Creating the Cloud of the Future (opens in new tab)
LY Corporation is consolidating Yahoo! JAPAN and LINE’s internal cloud services into Flava, a private cloud for application development. The article outlines how Flava could evolve over the next two to three years through unified developer platforms, stronger yet more usable security, scalable multimedia storage, AI infrastructure, and intelligent cloud management. Its ultimate goal is to make complex infrastructure easier to consume while automating operational work. ## Platform Flavaization - Flava currently focuses on infrastructure, databases, and containers, while other development services are spread across separate internal platforms. - Developers must learn different systems for: - Access control and approvals - Logging, monitoring, metering, and billing - APIs, CLIs, and user interfaces - Multi-region and availability-zone operations - “Flavaization” means offering all development platforms through a consistent cloud experience. - LY expects much of this integration to be completed within the next one to two years. ## Stronger, More Usable Security - Flava incorporates security governance from the architecture and product-planning stages, working with the CISO organization. - Data environments are separated by security level: - Default - Secret - Top secret - Sensitive changes require role-based permissions, organizational reporting, expert review, and formal approval. - The main challenge is usability: - Resources can now be provisioned within minutes, but access may still require around ten workflows, such as VDI and Box account creation, taking up to two months. - VPC ACL controls can add several milliseconds of latency, which may affect latency-sensitive services such as LINE messaging. - Flava must provide “usable security” that preserves strong governance without making development excessively slow or difficult. ## Storage for Growing Multimedia Data - Users continuously generate and retain large volumes of photos, videos, and other multimedia content. - Storage demand can grow even when service traffic remains stable. - Flava needs storage technologies suited to different data lifecycles, balancing: - Cost - Throughput and latency - Searchability - Compression and deduplication - Encryption - Efficient tiered storage will be essential for managing long-lived user data economically. ## AI Operations Platforms - LY is adopting AI tools and agents across its organizations, creating demand for shared AIOps infrastructure. - Potential platform capabilities include: - Approved MCP server development and management - Vector databases - AI observability tools such as Langfuse - AI model management - Because AI systems handle internal data, these platforms must comply with company security and data-processing policies. - Flava aims to rapidly evaluate emerging AI technologies and provide compliant, standardized services across the company. ## Network and Storage Infrastructure for AI - AI workloads process larger datasets while requiring very low network latency and high throughput. - Relevant technologies include: - DPUs - Smart NICs - High-speed NVMe storage - Automated storage tiering - Operating networks and storage at cloud scale introduces major challenges in latency, reliability, fault tolerance, throughput, change management, and security. - Flava’s existing network and storage engineering teams have experience supporting LINE and Yahoo! JAPAN at large scale and will adapt that expertise for AI workloads. ## The Intelligent Cloud - Future users may describe infrastructure requirements in natural language rather than manually configuring resources through consoles, APIs, CLIs, or Terraform. - For example, Flava could translate requirements for image processing, AI-based content labeling, messaging, and tiered storage into an architecture and deployable system. - An intelligent Flava could also: - Generate network diagrams and ACL matrices - Identify vulnerabilities and prioritize remediation - Recommend cost optimizations - Detect underutilized resources - Find unencrypted personal information - Manage OSS vulnerability responses - Chatbots could automate tasks such as identifying low-utilization resources while excluding standby failover servers or proposing cost reductions for them. - Operational campaigns currently requiring substantial engineer participation could increasingly be handled by AI agents. Flava’s recommended direction is to combine a unified cloud experience with practical security, lifecycle-aware storage, AI-ready infrastructure, and natural-language automation. The article argues that building this future cloud requires both deep infrastructure expertise and strong attention to developer and user experience.