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Industrial environments require generative AI capabilities to detect and resolve operational issues quickly, but deploying AI models reliably in offline or edge scenarios with limited connectivity is challenging.

Organizations need to automatically detect and classify personally identifiable information (PII) at scale across large volumes of data stored in cloud environments without manual inspection.

Extending AWS CloudFormation with custom resources while maintaining resilience and consistency across multiple AWS regions.

Deploying Eclipse Dataspace Components connectors to production on AWS while maintaining isolation, security, and compliance with International Data Space Association standards.

How to implement secure, standardized data sharing across organizational boundaries while maintaining compliance with IDSA standards and the Dataspace Protocol.

Mapfre USA needed to detect insurance fraud in claims more effectively by moving beyond traditional rules-based and manual investigation approaches to leverage machine learning on large volumes of structured and unstructured data.

How to handle 121 million concurrent gRPC connections from mobile devices establishing persistent connections simultaneously during live events without concentrating traffic onto a single origin endpoint.

AWS customers running critical workloads need to prioritize and respond to heterogeneous service health events with varying operational impact.

Storing and managing petabytes of distributed video surveillance data across thousands of locations while meeting growing retention requirements and enabling operational insights extraction.

S&P Global needed to implement a disaster recovery strategy for their Capital IQ platform that could achieve rapid failover to a secondary region while maintaining data consistency for mission-critical financial operations.

Data pipelines suffer from duplicated transformation logic and cascading changes across multiple workflows as they scale from simple scripts to complex systems.

Managing operational stability and resource constraints when scaling a serverless SaaS platform from thousands to over 1 million concurrent Lambda functions.

Organizations struggle to systematically test system resilience and discover dependencies without manual effort, and need to integrate resilience testing into their CI/CD pipelines.

Samsung needed to serve real-time pricing data to high-traffic APIs while aggregating responses from multiple backend sources without building up state in their infrastructure.

Amazon Cognito lacks native search capabilities, making it difficult to build scalable user discovery and search features in applications.

Building Oracle database architectures that minimize recovery time and maximize availability while leveraging cloud infrastructure.

How to design systems that can recover from ransomware and destructive cyberattacks when backups, credentials, and infrastructure components have been compromised.

ALS GeoAnalytics needed to scale machine learning model training and inference for core logging analysis while managing computational costs effectively.

Building a multi-tenant architecture that isolates tenants without requiring separate AWS accounts while maintaining stateful service deployments.

Organizations must determine whether to operate under a single AWS organization or split into multiple organizations based on their operational, security, and scaling requirements.

Deloitte needed to significantly reduce the time required to provision and spin up testing environments for their Kubernetes workloads.

Enable multiple independent organizations to securely exchange Product Carbon Footprint (PCF) data within a shared data space while maintaining data sovereignty and tenant isolation.

Building a scalable multi-tenant configuration service that maintains strict tenant isolation while supporting real-time updates without cache staleness or downtime.

Simplifying the deployment and scheduling of machine learning inference workloads across multiple instances and instance types on Amazon SageMaker HyperPod.

Detecting safety hazards in real-time across hundreds of distributed operational sites using video feeds while maintaining low latency and managing the computational complexity of processing multiple camera streams.

Aigen needed to scale machine learning pipelines across hundreds of distributed edge solar robots while managing data labeling and model training challenges in agricultural robotics.

Generali Malaysia needed to optimize Kubernetes operations on AWS while reducing operational overhead, managing costs, and improving security posture.

Organizations need a streamlined way to protect and recover entire AWS workloads across multiple layers (data, compute, infrastructure, networking, and configuration) in the event of a disaster.

Managing 6,000 AWS accounts for a multi-tenant serverless SaaS platform with only three people created massive operational challenges around automation, observability, and cost management at scale.

Diagnosing and resolving issues in complex Kubernetes clusters is slow and requires expert knowledge, leading to high Mean Time to Recovery (MTTR) and heavy reliance on specialized engineers for root cause analysis.

Santander struggled to manage cloud infrastructure supporting billions of daily transactions across 200+ critical systems, facing complexity and scalability challenges in their banking operations.

Agricultural supply chains (cotton/food) lack end-to-end traceability, making it difficult to verify sustainability claims, track climate impact, and ensure circularity across complex multi-party value chains.

Salesforce's Cluster Autoscaler could not efficiently scale and manage node provisioning across their fleet of 1,000+ EKS clusters, likely suffering from slow scaling decisions, suboptimal bin-packing, and operational complexity at massive scale.

Securing Amazon Elastic VMware Service (EVS) environments requires centralized traffic inspection across multiple VPCs, on-premises data centers, and internet egress points, which is complex to architect and implement.

Organizations operating under European digital sovereignty requirements need resilient failover capabilities, but regulatory constraints on data residency and governance make cross-partition (sovereign-to-commercial cloud) failover architecturally complex.

Organizations migrating to or operating in the cloud encounter hidden and unexpected costs due to suboptimal architectural decisions, resource misconfigurations, and lack of adherence to cloud best practices.