Low Code DevOps Platform
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Low Code DevOps Platform
Configure and run continuous integration and deployment of artifacts. Accelerate the DevOps lifecycle by streamlining application development with features, fixes, and updates. Implement changes in applications and deploy them instantly by leveraging comprehensive DevOps tools. Streamline different stages of the pipeline with a user-friendly pipeline designer and ensure real-time monitoring.
Applications are deployable on Amazon Web Services and Microsoft Azure.
Seamless DevOps Lifecycle
- Faster application deployment and superior delivery with fast code changes and automated testing for developers
- Integration with testing, validation and verification tools at various stages of application development for developing error free applications
- Govern the pipeline execution based on user rights
- Seamless orchestration of APIs, from both the platform and external sources, for streamlined development and deployment process
Simplified Application Deployment
- Support for various application types, including portal, progressive web application, mobile, process, rules, reports, and others, for orchestrating complete application pipeline
- User-friendly interface for system-defined roles – IT admin, release managers, and DevOps engineers. Provision to define custom roles according to the organizational needs
- Artifact versioning, auto-backup, and restore actions for efficient management of application deployment
Flexible Deployment Environment
- Smooth on-premises, cloud-based, and hybrid deployment,giving flexibility to organizations to manage their deployment environments
- Easily manage multiple deployment environments with an intuitive pipeline designer
Comprehensive Dashboard for Reporting and Analysis
- Detailed dashboards for monitoring the performance of applications
- Real-time pipeline monitoring for better visibility
- Tracking of the previously executed pipelines for detailed analysis
Account opening and loan disbursal in 2-3 days
90% increase in workforce productivity
Improved agility and responsiveness
How does NewgenONE reduce risks during deployment?
NewgenONE facilitates the blue-green deployment model for containerized cloud deployments. It enables the operations team to run two identical production environments, where only one environment (blue) is live most of the time, whereas the other is idle (green). Once a new version of the software is available, it is moved to the green environment, and then the traffic is redirected from the blue environment to the green using the load balancer.
This capability benefits operations teams by enabling customers to switch from an old to a new version without downtime. Furthermore, it allows the blue environment to serve as a backup in case of any failure or disaster on the newly deployed green environment.
How do you integrate security into a DevOps workflow?
To integrate security into a DevOps workflow, you can embed security practices into each stage of the software development lifecycle. Also, use automated security testing tools and techniques, perform regular vulnerability assessments, and ensure compliance with industry security standards and regulations.
What role does automation play in DevOps?
Automation plays a crucial role in DevOps by streamlining and automating manual and repetitive tasks, such as testing, building, and deployment. Also, enabling faster and more frequent releases, reducing errors and downtime, and improving the overall efficiency and quality of the software development process.
Does NewgenONE users need to procure a database separately for storing user data?
Yes. The NewgenONE platform has a database for managing user data. It also supports a cloud-only deployment.
What are some common challenges of cloud deployment?
Common challenges of cloud deployment include data security and compliance, vendor lock-in, performance and availability, integration with existing systems, and the need for specialized skills and expertise.
How can an enterprise optimize cloud deployment for performance and scalability?
To optimize cloud deployment for performance and scalability, it is important to use auto-scaling, load balancing, caching, and other optimization techniques. Monitoring and analyzing performance metrics, identifying bottlenecks, and making necessary changes are also crucial to achieve optimal performance and scalability in the cloud.
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