InfoQ Homepage Edge Content on InfoQ
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Relational Data at the Edge
Justin Kwan and Vignesh Ravichandran discuss Cloudflare’s edge database architecture, unique challenges and practices for data replication, failover and recovery, and custom performance techniques.
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Living on the Edge: Boosting Your Site's Performance with Edge Computing
Erica Pisani discusses what the edge is, how running code and serving data on the edge can improve site performance, and how to leverage these options to maximize site performance.
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Living on the Edge: Running Code and Serving Data with Edge Services
Erica Pisani discusses what the edge is, how running code and serving data on the edge can improve the performance of services, and how to leverage these tools to maximize performance.
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How to Operationalize Transformer Models on the Edge
Cassie Breviu discusses different model deployment architectures, how to deploy with edge devices and inference in different programming languages.
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GraphQL Caching on the Edge
Max Stoiber discusses why and how to edge cache production GraphQL APIs at scale.
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Building Modern Transportation System with KubeEdge: How We Made It
Kevin Wang and Huan Wei discuss the benefits and challenges of adopting cloud-native technologies, cloud collaborative architecture with KubeEdge inside, and real-world use cases.
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Building Applications from Edge to Cloud
The panelists discuss the benefits and limitations of edge technologies and how to adopt them in existing applications and deployments.
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Machine Learning at the Edge
Katharine Jarmul discusses utilizing new distributed data science and machine learning models, such as federated learning, to learn from data at the edge.
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Architecting for the Edge
The panelists discuss main differences in how one should design and build services when embracing the Edge as part of the system architecture.
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Panel: Living on the Edge
Jose Nino, Rita Kozlov, and Ivan Ivanov discuss when we need to care about edge optimizations, what the development workflow looks like when on the edge, and some of the challenges.
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Machine Learning on Mobile and Edge Devices with TensorFlow Lite
Daniel Situnayake talks about how developers can use TensorFlow Lite to build machine learning applications that run entirely on-device.
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The Internet of Things Might Have Less Internet Than We Thought?
Alasdair Allan looks at the possible implications of machine learning on the edge around privacy and security.
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