Posts Tagged ‘CloudTransformation’
[AWSReInvent2025] Transforming Tire Innovation: How Apollo Tyres Harnessed AWS High-Performance Computing to Redefine Engineering Velocity
Lecturers
Alex Fronasier serves as Business Development Lead for Product Engineering in North America at Amazon Web Services (AWS), championing cloud-enabled advances across manufacturing domains. Shalender Gupta is Global Head of Data Engineering, Analytics, and Reporting at Apollo Tyres, steering the organization’s worldwide data and digital strategy. Gautam, representing AWS partner expertise, contributed deep insights into bespoke HPC platform customization.
Abstract
In an industry where milliseconds of performance and fractions of material efficiency separate market leaders from followers, simulation-driven design has become the lifeblood of innovation. Apollo Tyres’ bold migration to AWS High-Performance Computing stands as a compelling case study in how purposeful cloud architecture can dramatically accelerate engineering workflows while simultaneously driving down costs. This narrative traces the company’s journey from constrained on-premises systems to a scalable, self-service HPC environment, revealing the strategic decisions, technical foundations, and cultural shifts that unlocked unprecedented gains in speed, agility, and sustainability.
The New Imperatives of Engineering Excellence
Manufacturing no longer unfolds in isolated silos; it now competes in a digital-first arena where speed is existential. Established enterprises face disruptors unencumbered by legacy infrastructure, capable of moving from concept to market at breathtaking pace. Success, therefore, hinges on two intertwined capabilities: modernizing operations through cloud and automation, and compressing product development cycles to shrink time-to-market.
Today’s products are marvels of complexity—millions of lines of code, thousands of components, and sprawling global supply chains. Managing this intricacy demands a digital thread: a continuous, traceable flow of data across the entire lifecycle, from requirements to configuration to multidisciplinary validation. Apollo Tyres illustrated this beautifully with their tire genealogy—a living digital record that links every design decision to its downstream performance implications.
Yet complexity alone does not guarantee advantage. True differentiation emerges when organizations leverage simulation to explore thousands of virtual experiments, uncovering innovations that physical prototyping could never economically reveal. Quality must be engineered in from the outset, augmented by AI, IoT, and advanced analytics, rather than inspected in at the end. Efficiency, meanwhile, is not about cutting corners but about eliminating waste through smarter, data-driven choices.
These forces—digital primacy, digital thread mastery, and simulation at scale—are mutually reinforcing. Cloud-enabled operations feed the thread; the thread supplies rich data for quality optimization; simulation accelerates both. Companies that harmonize all three are positioned to dominate.
AWS lives these principles daily. Designing much of its own hardware while orchestrating a planetary supply chain gives the company intimate familiarity with these challenges. A relentless “working backwards” philosophy—from customer needs to rapid prototyping—infuses everything from data center infrastructure to consumer devices and warehouse robotics. At the heart of this agility lies secure, cloud-native collaboration, enabling globally distributed teams to innovate seamlessly, whether crafting integrated circuits or pioneering satellite constellations.
The Anatomy of Simulation and the Allure of the Cloud
A typical engineering simulation journey begins with conceptual design, evolves into detailed model preparation with boundary conditions, proceeds to systematic exploration of design alternatives, and concludes with job execution, result analysis, and insight extraction. These cycles repeat across phases: early design space mapping builds competitive edge, mid-stage robustness testing exposes failure modes, and pre-manufacturing validation de-risks production.
Organizations are flocking to the cloud for compelling reasons. Unlimited elastic capacity banishes queue times, dramatically lifting engineer productivity. Pay-as-you-go economics paired with on-demand scaling delivers financial flexibility. Global teams collaborate without friction, while built-in resilience ensures business continuity. Cutting-edge hardware becomes instantly accessible without capital outlay, and software licenses achieve far higher utilization—driving superior ROI. Shared infrastructure even advances corporate sustainability goals.
AWS structures its HPC offering around three pillars: an intuitive front-end for job submission, virtual desktops, and high-performance remote visualization; a vast compute layer with purpose-built instances; and sophisticated data management that preserves traceability—the very essence of the digital thread.
The true power lies in workload-to-instance matching. Different simulations—structural, thermal, fluid dynamics—exhibit distinct compute, memory, or accelerator profiles. AWS’s broad portfolio allows each job to run on its optimal instance, yielding dramatic cost-performance gains. Spot instances handle interruptible workloads, on-demand serves mission-critical runs, and savings plans lock in baseline capacity. Emerging AI-driven provisioning promises to automate these decisions entirely, while GPU instances capitalize on solver redesigns that exploit parallel processing.
Apollo Tyres’ Awakening: From Legacy Constraints to Cloud Liberation
Apollo Tyres commands respect across Asia-Pacific and Europe, with premium offerings marketed under the Vredestein banner for luxury and performance vehicles. Operating seven plants and spanning every tire category—from passenger cars to agricultural and off-road—the company faced classic HPC growing pains.
On-premises clusters imposed crushing capital burdens, interminable procurement cycles, and inflexible scaling during demand peaks. Visibility across global sites was fragmented, and manual job orchestration created bottlenecks that delayed critical insights. Tire design, after all, demands exquisitely detailed multiphysics simulation—modeling rubber compounds, structural integrity, heat dissipation, and wear under extreme conditions.
The pivot to AWS began with foundational services: AWS ParallelCluster for orchestration, Amazon DCV for seamless remote workstation access, and FSx for NetApp ONTAP for high-throughput storage. This triad enabled tight integration between simulation suites and design tools, delivering up to 59% faster runtimes and more than 60% cost reduction.
Rigorous benchmarking proved pivotal. Shalender Gupta shared a clear hierarchy: Graviton processors running Amazon Linux offered the lowest cost; if incompatible, shift to x86 AMD, then Intel; reserve Windows only for unavoidable enterprise applications. This disciplined approach shattered myths of cloud expense, revealing optimal configurations that balanced performance and economy.
Tachyon: Placing Power Back in Engineers’ Hands
To eliminate operational friction, Apollo Tyres partnered with AWS to deploy Tachyon—a tailored, cloud-native HPC management platform. Tachyon fundamentally rebalances control: researchers gain self-service autonomy, while administrators retain comprehensive visibility and governance.
Engineers now submit, monitor, and troubleshoot jobs through an elegant interface. They provision workstations on demand from a curated catalog and navigate files effortlessly—no more IT tickets. Administrators enjoy unified observability across clusters, project-level budgeting, and seamless Active Directory integration.
Under the hood, Tachyon runs on Amazon EKS with lightweight nodes, leverages OpenSearch for metadata, uses Lambda for scheduled billing and notifications, and deploys proxy nodes close to compute clusters. Secure private connectivity via Direct Connect or VPN completes the enterprise-grade posture.
Live demonstrations revealed the platform’s finesse: granular job configuration (queues, nodes, tasks per node, memory), instant cost previews before submission, deep utilization telemetry, and direct access to simulation outputs. Workstation sharing and lifecycle monitoring further streamline collaboration.
Tachyon AI elevates the experience further. Physics-informed models accelerate simulations, while an Amazon Bedrock-powered assistant enables natural-language interaction—querying job status, generating scripts, diagnosing failures, or optimizing for cost versus speed.
The results speak volumes: simulation times fell by 60% compared to on-premises, capital expenditure shifted to controlled operational spend, engineers refocused on innovation rather than infrastructure wrangling, and virtual prototyping largely supplanted physical testing.
Wisdom Earned and Horizons Ahead
Key lessons crystallized: exhaustive benchmarking is non-negotiable for cost and performance optimization; design everything for elasticity; monitor relentlessly with budget alerts; automate wherever possible. Planning for multi-cluster scale from day one smoothed subsequent expansion.
Looking forward, Apollo Tyres envisions chemical compound simulation to optimize material performance and longevity, component rationalization to simplify the bill of materials, global rollout across all R&D centers, and AI agents that autonomously run simulations and recommend optimal designs.
By mastering cloud HPC, Apollo Tyres has not merely accelerated workflows—it has redefined what is possible in tire engineering, setting a benchmark for simulation-driven manufacturing in the digital age.