With global data creation predicted to hit 180 zettabytes by 2025, leading data storage provider Seagate needed to introduce greater automation at immense scale to its operations, to ensure it could keep pace with growing demand.
To manage the complexity of manufacturing storage for such colossal amounts of data, and transform and modernize its legacy mission-critical systems across eight factories, Seagate engineered edgeRX from the ground up. Powered by multiple cloud native projects, including Kubernetes and Prometheus, edgeRX established real-time analytics at the edge via inference and machine learning, and leveraged digitalization to enable Seagate to become much more agile and efficient.
“We aim to drive more Artificial Intelligence into our day-to-day factory operations across the globe, and we optimize the performance of existing processes through analytics and AI. This can only be realized through growing capability in data processing in volume, velocity, variety and veracity,” said Hamid Hadavi, Enterprise Architect, Seagate Technology.
Scalability at the Edge
Scalability is a huge challenge for a company as large as Seagate. As it moved to edge computing, scalability became harder still.
“Scalability is one of the big challenges, especially when we incorporate edge and endpoints into account. Our computation paradigm, historically, has always been on core data centers, but the more we move to computation on-edge, the services we build do not necessarily enjoy all the resources that are available on the core,” said Hadavi.
Seagate considered multiple solutions to their scalability challenge, including proprietary software, but chose to develop solutions in-house so that they would own the technology and create capability within Seagate.
“Cloud native computing, in particular the Kubernetes project, is very friendly to the kind of scalability that we need. We are targeting AI computation, not just in the data center, but at the edge and in the endpoint, so Kubernetes became a very attractive proposition for us. As container orchestration in general is being standardized by CNCF, cloud native projects have become the platforms that we gravitate towards,” said Hadavi.
Operational changes driven by edgeRX have fundamentally advanced Seagate operations, improving design quality while speeding time-to-value, which has had a positive impact on customer satisfaction. Seagate has seen a major return on investment, far beyond the initial costs of developing edgeRX. In addition, leveraging cloud native projects has also driven a deeper cultural transformation within Seagate, which has moved to agile ways of working and lean product development.
Learn how Seagate runs real-time analytics at the edge via inference and machine learning, leveraging digitalization to enable greater agility and efficiency across its global factories, in this exclusive case study.