Apache Superset

49 reviews

Apache Superset is an open-source data exploration and visualization platform designed to handle data at scale. It enables users to create interactive dashboards and perform complex data analyses with ease. Superset supports a wide range of data sources and integrates seamlessly with various databases, making it a versatile tool for data professionals. Key Features and Functionality: - Interactive Dashboards: Build and customize dashboards with a variety of visualization options to represent data effectively. - SQL IDE: Utilize a rich SQL editor with syntax highlighting and autocomplete features for efficient query writing. - Extensive Database Support: Connect to numerous databases, including relational and non-relational systems, through a robust connector framework. - Security and Authentication: Implement granular access control and integrate with various authentication backends to ensure data security. - Scalability: Designed to scale out to large, distributed environments, accommodating the needs of growing organizations. Primary Value and User Solutions: Apache Superset empowers organizations to make data-driven decisions by providing an intuitive platform for data visualization and exploration. It addresses the need for a scalable and flexible tool that can integrate with diverse data sources, allowing users to derive insights without extensive technical expertise. By offering a user-friendly interface and powerful features, Superset enhances productivity and facilitates a deeper understanding of complex datasets.

RStudio Kubernetes Container Solution

10 reviews

The RStudio Kubernetes Container Solution is a comprehensive, containerized environment designed to deploy RStudio Server and Shiny applications on Kubernetes platforms. This solution leverages the scalability and flexibility of Kubernetes to provide data scientists and developers with a robust infrastructure for R-based data analysis and interactive web applications. Key Features and Functionality: - Containerized Deployment: Facilitates the deployment of RStudio Server and Shiny applications within Docker containers, ensuring consistency and portability across different environments. - Kubernetes Integration: Utilizes Kubernetes for orchestration, enabling efficient management of containerized applications, including automated scaling, load balancing, and self-healing capabilities. - Scalability: Supports horizontal scaling of Shiny applications to handle varying user loads, ensuring optimal performance during peak usage times. - Persistent Storage: Integrates with storage solutions like Amazon Elastic File System (EFS to provide persistent storage for RStudio and Shiny applications, ensuring data durability and availability. - Security: Incorporates security best practices, including the use of AWS Web Application Firewall (WAF and AWS Certificate Manager for secure access and data protection. Primary Value and User Solutions: The RStudio Kubernetes Container Solution addresses the challenges of deploying and managing R-based applications by providing a scalable, secure, and highly available environment. By leveraging Kubernetes and containerization, it reduces infrastructure management overhead, allowing data scientists and developers to focus on building and deploying analytical models and interactive applications. This solution ensures that RStudio and Shiny applications can efficiently handle varying workloads, maintain high availability, and adhere to security best practices, thereby accelerating the development and deployment of data-driven solutions.

MySQL Container Solution

1 review

The MySQL Container Solution is a pre-configured, ready-to-deploy containerized version of the MySQL database, designed for seamless integration into cloud environments. This solution offers a fast, reliable, and scalable open-source relational database system, ideal for mission-critical, heavy-load production applications. By leveraging containerization, it simplifies deployment and management, ensuring consistency across various environments. Key Features and Functionality: - Up-to-Date and Secure: The container is regularly updated to include the latest MySQL versions and security patches, ensuring optimal performance and protection against vulnerabilities. - Kubernetes Compatibility: Designed to run seamlessly on Kubernetes, it facilitates easy deployment and scaling within container orchestration platforms. - Multiple Storage Engine Support: MySQL supports various storage engines, allowing users to select the most effective one for each table in their application. - Language-Specific APIs: It offers libraries for multiple programming languages, enabling developers to access MySQL databases using language-specific APIs. Primary Value and Problem Solved: The MySQL Container Solution addresses the complexities associated with deploying and managing relational databases in cloud environments. By providing a containerized version of MySQL, it ensures consistency, scalability, and ease of management across development, testing, and production stages. This solution is particularly beneficial for organizations seeking to streamline their database operations, reduce deployment times, and maintain high availability and performance in their applications.

Prometheus Container Monitoring Solution

1 review

Prometheus works well for recording any purely numeric time series. It fits both machine-centric monitoring as well as monitoring of highly dynamic service-oriented architectures. In a world of microservices, its support for multi-dimensional data collection and querying is a particular strength. Prometheus is designed for reliability, to be the system to go during an outage to allow for quickly diagnose problems. Each Prometheus server is standalone, not depending on network storage or other remote services. One can rely on it when other parts of infrastructure are broken, and do not need to setup extensive infrastructure to use it.

PyTorch Deep Learning Kubernetes Container Solution

0 reviews

The PyTorch Deep Learning Kubernetes Container Solution is a pre-configured container image designed to streamline the deployment of PyTorch-based deep learning models on Kubernetes platforms such as Amazon Elastic Kubernetes Service (EKS. This solution provides a consistent and optimized environment for both training and inference tasks, enabling developers and data scientists to efficiently manage and scale their machine learning workloads. Key Features and Functionality: - Pre-configured Environment: The container includes all necessary dependencies, such as NVIDIA CUDA, cuDNN, and Intel MKL, ensuring compatibility and optimal performance for deep learning tasks. - Support for Multiple Versions: Regular updates incorporate the latest versions of PyTorch, with support for CUDA 12.4 on Ubuntu 22.04, providing access to new features and performance improvements. - Compatibility with AWS Services: The solution is tested and optimized for deployment on AWS services, including EC2, ECS, and EKS, facilitating seamless integration into existing AWS infrastructures. - Security and Compliance: All software components are scanned for security vulnerabilities and updated in accordance with AWS security best practices, ensuring a secure environment for model deployment. Primary Value and Problem Solved: This container solution addresses the challenges associated with setting up and managing deep learning environments by providing a ready-to-use, optimized platform for PyTorch applications. It simplifies the deployment process, reduces setup time, and ensures consistency across different stages of model development and deployment. By leveraging this solution, users can focus more on developing and refining their models rather than dealing with the complexities of environment configuration and management.

GoCD Kubernetes Container Solution

0 reviews

GoCD gives you the flexibility to effectively represent CD pipelines that suit organization's processes. Kubernetes gives you a highly programmable delivery infrastructure platform. And together, they provide the foundation for a powerful Continuous Delivery platform.GoCD aims to support the most common CD scenarios out of the box without any plugin installation. GoCD's test reporting will tell you in exactly which changeset and on which platform a test started breaking, which comes in extremely handy when fixing a complex broken build.

Yobitel Cloud-Native Stacks

0 reviews

Drupal Kubernetes Container Solution is a free and open source Content Management System (CMS) that allows organizing, managing and publishing your content. This reliable and secure CMS is built on PHP based environment and powers millions of applications and websites.

Redmine Kubernetes Solution Stack

0 reviews

Redmine Kubernetes Solution Stack is a flexible project management web application. Redmine integrates News, documents and files management and allows Web feeds and e-mail notifications.