micah Everett, et al., "Machine Learning-Powered Dynamic Resource Allocation for Sustainable Cloud Infrastructure," 2024. Available: https://www.researchgate.net/publication/384660265_Machine_Learning-Powered_Dynamic_Resource_Allocation_for_Sustainable_Cloud_Infrastructure
Riccardo Pinciroli, et al., "Performance Modeling and Analysis of Design Patterns for Microservice Systems," 2023. Available: https://cs.gssi.it/catia.trubiani/download/2023-ICSA-DesignPatterns-Performance.pdf
Avital trifsik, "Building a Scalable Search Architecture," 2022. Available: https://dev.to/memphis_dev/building-a-scalable-search-architecture-3jj0
GeeksforGeeks, "Advanced Distributed Systems," 2024. Available: https://www.geeksforgeeks.org/advanced-distributed-systems/
Fortinet, "What Is Fault Tolerance?," Available: https://www.fortinet.com/resources/cyberglossary/fault-tolerance
GeeksforGeeks, "Deploying an Elasticsearch Cluster in a Production Environment," 2024. Available: https://www.geeksforgeeks.org/deploying-an-elasticsearch-cluster-in-a-production-environment/
GeeksforGeeks, "Performance Optimization of Distributed System," 2024. Available: https://www.geeksforgeeks.org/performance-optimization-of-distributed-system/
Serge Stephane Aman et al., "Search engine Performance optimization: methods and techniques," 2024. Available: https://f1000research.com/articles/12-1317
David Lomet, "Cost/performance in modern data stores: how data caching systems succeed," 2018. Available: https://dl.acm.org/doi/10.1145/3211922.3211927
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