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How Google Uses Google Cloud Storage

8 engineering articles about Google Cloud Storage from Google's engineering team

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Intermediate
Google Cloud has introduced a high-performance integration that connects Rapid Storage directly to PyTorch via the fsspec interface to eliminate AI training bottlenecks. By utilizing Google’s Colossus architecture and bidirectional gRPC streaming, the solution offers up to 15 TiB/s aggregate throughput and significant reductions in latency. These improvements allow developers to speed up total training time by 23% with zero code changes required beyond updating the storage bucket type.
Trinadh Kotturu, Martin Durant
4 min read
Includes Code
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Intermediate
Google has released version 1.0.0 of the Agent Development Kit (ADK) for Java, introducing powerful new features like Google Maps grounding, built-in URL fetching, and a standardized Agent2Agent protocol for cross-framework collaboration. The update enhances agent control through a new "App" and "Plugin" architecture, which allows for global logging, automated context window management via event compaction, and "Human-in-the-Loop" workflows for action confirmations. Additionally, the release provides robust session and memory services using Google Cloud integrations like Firestore and Vertex AI to manage long-term state and large data artifacts.
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Advanced
The article discusses the limitations of traditional request-response models in AI agent development and proposes a real-time bidirectional streaming architecture as a solution.
Hangfei Lin
7 min read
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Advanced
The article discusses building high-performance data pipelines using Grain, a data loading library for JAX, and ArrayRecord, an efficient file format.
Jiyang Kang, Shivaji Dutta, Ihor Indyk, Felix Chern
10 min read
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Intermediate
The article discusses the introduction of Managed I/O in Google Cloud Dataflow, which simplifies the management of Apache Beam I/O connectors.
Chamikara Jayalath
8 min read
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Advanced
The article discusses the implementation of Gemma 2, a lightweight large language model (LLM) by Google, for processing streaming data with Dataflow.
Reza Rokni, Ravin Kumar
16 min read
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Beginner
Google Compute Engine is an Infrastructure-as-a-Service product that allows users to run Linux Virtual Machines on Google's powerful infrastructure.
Craig McLuckie, Product Manager, Google Compute Engine
4 min read
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Beginner
The article discusses the enhancements made to the Google Prediction API, highlighting its improved speed, ease of use, and accuracy.
Marc Cohen, Developer Relations
2 min read
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