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AWS

Wednesday, September 16, 2026 · 7 stories, curated & summarized — click any story for the source.

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InfoQ generaldevops

Amazon Linux 2027 Preview Enforces SELinux by Default, Breaking Permissive Apps

AWS has launched Amazon Linux 2027 in public preview, upgrading to kernel 7.1 and switching SELinux to enforcing mode as the default. This shift means applications that previously operated under AL2023's permissive policy will likely fail to start or function correctly. The announcement provides no specific dates for general availability or end-of-support for AL2023, nor does it outline an in-place migration strategy.

  • AL2027 defaults to SELinux enforcing, unlike AL2023's permissive stance.
  • Apps relying on permissive policies will break immediately upon migration.
  • Kernel is upgraded to version 7.1 in this new preview release.
  • No GA date, EOL date, or in-place migration path has been announced.
  • Test workloads against AL2027 now to identify SELinux compliance gaps.
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AWS What's New awsdatabase

AWS expands root user sign-in to three US regions for better resiliency

AWS now distributes root user sign-in traffic across US East (N. Virginia), US East (Ohio), and US West (Oregon), reducing single-region dependency. The service automatically routes requests to a healthy region without user intervention. CloudTrail ConsoleLogin events for root users are now logged in the specific Region that processed the authentication request.

  • Root sign-in is now resilient across three US East and West regions.
  • Traffic routing is automatic; no user action is required for sign-in.
  • CloudTrail logs root events in the processing region, not just Virginia.
  • Update monitoring and alerting to cover all three regions for full visibility.
  • This change applies to all AWS accounts and is available immediately.
HOW IT WORKSResilient Root Sign-In1User initiates root login2AWS routes to healthy region3Authentication processed automatically4CloudTrail logs in region
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InfoQ generaldevops

Dropbox: Infrastructure Efficiency Creates AI Headroom

Dropbox leverages a decade of infrastructure optimization to handle surging AI demand without relying solely on new data center capacity. Their strategy focuses on forecasting, fleet utilization, storage density, and hardware lifecycle management. This approach allows them to absorb growth by maximizing existing resources rather than just expanding physical footprint.

  • AI demand is absorbed through efficiency, not just new capacity.
  • Forecasting and fleet utilization are key to managing load.
  • Storage density and hardware lifecycles drive long-term savings.
  • Rack-level power delivery optimization supports higher compute.
  • Decade-long optimization predates current AI boom trends.
Read at source →
The Register general

Cornelis and Delos Data challenge Nvidia NVLink with open AI networking

Intel spin-off Cornelis and startup Delos Data are introducing open alternatives designed to scale AI workloads beyond individual racks. These solutions aim to break the dependency on Nvidia's proprietary NVLink interconnect technology. The move signals growing competition in the high-speed fabric layer essential for large-scale distributed AI training.

  • Cornelis and Delos Data are targeting the rack-scale AI networking gap left by NVLink.
  • Open alternatives could reduce vendor lock-in for hyperscalers building massive clusters.
  • Competition may drive down costs and improve interoperability in AI infrastructure.
  • This shift challenges Nvidia's dominance in the high-performance interconnect market.
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AWS What's New awsdatabase

AWS Adds Detected Anomalies Widget to Billing Dashboards

AWS has introduced a Detected Anomalies widget for Billing and Cost Management Dashboards, unifying cost tracking with anomaly detection. The widget displays the count and total cost impact of anomalies relative to month-to-date spend, while allowing users to drill into root causes and duration. Users can configure the view with 30, 60, or 90-day look-back periods and filter by severity, service, account, and region.

  • Centralize cost, usage, and anomaly data in a single dashboard view.
  • Filter anomalies by service, account, region, and severity for targeted analysis.
  • Review root cause and duration details directly within the widget.
  • Select 30, 60, or 90-day look-back periods to assess trend context.
CHECKLISTOptimize Anomaly DetectionCentralize cost and anomaly data in one viewFilter by service, account, region, and severityReview root cause and duration details directlySelect 30, 60, or 90-day look-back periods
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AWS What's New awsdatabase

AWS Glue zero-ETL now captures archived Salesforce records

AWS Glue zero-ETL integrations for Salesforce have been updated to include archived records in target tables, ensuring a complete data replica for analytics. The isArchived field accurately reflects the status of records, maintaining synchronization between the analytical store and the Salesforce source. This update automatically applies to new integrations and backfills existing ones without requiring manual intervention.

  • Zero-ETL Salesforce jobs now include archived records for complete analytics coverage.
  • The isArchived field tracks status, keeping analytical data in sync with Salesforce.
  • No action required; new integrations capture archived data automatically from creation.
  • AWS Glue automatically backfills archived records for existing integrations.
CHECKLISTZero-ETL Salesforce UpdatesArchived records now included in target tablesisArchived field maintains sync with sourceNew integrations capture data automaticallyExisting jobs backfill archived records automatically
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AWS What's New awsdatabase

AWS Glue zero-ETL adds table ownership and conflict detection

AWS Glue zero-ETL integrations now track which integration owns the properties of a target table, preventing silent collisions between multiple pipelines. This feature enforces isolation by detecting conflicts when different integrations attempt to write to the same destination catalog. Users are guided to either select a new target or update the existing integration, ensuring predictable data landing across S3 Tables and SageMaker Lakehouse.

  • Prevents multiple zero-ETL integrations from silently overwriting the same target table
  • Tracks ownership of table properties to the specific integration that created them
  • Validates conflicts at creation or modification time for S3 Tables and SageMaker Lakehouse
  • Guides users to resolve conflicts by choosing different targets or updating existing configs
  • Ensures data pipelines remain isolated and land exactly where intended
CHECKLISTZero-ETL Conflict PreventionTrack ownership of target table propertiesDetect conflicts during creation or modificationEnsure pipeline isolation for S3 TablesResolve collisions by updating configs or targets
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