We conducted a migration to the new server after investigating and organizing the specifications of the existing server, followed by the design, implementation, and testing phases.
We will introduce the implementation of "Linux server replacement/migration." "Server replacement/migration" refers to the process of replacing aging existing servers with new ones or servers that have equivalent functionality. Our company has conducted migration work for servers that are over 10 years old, and the risks of failure due to aging, as well as the difficulty of migrating old systems to new servers, increase with the passage of time. Additionally, if those with knowledge of the servers are no longer present on-site, the project timeline can expand. It is advisable to plan in advance to enable maintenance approximately every five years. [Details] ■ Since most of the documentation from that time is no longer available, we conducted the migration to new servers through phases of investigating and organizing the specifications of the existing servers, followed by design, implementation, and testing. *For more details, please refer to the related links or PDF materials, or feel free to contact us.
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What is the appropriate timing for server replacement/migration? ■ Generally, it is advisable to do it every 5 years. *For more details, please refer to the related links or PDF materials, or feel free to contact us.*
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For more details, please refer to the related links or the PDF materials, or feel free to contact us.
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Founded in 2007, primarily engaged in control system software development. In recent years, we have been involved in cloud development due to current trends. We focus on IoT software development and undertake commissioned development of software for embedded devices directly from major companies. Since 2019, we have also been focusing on improving business efficiency through data utilization and software implementation, supporting our clients in solving their challenges. We address customer issues with a one-stop solution across the following three layers: Edge layer (data collection) Cloud layer (data storage, visualization) Data utilization (guidance for business challenges)