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AWS

Sunday, July 26, 2026 · 8 stories, curated & summarized — click any story for the source.

Amazon EKS now supports reverting the control plane to the previous Kubernetes version within seven days of an upgrade. This safety net allows teams to quickly recover from issues caused by problematic updates during in-place cluster upgrades. The feature directly reduces the operational risk associated with version transitions.

  • Control plane rollbacks are supported within a 7-day window post-upgrade.
  • In-place upgrade risks are mitigated by this quick recovery mechanism.
  • Teams can revert to the prior version if the new one causes issues.
  • No need to rebuild clusters from scratch for recent failed upgrades.
Hacker News (100+ points) general

Cloudflare launches new AI traffic routing options for customers

Cloudflare has introduced new capabilities allowing customers to direct AI traffic through its network. These options provide greater control over how AI workloads are handled and routed. The announcement positions Cloudflare to better support the growing demands of AI-driven applications.

  • New traffic routing options specifically target AI workloads
  • Customers gain more control over AI traffic handling
  • Cloudflare aims to support growing AI application demands
CHECKLISTCloudflare AI Routing TakeawaysTarget traffic routing specifically for AI workloadsGain granular control over AI traffic handlingSupport growing demands of AI applications

Airbus has selected Scaleway as its sovereign cloud provider, prioritizing immunity from non-European legislation alongside technical performance. This move complements its existing multi-cloud strategy rather than replacing hyperscalers like AWS. The decision highlights a broader industry trend where sovereignty claims are becoming a decisive factor in vendor selection, extending beyond major providers to smaller US SaaS vendors.

  • Airbus treats legal sovereignty as a scored criterion equal to technical capability in cloud tenders.
  • Selection of Scaleway complements rather than replaces existing AWS multi-cloud architecture.
  • Sovereignty requirements are expanding to include smaller US SaaS vendors, not just hyperscalers.
  • Practitioners must verify that claimed sovereignty controls are enforceable and auditable.
AWS What's New awsdatabase ↺ since 07-24

AWS expands G7e SageMaker inference to Seoul, London, Tokyo

Amazon SageMaker AI inference now supports G7e instances in Asia Pacific (Seoul, Tokyo) and Europe (London). These instances deliver up to 2.3x performance over G6e, featuring up to 8 NVIDIA RTX PRO 6000 Blackwell GPUs and 1,600 Gbps networking. The expansion allows low-latency deployment of medium-to-large language models up to 70B parameters closer to end users.

  • G7e instances reduce inference latency for GenAI workloads in Asia and Europe.
  • Performance is up to 2.3x faster than previous G6e generation instances.
  • Each instance supports up to 768 GB total GPU memory for large models.
  • Enables serving language models up to 70B parameters locally in new regions.
BY THE NUMBERS2.3x Inference Speed Boost2.3xPerformance over G6e instancesNew G7e instances in Seoul, London, Tokyo
AWS What's New awsdatabase ↺ since 07-24

AWS SageMaker AI adds G7 instances with 4.6x inference performance boost

Amazon SageMaker AI now supports G7 instances powered by NVIDIA RTX PRO 4500 Blackwell Server Edition GPUs, delivering up to 4.6x AI inference performance over G6. These instances offer 32 GB GPU memory per card, 5th Generation Tensor Cores, and networking speeds up to 700 Gbps with EFA. The addition of up to 7.6 TB of local NVMe storage allows large models to remain close to compute without over-provisioning.

  • Deploy generative AI models with 4.6x higher inference performance compared to G6 instances.
  • Access 700 Gbps EFA-enabled networking for faster multi-node training and inference.
  • Store large models locally using up to 7.6 TB NVMe SSDs to reduce latency.
  • Avoid model quantization and over-provisioning with 32 GB GPU memory per device.
BY THE NUMBERS4.6x Inference Performance Boost4.6xPerformance over G6 instancesPowered by NVIDIA RTX PRO 4500 GPUs
The Register general ↺ since 07-24

Microsoft fiber maintenance outage takes out 27 Azure California services

A maintenance error involving fiber optics caused an outage in Azure California for nearly five hours. The incident immediately impacted 27 distinct services, highlighting the fragility of physical layer dependencies in cloud infrastructure. This event underscores the risks associated with routine operational changes in critical connectivity paths.

  • Fiber maintenance errors can cause immediate, widespread service disruptions.
  • 27 Azure services were affected during the near-five-hour California outage.
  • Physical layer changes require rigorous validation to prevent cascading failures.
  • Outages often stem from operational mistakes rather than complex software bugs.
AWS What's New awsdatabase ↺ since 07-23

EKS Auto Mode and Karpenter now support EFA and placement groups

Amazon EKS has added support for Elastic Fabric Adapter (EFA) and EC2 placement groups within EKS Auto Mode and Karpenter node pools. This update allows users to optimize distributed training and inference workloads by controlling instance physical distribution and network interface configurations. Administrators can now specify EFA-only or standard ENI settings on EFA-capable instances, offering finer control over VPC IP utilization.

  • EKS Auto Mode and Karpenter now natively support EFA and placement groups.
  • Optimize distributed training and inference workloads with better network control.
  • Configure EFA-only interfaces to conserve VPC IP addresses on EFA instances.
  • Control physical instance distribution across AWS infrastructure for availability.
TRADE-OFFEKS Network Control OptionsStandard ENIUses default network interfacesHigher VPC IP usageStandard connectivityEFA OnlyOptimizes distributed trainingConserves VPC IP addressesControls physical distributionvs
AWS Database Blog awsdatabase ↺ since 07-23

Amazon Timestream for InfluxDB 3 Enterprise adds multi-node scaling

AWS has enabled multi-node scaling for Amazon Timestream for InfluxDB 3 Enterprise, allowing clusters to expand to 15 nodes with distinct roles for ingestion, querying, and compaction. The update provides guidance on choosing between vertical and horizontal scaling strategies to balance stability and cost. This capability lets teams isolate workload components to better match specific demand patterns.

  • Clusters now support up to 15 nodes with dedicated roles for ingestion, query, and compaction.
  • Separating roles allows right-sizing individual components rather than scaling the entire cluster.
  • Guidance is provided for deciding when to scale vertically versus horizontally.
  • Isolating workloads helps optimize both system stability and infrastructure costs.