Windocks
Windocks provides on-demand Oracle, SQL Server, as well as other databases that can be customized for Dev, Test, Reporting, ML, DevOps, and DevOps. Windocks database orchestration allows for code-free end to end automated delivery. This includes masking, synthetic data, Git operations and access controls, as well as secrets management. Databases can be delivered to conventional instances, Kubernetes or Docker containers.
Windocks can be installed on standard Linux or Windows servers in minutes. It can also run on any public cloud infrastructure or on-premise infrastructure. One VM can host up 50 concurrent database environments. When combined with Docker containers, enterprises often see a 5:1 reduction of lower-level database VMs.
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JS7 JobScheduler
JS7 JobScheduler, an Open Source Workload Automation System, is designed for performance and resilience. JS7 implements state-of-the-art security standards. It offers unlimited performance for parallel executions of jobs and workflows.
JS7 provides cross-platform job execution and managed file transfer. It supports complex dependencies without the need for coding. The JS7 REST-API allows automation of inventory management and job control.
JS7 can operate thousands of Agents across any platform in parallel.
Platforms
- Cloud scheduling for Docker®, OpenShift®, Kubernetes® etc.
- True multi-platform scheduling on premises, for Windows®, Linux®, AIX®, Solaris®, macOS® etc.
- Hybrid cloud and on-premises use
User Interface
- Modern GUI with no-code approach for inventory management, monitoring, and control using web browsers
- Near-real-time information provides immediate visibility to status changes, log outputs of jobs and workflows.
- Multi-client functionality, role-based access management
- OIDC authentication and LDAP integration
High Availability
- Redundancy & Resilience based on asynchronous design and autonomous Agents
- Clustering of all JS7 Products, automatic fail-over and manual switch-over
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Oracle Container Engine for Kubernetes
Oracle's Container Engine for Kubernetes (OKE) serves as a managed container orchestration solution that significantly minimizes both the time and expenses associated with developing contemporary cloud-native applications. In a departure from many competitors, Oracle Cloud Infrastructure offers OKE as a complimentary service that operates on high-performance and cost-efficient compute shapes. DevOps teams benefit from the ability to utilize unaltered, open-source Kubernetes, enhancing application workload portability while streamlining operations through automated updates and patch management. Users can initiate the deployment of Kubernetes clusters along with essential components like virtual cloud networks, internet gateways, and NAT gateways with just a single click. Furthermore, the platform allows for the automation of Kubernetes tasks via a web-based REST API and a command-line interface (CLI), covering all aspects from cluster creation to scaling and maintenance. Notably, Oracle does not impose any fees for managing clusters, making it an attractive option for developers. Additionally, users can effortlessly and swiftly upgrade their container clusters without experiencing any downtime, ensuring they remain aligned with the latest stable Kubernetes version. This combination of features positions Oracle's offering as a robust solution for organizations looking to optimize their cloud-native development processes.
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Pipeshift
Pipeshift is an adaptable orchestration platform developed to streamline the creation, deployment, and scaling of open-source AI components like embeddings, vector databases, and various models for language, vision, and audio, whether in cloud environments or on-premises settings. It provides comprehensive orchestration capabilities, ensuring smooth integration and oversight of AI workloads while being fully cloud-agnostic, thus allowing users greater freedom in their deployment choices. Designed with enterprise-level security features, Pipeshift caters specifically to the demands of DevOps and MLOps teams who seek to implement robust production pipelines internally, as opposed to relying on experimental API services that might not prioritize privacy. Among its notable functionalities are an enterprise MLOps dashboard for overseeing multiple AI workloads, including fine-tuning, distillation, and deployment processes; multi-cloud orchestration equipped with automatic scaling, load balancing, and scheduling mechanisms for AI models; and effective management of Kubernetes clusters. Furthermore, Pipeshift enhances collaboration among teams by providing tools that facilitate the monitoring and adjustment of AI models in real-time.
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