InfoQ Homepage Performance & Scalability Content on InfoQ
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OpenSearch Cluster Topologies for Cost Saving Autoscaling
Tech lead Amitai Stern shares insights on OpenSearch autoscaling, covering common pitfalls and innovative architectural approaches.
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Lessons Learned in the Financial Market about Performance and Observability in Front-End Projects
Jessica Felix discusses how to navigate the intricate balance between performance and observability, and the challenges of maintaining equilibrium.
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Unveiling the Tech Underpinning FinTech's Revolution
Wojtek Ptak, Andrzej Grzesik discuss how to avoid wasting time, problems of scaling architecture, imposing constraints and restrictions, and practical tips for increasing collaboration and ownership.
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Why a Hedge Fund Built Its Own Database
James Munro discusses ArcticDB and the practicalities of building a performant time-series datastore and why transactions, particularly the Isolation in ACID, is just not worth it.
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Delivering Millions of Notifications within Seconds During the Super Bowl
Zhen Zhou discusses how they built/test an on-demand notification system, what it takes to manage cloud resources/site-reliability at the same time, and how to mitigate reliability issues.
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LIquid: a Large-Scale Relational Graph Database
Scott Meyer discusses LIquid, the graph database built to host LinkedIn, serving a ~15Tb graph at ~2M QPS.
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From Mainframes to Microservices - the Journey of Building and Running Software
Suhail Patel discusses the platforms and software patterns that made microservices popular, and how virtual machines and containers have influenced how software is built and run at scale today.
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Modern Compute Stack for Scaling Large AI/ML/LLM Workloads
Jules Damji discusses which infrastructure should be used for distributed fine-tuning and training, how to scale ML workloads, how to accommodate large models, and how CPUs and GPUs can be utilized.
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Sleeping at Scale - Delivering 10k Timers per Second per Node with Rust, Tokio, Kafka, and Scylla
Lily Mara and Hunter Laine walk through the design of a system, its performance characteristics, and how they scaled it.
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Several Components are Rendering: Client Performance at Slack-Scale
Jenna Zeigen discusses front-end performance issues encountered by Slack as they continue to grow and evolve the desktop app.
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Effective Performance Engineering at Twitter-Scale
Yao Yue recapitulates scaling a project at Twitter while summarizing some key lessons learned about effective performance engineering.
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Scaling Organizations with Platform Engineering
Lesley Cordero focuses on how Platform Engineering can drive sustainability for growing organizations through DevOps principles, centralization, and scalable technical practices.
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