AWS

AWS has expanded its 7th-generation U7i instances to the South America (São Paulo) region, offering the u7in-24tb.224xlarge configuration. These instances feature 24 TiB of DDR5 memory and 896 vCPUs powered by fourth-generation Intel Xeon Scalable processors. With 200 Gbps network bandwidth and 100 Gbps EBS throughput, they are optimized for mission-critical in-memory databases.

• U7in-24tb.224xlarge instances are now available in the SA1 region for local latency-sensitive workloads.
• 24 TiB DDR5 memory and 896 vCPUs support massive in-memory database scales without external sharding.
• ENA Express and 200 Gbps network bandwidth reduce inter-node communication latency for clustered DBs.
• Ideal for SAP HANA, Oracle, and SQL Server deployments requiring high transaction throughput locally.

Amazon EC2 now monitors application-level health alongside system checks, detecting issues like stopped web servers or failed Docker daemons. This feature eliminates the need for custom monitoring scripts to identify when applications stop accepting traffic or misconfigure networking. It extends existing instance reachability alerts to cover specific service failures running on the instance.

• Detects stopped web servers and non-running Docker daemons natively
• Identifies networking misconfigurations or interfaces dropping traffic
• Replaces custom scripts for basic application health monitoring
• Combines app-level alerts with existing EC2 system status checks

Amazon OpenSearch Serverless now allows up to 10,000 collections per collection group, a significant increase from the previous 1,500 limit. This enhancement enables organizations to consolidate more collections under shared OpenSearch Compute Units (OCUs), even when using different AWS KMS keys for encryption. The update supports multi-tenant workloads by reducing costs through shared capacity while maintaining granular security controls.

• High-density consolidation: Support for 10,000 collections per group reduces management overhead.
• Cost efficiency: Share OCU capacity across many collections instead of provisioning per key.
• Security isolation: Different KMS keys are supported within the same shared group.
• Multi-tenant ready: Better suited for workloads requiring many isolated data sets.

Canva replaced database-heavy session revocation with an S3-backed architecture to handle 100 million active sessions. The system stores durable revocation records in S3 and distributes compact, in-memory indexes to application gateways. This shift reduced database infrastructure needs and cut cache memory usage by 87.5% while speeding up deployments.

• S3 serves as durable storage for revocation records, eliminating DB lookup bottlenecks at scale.
• Compact in-memory indexes are pushed to gateways, enabling fast local checks without central DB hits.
• Memory footprint for revocation caches dropped by 87.5%, significantly reducing resource overhead.
• Architecture simplifies deployment cycles and lowers overall database infrastructure requirements.

Amazon SageMaker JumpStart now hosts Black Forest Labs' FLUX.2-small-decoder and Google's gemma-4-12B-it foundation models. The FLUX.2 variant acts as a distilled VAE decoder, offering 1.4x faster image decoding and reduced VRAM usage while maintaining quality. Gemma-4-12B-it provides unified multimodal understanding capabilities for AWS customers.

• FLUX.2-small-decoder is a drop-in replacement for standard FLUX.2 decoders in image generation pipelines.
• Achieves 1.4x speedup and 1.4x lower VRAM consumption with minimal quality loss.
• Performance gains for FLUX.2 are more pronounced at higher image resolutions.
• Gemma-4-12B-it enables unified multimodal understanding on SageMaker JumpStart.
• Both models expand the available foundation model portfolio for AWS infrastructure.

Amazon SageMaker JumpStart now offers three new foundation models: Redis's langcache-embed-v3-small, JetBrains' Mellum2-12B-A2.5B-Thinking, and LightOn's LightOnOCR-2-1B. The embedding model optimizes semantic caching for LLMs by mapping text to dense vectors for efficient query matching. The other two models provide specialized capabilities in code-focused reasoning and end-to-end document OCR, respectively.

• Deploy Redis's langcache-embed-v3-small to reduce redundant LLM calls via semantic caching.
• Use Mellum2-12B-A2.5B-Thinking for specialized code reasoning tasks on SageMaker.
• Integrate LightOnOCR-2-1B for high-performance, end-to-end document OCR workflows.
• New models are immediately available in SageMaker JumpStart for AWS customers.

Amazon SageMaker JumpStart now hosts Z.ai’s GLM-5.2 FP8, NVIDIA’s Nemotron-Nano-12B-v2, and Z.ai’s GLM-OCR models. GLM-5.2 FP8 targets long-horizon agentic workflows with a 1M-token context window for full-cycle software development. The new portfolio expands options for hybrid reasoning and advanced document understanding on AWS infrastructure.

• GLM-5.2 FP8 supports 1M-token context for long-horizon agentic engineering tasks.
• Nemotron-Nano-12B-v2 offers efficient hybrid reasoning capabilities.
• GLM-OCR provides specialized advanced document understanding.
• All three models are deployable via SageMaker JumpStart on AWS.