2.1 Explore & Discover (Public Product Catalog) #
Comprehensive software marketplace allowing users to explore technology artifacts from multi-vendors across different business areas to discover the most suitable software solution to fulfill a business requirement. User-friendly interface to navigate across the marketplace that would help identify the most relevant product based on product vendor or segment.
2.2 Private Catalog (Private Product Repository) #
Onboard users own Kubernetes-based containerized products in a private product repository which is accessible only to the user so that solutions can be designed and orchestrated to cater to user-specific business requirements along with integrations with other products.
2.3 Solution Design #
Mix & Match concept allows the users to pick artifacts from vendors to design the required solution as well as Onboard their own containerized products and maintain it in their private catalog which would allow designing solutions to cater to business needs.
2.4 Easy to use Drag & Drop Canvas #
A canvas that would allow users to design an end-to-end technological solution architecture on a GUI canvas after hand-picking the technology artifacts. Update the canvas whenever required before publishing & deploying so that necessary changes can be made to the required solution.
2.5 One-click Deployment #
Upon publishing the solution architecture on the canvas, the user will be able to deploy the solution within a Kubernetes cluster on a preferred environment with a single button click. Ahasa supports AWS & GCP currently but will be improved to cater to on-premise infrastructure setups as well.
2.6 Continuous Updates #
Deployed solutions are kept up to date with the artifact vendors deploying the latest available version of artifacts to the catalog. Automated release management will be provided to ensure smooth and continuous updates of technological artifacts.
2.7 Monitoring #
Users can monitor the status of deployed clusters which will allow them to get an idea of the infrastructure usage and capacity-related information of the clusters which will be helpful in terms of decision-making and other operational matters.
