Scalable Cloud Architectures: Sharding Services for High Availability (Published)
Service sharding has emerged as a critical architecture pattern for achieving high availability in modern cloud environments where traditional monolithic systems fail to meet scalability demands. This article presents a comprehensive framework for implementing service sharding across distributed infrastructures, detailing both technical benefits and operational challenges. The distributed nature of sharded architectures enables organizations to contain failures within limited blast radii, significantly enhancing system resilience during infrastructure disruptions. Through the proper implementation of multi-instance deployments across availability zones, metadata routing services, and dynamic provisioning mechanisms, enterprises can achieve substantial improvements in service availability, response times, and resource utilization. The architecture described emphasizes consistent request routing and fault isolation while addressing practical implementation considerations, including staggered deployment strategies, stateful migration techniques, and monitoring approaches. Evidence from industry implementations demonstrates that properly sharded systems can accommodate substantially higher concurrent connection volumes, achieve faster recovery times, and maintain performance during traffic spikes. While acknowledging the increased complexity introduced by sharding, the article provides strategic mitigation approaches through automation, redundancy, and observability solutions. These strategies effectively address challenges related to infrastructure complexity, routing service reliability, data consistency, debugging complexity, and operational overhead, allowing organizations to maximize the benefits of service sharding while minimizing associated complexities.
Keywords: Service sharding, cloud scalability, distributed architecture, fault isolation, high availability, metadata routing
Improving High Availability Services Using KVM Full Virtualization (Published)
In the digital era, critical sectors like banking, ISPs, and cloud-based services depend on robust, secure networks to ensure uninterrupted service availability. Key operations such as financial transactions, customer support, and online services rely on high system uptime, essential for business continuity and customer trust. Network and server administrators play a vital role in maintaining high availability (HA) for systems like file servers, web servers, database servers, backup systems, and enterprise applications. HA infrastructures often use multiple servers working collaboratively to ensure continuous service. If one server fails, another takes over seamlessly, preventing significant disruptions. Virtualization technology enhances HA systems by hosting services on virtual machines (VMs) that can migrate between physical nodes within a cluster. This ensures uninterrupted service even during hardware failures. This paper examines the use of open-source tools for managing HA services, focusing on cost efficiency and system optimization. The Heartbeat program facilitates real-time VM migration across cluster nodes, maintaining service continuity. To improve this process, the Perf+ algorithm is introduced. Perf+ optimizes CPU performance, reduces memory usage, and minimizes downtime by transferring fewer bytes of modified memory pages during migration, reducing CPU and network load. The proposed solution is implemented in an experimental HA system to evaluate the performance of real-time VM migrations. The research analyzes the impact of these migrations on system efficiency, aiming to advance HA infrastructures in virtualized environments through optimized resource utilization and reduced operational interruptions.
Keywords: KVM, full-virtualization, high availability, open source, virtualization