A DMP as a network of data services.

Easy to build. Inexpensive to maintain.

Make informed decisions using reliable, comprehensive data that paints a 360 view of your business ecosystem. Our Data Management Platform design is built as a network of data services on Kubernetes and comes complete with a Data orchestration layer for faster reads and writes, a data warehousing service ,a SQL Engine,a notebook Server and a Dashboard application. Leveraging the power and flexibility of containerised applications with Docker on Kubernetes allows for a comprehensive and flexible platform that is easy to build and inexpensive to maintain.It allows organisations to straight away start using the data for deriving business value rather than spend valuable time and resources managing it. Our design incorporates all the industry standards and best practices and takes into account pre-production and post production bottle necks and pain points and mitigates them.

Using Open source technologies that have been time tested in production by large corporations along with running it on Kubernetes, with a file system for persistence brings down the recurring monthly costs considerably as opposed to using other managed services offered by the cloud providers.The flexibility it offers let's you adapt new technologies or sunset obsolete components easily with minimal effort helping your data infrastructure keep up with the changing times making it always cutting edge.


It's just adding more replicas of your application or adding new nodes to your Kubernetes cluster on the fly. Designed to be deployed on Kubernetes, the platform is inherently scalable and inherits all the capabilities that Kubernetes has to offer.The Kubernetes network model and service discovery mechanism along with resource types like Replica sets and Deployments make sure the applications are run in a distributed mode and load balanced appropriatley.

We make sure there is in built capability in all the applications deployed to auto-scale and also have necessary processes in place to scale up or scale down the architecture with minimal manual intervention, depending on the data sizes or traffic patterns.


It's a freedom of choice. Containerised applications let you integrate disparate technologies running on disparate kernels as long as they adhere to the common Kubernetes network model.This gives us flexibilty on choosing only the best technologies for individual components making up the platform architecture and yet integrate them to work in cohesion as a single unit.

Since the individual components in the architecture are isolated conatiners not dependent on a set of common binaries or dependencies, they can be easily integrated with any new custom built services or 3rd party applications. We make sure you have the right automation and processes in place that would let you in the future design or re-design the architecture at will with minimal effort.

High Availability Fault Tolerance

It's a must. A persistence layer is the key part of the platform, not only to persist data but also the state of the applications and services deployed on Kubernetes across failures and restarts making them stateful.

Recovery mechanism , Rolling updates and High availability is an integral part of the Kubernetes model with resources like Replica Sets and Deployments.We have in the design extended this capability with appropriate automation to make sure your applications recover automatically in case of a failure and updates to the services are applied in a rolling fashion mitigating the need for restarts.

We made sure the design makes all the data and the applications in the platform Stateful.We have incorporated into the design processes that with a combination of persistence file systems like S3 and database systems will make sure the state of your data and the applications making up the platform is maintained across failures and restarts.We provide robust backup mechanisms that prevent data loss or corruption. ​

Time and Effort

It's on us. The platform design is an outcome of years of experience from our team developing such Data platforms for large Corporations like ATT and NIke in the U.S.A.The team members have a long experience in designing Data Management Platforms from scratch and incorporated all there learnings and lessons in this design making it robust in performance and easy to maintain.

Between Custom built Docker images, DevOps templates and previous experiences, we make sure the time to production is small and effort for post production maintenance is low.We work with your IT staff during pre-productiuon and post-production in onbaording them to eventually take over the operations. Of course, we'll stay back as along as you want. ​

Recurring Costs

It's inexpensive.The platform design is completely based on containerised applications running on Kubernetes and the technologies used are open-source , which have been time tested in production by Big Corporations like ATT, Nike,Airbnb etc.This helps you get a scalable, and flexible platform that can be extended or re-designed with minimal effort to keep up with the changing times to keep it always cutting edge.

​ Platform designs that use managed services provided by the cloud providers prove to be expensive as data storage and data transfer costs start accumulating every time the service is been called upon .Inefficient way of storing data in a warehousing service like Redshift and inappropriate use of services like Lambda or EMR result in a loss of hundreds of thousands of Euros every year.While some is the result of improper design, lack of vision or ad-hoc development effort ,due to lack of experience , other is getting vendor locked unable to switch to more efficient technologies in the process.

With our design you only pay for the persistence data in file systems like S3 for storing data and infrastructure costs like EC2 systems for the Kubernetes cluster which will be minuscule compared to using other managed services. We have made sure you get processes to scale up or down the platform based on your data loads and processing requirements as often as you need.