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The June 2025 Google Cloud outage, caused by an untested code change that triggered a NullPointerException, crippled over 70 core services worldwide, prompting a rapid technical fix, public apology, and industry‑wide reflections on cloud stability, fault tolerance, and deployment practices.
At Google Cloud Next 25, Google introduced the open‑source Agent2Agent (A2A) protocol—a standardized interaction model for AI agents that breaks system silos, supports major enterprise platforms, follows five design principles, and is already being adopted by dozens of leading companies across various industries.
Google Cloud Next 25 unveiled a wealth of AI advancements, including five new generative models, a groundbreaking Agent‑to‑Agent protocol, upgraded AI‑powered developer tools, expanded AI applications across Workspace, and the high‑performance Ironwood TPU for inference, offering developers a clear view of the latest AI landscape.
Google Cloud mistakenly deleted data and backups for Australian pension fund UniSuper, causing over 600,000 members to lose access for more than a week, and the incident highlights the risks of single‑provider reliance, the importance of robust backup strategies, and the growing relevance of hybrid and multi‑cloud architectures.
This guide explains how to select suitable service‑level indicators (SLIs), define customer‑centric service‑level objectives (SLOs), use error budgets, and iteratively improve reliability for various system types such as services, data processing, and storage, with practical recommendations for Google Cloud environments.
The article explains how ForgeRock’s engineering team improves developer efficiency and product delivery by using Google Cloud’s native DevOps suite—including Cloud Code, Tekton, Cloud Build, and Container Registry—to streamline IDE workflows, enable end‑to‑end automation, and adopt a multi‑cloud strategy across GKE, EKS, and AKS.
An analysis of recent data from Canalys, Synergy Research Group and other sources reveals that the global cloud computing market grew 37.6% to $107.1 billion in 2019, projects continued rapid expansion to $2840 billion by 2024, and compares the performance and strategies of AWS, Azure, Google Cloud and Alibaba Cloud.
This article explains Knative Eventing architecture, demonstrates a Hello World event pipeline using GCP Pub/Sub, and shows how to integrate Cloud Storage events with Google Vision API through Knative services, providing full YAML definitions and command‑line steps.
AutoML and Neural Architecture Search automate deep‑learning model design by using controller networks to explore and evaluate candidate architectures, with efficient variants like PNAS and ENAS reducing cost, while platforms such as Google Cloud AutoML and open‑source AutoKeras make these techniques accessible, promising broader, democratized AI breakthroughs.
This article explains how Google App Engine Datastore works from a programmer's perspective, covering its entity‑based data model, hierarchical structure, query capabilities, comparison with relational databases, and the underlying implementation built on BigTable including entities, indexes, transactions, and backup mechanisms.
The article summarizes Google’s recent papers that outline an architectural guide for creating elastic, scalable web applications on Google Cloud Platform, describing key components such as regions, zones, load balancers, autoscalers, Cloud SQL, Cloud Storage, and deployment best‑practices.