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    <title>InfoQ - Architecture &amp; Design</title>
    <link>https://www.infoq.com</link>
    <description>InfoQ Architecture &amp; Design feed</description>
    <item>
      <title>Cloudflare Identifies Query Planning Bottleneck in ClickHouse</title>
      <link>https://www.infoq.com/news/2026/06/cloudflare-clickhouse-bottleneck/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Architecture+%26+Design</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/06/cloudflare-clickhouse-bottleneck/en/headerimage/generatedHeaderImage-1779253744444.jpg"/&gt;&lt;p&gt;Cloudflare recently described how a slowdown in its billing pipeline was traced to contention inside the query planning stage of ClickHouse. The team profiled the bottleneck and patched ClickHouse to replace an exclusive lock with a shared lock, drop the per-query copy of the parts list, and improve part filtering.&lt;/p&gt; &lt;i&gt;By Renato Losio&lt;/i&gt;</description>
      <category>Columnar Databases</category>
      <category>Data Partitioning</category>
      <category>Cloudflare</category>
      <category>Database</category>
      <category>ClickHouse</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Architecture &amp; Design</category>
      <category>news</category>
      <pubDate>Sat, 06 Jun 2026 04:55:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/06/cloudflare-clickhouse-bottleneck/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Architecture+%26+Design</guid>
      <dc:creator>Renato Losio</dc:creator>
      <dc:date>2026-06-06T04:55:00Z</dc:date>
      <dc:identifier>/news/2026/06/cloudflare-clickhouse-bottleneck/en</dc:identifier>
    </item>
    <item>
      <title>How OpenAI Built a Secure Windows Sandbox for Codex Agents</title>
      <link>https://www.infoq.com/news/2026/06/codex-windows-sandbox-design/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Architecture+%26+Design</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/06/codex-windows-sandbox-design/en/headerimage/generatedHeaderImage-1780184710031.jpg"/&gt;&lt;p&gt;OpenAI details Codex Windows sandbox architecture, showing how SIDs, ACLs, restricted tokens, and dedicated sandbox accounts enable safe execution of autonomous coding tasks. The design balances isolation with real developer workflows and shows how OS security primitives must be composed for AI agents on local development environments.&lt;/p&gt; &lt;i&gt;By Leela Kumili&lt;/i&gt;</description>
      <category>Identity Management</category>
      <category>IDE</category>
      <category>Access Control</category>
      <category>AI Assisted Coding</category>
      <category>Security</category>
      <category>Integrated Development Environment</category>
      <category>CLI</category>
      <category>Operating Systems</category>
      <category>Design Systems</category>
      <category>Windows</category>
      <category>Agents</category>
      <category>DevOps</category>
      <category>Development</category>
      <category>Architecture &amp; Design</category>
      <category>news</category>
      <pubDate>Fri, 05 Jun 2026 14:37:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/06/codex-windows-sandbox-design/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Architecture+%26+Design</guid>
      <dc:creator>Leela Kumili</dc:creator>
      <dc:date>2026-06-05T14:37:00Z</dc:date>
      <dc:identifier>/news/2026/06/codex-windows-sandbox-design/en</dc:identifier>
    </item>
    <item>
      <title>30+ Updates per Second per Account: Uber Scales Ledger Processing with Batching</title>
      <link>https://www.infoq.com/news/2026/06/uber-payment-batching-system/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Architecture+%26+Design</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/06/uber-payment-batching-system/en/headerimage/generatedHeaderImage-1779570527807.jpg"/&gt;&lt;p&gt;Uber introduced a high-throughput financial ledger processing system designed to handle hot account write contention at scale. Using 250ms batching, Redis coordination, and optimistic atomic updates, the system supports 30+ updates per second per account while preserving consistency and auditability, reducing multi-hour processing pipelines to minutes in its distributed accounting infrastructure.&lt;/p&gt; &lt;i&gt;By Leela Kumili&lt;/i&gt;</description>
      <category>Distributed Systems</category>
      <category>HotSpot</category>
      <category>Low Latency</category>
      <category>Event Driven Architecture</category>
      <category>payment</category>
      <category>Transactions Processing</category>
      <category>Consistency</category>
      <category>Optimization</category>
      <category>Event Stream Processing</category>
      <category>Financial Applications</category>
      <category>Batch Processing</category>
      <category>Performance</category>
      <category>Development</category>
      <category>Architecture &amp; Design</category>
      <category>news</category>
      <pubDate>Thu, 04 Jun 2026 14:02:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/06/uber-payment-batching-system/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Architecture+%26+Design</guid>
      <dc:creator>Leela Kumili</dc:creator>
      <dc:date>2026-06-04T14:02:00Z</dc:date>
      <dc:identifier>/news/2026/06/uber-payment-batching-system/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: Architecting a Centralized Platform for Data Deletion at Netflix</title>
      <link>https://www.infoq.com/presentations/architecting-deletion-system/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Architecture+%26+Design</link>
      <description>&lt;img src="https://res.infoq.com/presentations/architecting-deletion-system/en/mediumimage/medium-1779869686290.jpg"/&gt;&lt;p&gt;The speakers discuss the architectural challenges of executing safe data deletion across distributed datastores. Balancing durability, availability &amp;  correctness, they explain how to orchestrate multi-system deletion propagation without impacting live traffic. They share lessons on controlling tombstone accumulation, building continuous audit loops, and gaining trust with a centralized platform.&lt;/p&gt; &lt;i&gt;By Vidhya Arvind, Shawn Liu&lt;/i&gt;</description>
      <category>Transcripts</category>
      <category>Platform Engineering</category>
      <category>QCon San Francisco 2025</category>
      <category>Data</category>
      <category>Performance &amp; Scalability</category>
      <category>Reliability</category>
      <category>Architecture &amp; Design</category>
      <category>presentation</category>
      <pubDate>Thu, 04 Jun 2026 10:26:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/architecting-deletion-system/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Architecture+%26+Design</guid>
      <dc:creator>Vidhya Arvind, Shawn Liu</dc:creator>
      <dc:date>2026-06-04T10:26:00Z</dc:date>
      <dc:identifier>/presentations/architecting-deletion-system/en</dc:identifier>
    </item>
    <item>
      <title>Article: Architectural Change Cases: A Practical Tool for Evolutionary Architectures</title>
      <link>https://www.infoq.com/articles/architectural-change-cases/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Architecture+%26+Design</link>
      <description>&lt;img src="https://res.infoq.com/articles/architectural-change-cases/en/headerimage/architectural-change-cases-header-1780316814045.jpg"/&gt;&lt;p&gt;Architectural change cases extend architecture decision record (ADR) thinking by evaluating how decisions may evolve over time. Change cases expose hidden assumptions and help teams estimate the reversibility and cost of change.&lt;/p&gt; &lt;i&gt;By Pierre Pureur, Kurt Bittner&lt;/i&gt;</description>
      <category>Transcripts</category>
      <category>Architecture Documentation</category>
      <category>Architecture Evaluation</category>
      <category>Architecture Decision Records</category>
      <category>Evolutionary Architecture</category>
      <category>Development</category>
      <category>Architecture &amp; Design</category>
      <category>article</category>
      <pubDate>Thu, 04 Jun 2026 09:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/articles/architectural-change-cases/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Architecture+%26+Design</guid>
      <dc:creator>Pierre Pureur, Kurt Bittner</dc:creator>
      <dc:date>2026-06-04T09:00:00Z</dc:date>
      <dc:identifier>/articles/architectural-change-cases/en</dc:identifier>
    </item>
    <item>
      <title>AWS Replaces Fat-Tree Data Center Networks with Random Graph Theory, Cutting Routers by 69%</title>
      <link>https://www.infoq.com/news/2026/06/aws-random-graph-data-center/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Architecture+%26+Design</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/06/aws-random-graph-data-center/en/headerimage/generatedHeaderImage-1780475849954.jpg"/&gt;&lt;p&gt;AWS disclosed that Resilient Network Graphs, a flat network architecture based on quasi-random graph theory, is now the default for most new data center builds. The design replaces fat-tree hierarchies with direct ToR-to-ToR mesh connections using passive optical ShuffleBoxes, cutting routers by 69%, boosting throughput by 33%, and reducing network power consumption by 40%.&lt;/p&gt; &lt;i&gt;By Steef-Jan Wiggers&lt;/i&gt;</description>
      <category>Amazon Web Services</category>
      <category>AWS</category>
      <category>Infrastructure</category>
      <category>Deployment / Datacenter</category>
      <category>Cloud</category>
      <category>DevOps</category>
      <category>Development</category>
      <category>Architecture &amp; Design</category>
      <category>news</category>
      <pubDate>Thu, 04 Jun 2026 08:25:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/06/aws-random-graph-data-center/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Architecture+%26+Design</guid>
      <dc:creator>Steef-Jan Wiggers</dc:creator>
      <dc:date>2026-06-04T08:25:00Z</dc:date>
      <dc:identifier>/news/2026/06/aws-random-graph-data-center/en</dc:identifier>
    </item>
    <item>
      <title>Inside Google’s System for Coordinated A/B Testing across its Global Service Fleet</title>
      <link>https://www.infoq.com/news/2026/06/google-fleet-ab-experimentation/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Architecture+%26+Design</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/06/google-fleet-ab-experimentation/en/headerimage/generatedHeaderImage-1779569949510.jpg"/&gt;&lt;p&gt;Google has shared details of its fleet wide large scale A/B experimentation system designed to standardize experiment assignment, exposure logging, and configuration propagation across distributed services. The approach enables consistent measurement across products, reduces experiment conflicts, and improves reliability of data driven decision making at scale.&lt;/p&gt; &lt;i&gt;By Leela Kumili&lt;/i&gt;</description>
      <category>Distributed Systems</category>
      <category>Data-Driven Decision Making Series</category>
      <category>Feature Toggle</category>
      <category>Infrastructure</category>
      <category>Platforms</category>
      <category>Systems Thinking</category>
      <category>Logging</category>
      <category>User Experience</category>
      <category>A/B Testing</category>
      <category>DevOps</category>
      <category>Development</category>
      <category>Architecture &amp; Design</category>
      <category>news</category>
      <pubDate>Wed, 03 Jun 2026 14:54:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/06/google-fleet-ab-experimentation/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Architecture+%26+Design</guid>
      <dc:creator>Leela Kumili</dc:creator>
      <dc:date>2026-06-03T14:54:00Z</dc:date>
      <dc:identifier>/news/2026/06/google-fleet-ab-experimentation/en</dc:identifier>
    </item>
    <item>
      <title>Article: Two Misconfigurations That Caused Spark OOM Failures on Kubernetes</title>
      <link>https://www.infoq.com/articles/spark-oom-kubernetes-misconfigurations/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Architecture+%26+Design</link>
      <description>&lt;img src="https://res.infoq.com/articles/spark-oom-kubernetes-misconfigurations/en/headerimage/spark-oom-kubernetes-misconfigurations-header-1780044756757.jpg"/&gt;&lt;p&gt;After migrating Spark pipelines to Azure Kubernetes Service, two infrastructure settings interacted destructively: spark.kubernetes.local.dirs.tmpfs=true backed shuffle spill with RAM instead of disk, and a hard podAffinity rule forced all executors onto one node. Together, they caused repeated OOM kills invisible to standard diagnostics.&lt;/p&gt; &lt;i&gt;By Pranav Bhasker&lt;/i&gt;</description>
      <category>Apache Spark</category>
      <category>Cloud</category>
      <category>Kubernetes</category>
      <category>DevOps</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Development</category>
      <category>Architecture &amp; Design</category>
      <category>article</category>
      <pubDate>Wed, 03 Jun 2026 09:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/articles/spark-oom-kubernetes-misconfigurations/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Architecture+%26+Design</guid>
      <dc:creator>Pranav Bhasker</dc:creator>
      <dc:date>2026-06-03T09:00:00Z</dc:date>
      <dc:identifier>/articles/spark-oom-kubernetes-misconfigurations/en</dc:identifier>
    </item>
    <item>
      <title>Java News Roundup: OpenJDK JEPs, Hazelcast, Quarkus, Hibernate, Koog, JHipster, Introducing Endive</title>
      <link>https://www.infoq.com/news/2026/06/java-news-roundup-may25-2026/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Architecture+%26+Design</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/06/java-news-roundup-may25-2026/en/headerimage/java-news-roundup-image-1780348608154.jpg"/&gt;&lt;p&gt;This week's Java roundup for May 25th, 2026, features news highlighting: lifecycle changes with two of the JEPs that were targeted for JDK 27; the GA release of Koog 1.0; point releases of Hazelcast, Quarkus, Hibernate and JHipster; the eighth milestone release of Spring AI 2.0; and introducing Endive, a JVM-native WebAssembly (Wasm) runtime.&lt;/p&gt; &lt;i&gt;By Michael Redlich&lt;/i&gt;</description>
      <category>Endive</category>
      <category>Koog</category>
      <category>Open JDK</category>
      <category>Hibernate ORM</category>
      <category>JDK 27</category>
      <category>Hazelcast</category>
      <category>Spring AI</category>
      <category>Quarkus</category>
      <category>JHipster</category>
      <category>Java</category>
      <category>Development</category>
      <category>Architecture &amp; Design</category>
      <category>news</category>
      <pubDate>Mon, 01 Jun 2026 21:30:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/06/java-news-roundup-may25-2026/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Architecture+%26+Design</guid>
      <dc:creator>Michael Redlich</dc:creator>
      <dc:date>2026-06-01T21:30:00Z</dc:date>
      <dc:identifier>/news/2026/06/java-news-roundup-may25-2026/en</dc:identifier>
    </item>
    <item>
      <title>Shopify Reports 15X Faster Graphql Execution with Breadth First Engine</title>
      <link>https://www.infoq.com/news/2026/06/shopify-graphql-cardinal-bfs/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Architecture+%26+Design</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/06/shopify-graphql-cardinal-bfs/en/headerimage/generatedHeaderImage-1779561076024.jpg"/&gt;&lt;p&gt;Shopify introduced GraphQL Cardinal, a new execution engine replacing depth-first traversal with breadth-first execution. The redesign improves large-scale GraphQL performance with up to 15x faster field execution, 6x lower GC overhead, and +4s P50 latency gains. It focuses on execution-layer efficiency and batched resolver processing for high-cardinality commerce queries.&lt;/p&gt; &lt;i&gt;By Leela Kumili&lt;/i&gt;</description>
      <category>Distributed Systems</category>
      <category>GraphQL</category>
      <category>API</category>
      <category>Low Latency</category>
      <category>Platform Engineering</category>
      <category>Optimization</category>
      <category>Search</category>
      <category>Performance</category>
      <category>Microservices</category>
      <category>Development</category>
      <category>Architecture &amp; Design</category>
      <category>news</category>
      <pubDate>Mon, 01 Jun 2026 14:25:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/06/shopify-graphql-cardinal-bfs/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Architecture+%26+Design</guid>
      <dc:creator>Leela Kumili</dc:creator>
      <dc:date>2026-06-01T14:25:00Z</dc:date>
      <dc:identifier>/news/2026/06/shopify-graphql-cardinal-bfs/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: Theme Systems at Scale: How To Build Highly Customizable Software</title>
      <link>https://www.infoq.com/presentations/liquid-theme-system-dsl/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Architecture+%26+Design</link>
      <description>&lt;img src="https://res.infoq.com/presentations/liquid-theme-system-dsl/en/mediumimage/medium-1779863262373.jpg"/&gt;&lt;p&gt;Shopify Staff Engineer Guilherme Carreiro discusses building and scaling highly customizable platforms. Using Shopify’s Liquid theme system as a case study, he explains how to balance extreme design flexibility with low-latency performance under massive traffic. He shares insights on implementing secure domain-specific languages, native code extensions, and resilient developer tooling.&lt;/p&gt; &lt;i&gt;By Guilherme Carreiro&lt;/i&gt;</description>
      <category>Transcripts</category>
      <category>Case Study</category>
      <category>InfoQ Dev Summit Munich 2025</category>
      <category>Domain Specific Languages</category>
      <category>Architecture &amp; Design</category>
      <category>presentation</category>
      <pubDate>Mon, 01 Jun 2026 11:30:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/liquid-theme-system-dsl/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Architecture+%26+Design</guid>
      <dc:creator>Guilherme Carreiro</dc:creator>
      <dc:date>2026-06-01T11:30:00Z</dc:date>
      <dc:identifier>/presentations/liquid-theme-system-dsl/en</dc:identifier>
    </item>
    <item>
      <title>Podcast: Requirements Analysis for Architects: A Conversation with Sonya Natanzon</title>
      <link>https://www.infoq.com/podcasts/requirements-analysis-architects/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Architecture+%26+Design</link>
      <description>&lt;img src="https://res.infoq.com/podcasts/requirements-analysis-architects/en/smallimage/the-infoq-podcast-logo-thumbnail-1777539225222.jpg"/&gt;&lt;p&gt;Michael Stiefel spoke to Sonya Natanzon, about the intersection of technical and social aspects of software architecture. Understanding the business and how a company operates is more important than the specific technologies used. Effective requirements analysis requires focusing on problems to be solved that describe good and bad outcomes, rather than statements of need or solution statements.&lt;/p&gt; &lt;i&gt;By Sonya Natanzon&lt;/i&gt;</description>
      <category>Architecture</category>
      <category>Requirements</category>
      <category>Artificial Intelligence</category>
      <category>AI Architecture</category>
      <category>The InfoQ Podcast</category>
      <category>Enterprise Architecture</category>
      <category>Domain Driven Design</category>
      <category>Architecture &amp; Design</category>
      <category>podcast</category>
      <pubDate>Mon, 01 Jun 2026 11:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/podcasts/requirements-analysis-architects/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Architecture+%26+Design</guid>
      <dc:creator>Sonya Natanzon</dc:creator>
      <dc:date>2026-06-01T11:00:00Z</dc:date>
      <dc:identifier>/podcasts/requirements-analysis-architects/en</dc:identifier>
    </item>
    <item>
      <title>A Trailing Slash Bypassed AWS API Gateway Authorization</title>
      <link>https://www.infoq.com/news/2026/06/aws-api-gateway-auth-bypass/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Architecture+%26+Design</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/06/aws-api-gateway-auth-bypass/en/headerimage/generatedHeaderImage-1779890404425.jpg"/&gt;&lt;p&gt;A security researcher found that adding a trailing slash to AWS HTTP API paths bypassed Lambda authorizer authentication entirely, enabling unauthenticated wire transfers at a fintech. The root cause is a path normalization mismatch between HTTP API's greedy route matching and its authorization layer. The same vulnerability class appeared in gRPC-Go via CVE-2026-33186.&lt;/p&gt; &lt;i&gt;By Steef-Jan Wiggers&lt;/i&gt;</description>
      <category>AWS</category>
      <category>API Gateway</category>
      <category>Application Security</category>
      <category>AWS Lambda</category>
      <category>Cloud</category>
      <category>Security Vulnerabilities</category>
      <category>DevOps</category>
      <category>Development</category>
      <category>Architecture &amp; Design</category>
      <category>news</category>
      <pubDate>Mon, 01 Jun 2026 09:55:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/06/aws-api-gateway-auth-bypass/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Architecture+%26+Design</guid>
      <dc:creator>Steef-Jan Wiggers</dc:creator>
      <dc:date>2026-06-01T09:55:00Z</dc:date>
      <dc:identifier>/news/2026/06/aws-api-gateway-auth-bypass/en</dc:identifier>
    </item>
    <item>
      <title>Google Cloud Suspends Railway's Production Account, Causing Eight-Hour Platform-Wide Outage</title>
      <link>https://www.infoq.com/news/2026/05/railway-gcp-account-outage/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Architecture+%26+Design</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/05/railway-gcp-account-outage/en/headerimage/generatedHeaderImage-1779878225205.jpg"/&gt;&lt;p&gt;Google Cloud's automated systems suspended Railway's production account without notice, triggering an eight-hour platform-wide outage affecting 3 million users. The cascade took down workloads across all providers including AWS and bare metal because Railway's control plane was hosted on GCP. Railway is demoting GCP to backup-only status.&lt;/p&gt; &lt;i&gt;By Steef-Jan Wiggers&lt;/i&gt;</description>
      <category>Cloud Architecture</category>
      <category>Google</category>
      <category>Google Cloud</category>
      <category>Google Cloud Platform</category>
      <category>Cloud</category>
      <category>Site Reliability Engineering</category>
      <category>DevOps</category>
      <category>Development</category>
      <category>Architecture &amp; Design</category>
      <category>news</category>
      <pubDate>Sat, 30 May 2026 10:03:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/05/railway-gcp-account-outage/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Architecture+%26+Design</guid>
      <dc:creator>Steef-Jan Wiggers</dc:creator>
      <dc:date>2026-05-30T10:03:00Z</dc:date>
      <dc:identifier>/news/2026/05/railway-gcp-account-outage/en</dc:identifier>
    </item>
    <item>
      <title>How Meta Rebuilt Data Ingestion for Petabyte-Scale Reliability</title>
      <link>https://www.infoq.com/news/2026/05/meta-cdc-migration/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Architecture+%26+Design</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/05/meta-cdc-migration/en/headerimage/generatedHeaderImage-1779134681732.jpg"/&gt;&lt;p&gt;The engineering team at Meta recently outlined how the company migrated a data ingestion platform that transfers several petabytes of MySQL social graph data daily to improve reliability and operational efficiency. The team used techniques like reverse shadowing and continuous checksum monitoring to ensure zero downtime during the transition.&lt;/p&gt; &lt;i&gt;By Renato Losio&lt;/i&gt;</description>
      <category>Facebook</category>
      <category>Big Data Infrastructure</category>
      <category>MySQL</category>
      <category>migration</category>
      <category>Scalability</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Architecture &amp; Design</category>
      <category>news</category>
      <pubDate>Sat, 30 May 2026 06:01:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/05/meta-cdc-migration/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Architecture+%26+Design</guid>
      <dc:creator>Renato Losio</dc:creator>
      <dc:date>2026-05-30T06:01:00Z</dc:date>
      <dc:identifier>/news/2026/05/meta-cdc-migration/en</dc:identifier>
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