Singularity is a container solution designed for scientific computing, enabling reproducible and portable environments. It allows users to create and share complete environments that can be executed on various platforms, ensuring consistency across different systems. Singularity is open-source and integrates seamlessly with existing workflows for both system engineers and researchers. It provides secure means to capture and distribute software and compute environments, making it a game-changing development for computational science. The scientific computing landscape has evolved, with virtualization becoming a global infrastructure necessity. However, traditional virtualization solutions have limitations in terms of performance and portability. Containers, introduced with lightweight virtualization features in the Linux kernel, offer a more efficient alternative. Despite their potential, containers have not been widely adopted in scientific computing due to security concerns and the need for reproducibility. Singularity addresses these challenges by providing a secure, portable, and reproducible container solution. It allows users to create and share environments that can be executed on different systems, ensuring consistency and reliability. Singularity is designed to work with existing HPC resources and integrates seamlessly with resource managers like SLURM. It supports various container formats and provides features such as SHA256 hashing for container validation, ensuring data integrity and compliance with regulatory standards. Singularity also offers user freedom by allowing users to install applications, versions, and dependencies without impacting the system. It supports existing traditional HPC resources and is compatible with a wide range of Linux distributions and hardware. Singularity can run on older systems and supports technologies like InfiniBand and Lustre, making it suitable for a variety of scientific computing environments. Singularity is used in various scenarios, including academic research, server administration, and eliminating redundancy in container technology. It allows researchers to develop and share analyses, ensuring reproducibility and validation of results. Singularity also supports running containers at scale, making it suitable for large-scale scientific computing. Singularity is compatible with standard workflows, pipes, and IO, allowing users to interact with containers and applications in a transparent manner. It supports bootstrapping containers from scratch or from Docker images, providing flexibility in container creation. Singularity also supports shared and mounted volumes, allowing users to access host file systems within containers. Overall, Singularity provides a robust solution for scientific computing, enabling reproducible, portable, and secure environments that can be used across different systems and platforms. It addresses the challenges of traditional virtualization and container solutions, making it a valuable tool for computational science.Singularity is a container solution designed for scientific computing, enabling reproducible and portable environments. It allows users to create and share complete environments that can be executed on various platforms, ensuring consistency across different systems. Singularity is open-source and integrates seamlessly with existing workflows for both system engineers and researchers. It provides secure means to capture and distribute software and compute environments, making it a game-changing development for computational science. The scientific computing landscape has evolved, with virtualization becoming a global infrastructure necessity. However, traditional virtualization solutions have limitations in terms of performance and portability. Containers, introduced with lightweight virtualization features in the Linux kernel, offer a more efficient alternative. Despite their potential, containers have not been widely adopted in scientific computing due to security concerns and the need for reproducibility. Singularity addresses these challenges by providing a secure, portable, and reproducible container solution. It allows users to create and share environments that can be executed on different systems, ensuring consistency and reliability. Singularity is designed to work with existing HPC resources and integrates seamlessly with resource managers like SLURM. It supports various container formats and provides features such as SHA256 hashing for container validation, ensuring data integrity and compliance with regulatory standards. Singularity also offers user freedom by allowing users to install applications, versions, and dependencies without impacting the system. It supports existing traditional HPC resources and is compatible with a wide range of Linux distributions and hardware. Singularity can run on older systems and supports technologies like InfiniBand and Lustre, making it suitable for a variety of scientific computing environments. Singularity is used in various scenarios, including academic research, server administration, and eliminating redundancy in container technology. It allows researchers to develop and share analyses, ensuring reproducibility and validation of results. Singularity also supports running containers at scale, making it suitable for large-scale scientific computing. Singularity is compatible with standard workflows, pipes, and IO, allowing users to interact with containers and applications in a transparent manner. It supports bootstrapping containers from scratch or from Docker images, providing flexibility in container creation. Singularity also supports shared and mounted volumes, allowing users to access host file systems within containers. Overall, Singularity provides a robust solution for scientific computing, enabling reproducible, portable, and secure environments that can be used across different systems and platforms. It addresses the challenges of traditional virtualization and container solutions, making it a valuable tool for computational science.