See how you can build scalable, reliable, and cost-efficient fast data pipelines with DKP
D2iQ Marchiecture

Fast Data Pipelines

Benefits of using Fast Data Pipelines on Kubernetes

Low Latency

The ways in which data is generated and used today has changed dramatically since Hadoop and batch processing. These processes would take hours or even days to get results, which is not optimal for the type of workloads or use cases organizations want to leverage in today's environments. Fast data pipelines help remove latency from the data collection and transport process so that organizations can make smarter decisions faster to improve the customer experience.

Manage Large Volumes of Data

The volume of data and data sources are growing every day. In fact, International Data Corporation (IDC) estimates that 175 zettabytes (a zettabyte is a trillion gigabytes) of data will be created annually, through 2025. Fast data pipelines enable organizations to collect, move, and store very large volumes of data that can be used for big data analysis to provide actionable insights.

Lower Costs

As the volume of generated data increases, so does the need for extracting value from it in real-time. However, the process of collecting, transporting, storing, and processing data can easily overwhelm a company's IT budget. Fast data pipelines constructed using open-source technologies can significantly cut costs, especially when combined with Kubernetes' ability to scale up and down resource utilization in response to demand.

Challenges of using Fast Data Pipelines on Kubernetes

Building a Data Pipeline Requires Time and Expertise

Organizations need the digital agility that only a fast data pipeline on Kubernetes can provide. However, setting up a production-ready environment includes a wide variety of open-source technologies that are very labor intensive to get up and running. Not only that, but operators must take into account the specific requirements and needs of each data service that comprise a fast data pipeline, making it difficult to build a robust data pipeline to support mission-critical workloads.

Operating Fast Data Pipelines is Manual and Error-Prone

In today's data-centric economy, managing your data pipeline throughout its lifecycle is more important than ever. However, managing all of the data sources and the large-scale processes that come with it is incredibly complex. Ongoing maintenance includes a number of tasks, such as upgrading software, deploying updates, and more, that are often manual and time-consuming. Without a way to automate many of the manual tasks, it can lead to an increase in overhead, operating costs, and opportunity costs.

Lack of Centralized Visibility and Standardization

When many different people in the organization are working with data independently and in different ways, it inevitably leads to a lack of standardization. And when there is no single point of control to track where the data comes from, where it moves to, or where it ends up, managing the sprawling web of data sources and the large-scale processes that come with them is hard. This becomes more difficult to manage as the number of data sources and integrations grow and team members multiply.

Unable to Unify Access Across Different Infrastructures

Organizations require a flexible solution that aligns with upstream, open-source Kubernetes so they can integrate with key data services across the ecosystem and deploy anywhere. Being able to unify your fast data pipeline on a single platform gives you the ability to access data services and high value workloads with Day 2 consistency, regardless of cloud provider.

How DKP Enables Simple Provisioning and Deployment of Fast Data Pipelines

Build Production-Ready Fast Data Pipelines with Ease

Enable Fast and Easy Deployment of Key Data Services

Rather than having to piece together a solution, D2iQ does the difficult work for you by selecting all of the key data services from the CNCF landscape, integrating them with the Kommander Catalog, automating their installation, and testing them to ensure they all work together for quick and easy deployment into Kubernetes clusters. Organizations can benefit from faster time to value, reduced overhead, and the robust Day 2 readiness features that Kommander provides, including security, observability, RBAC, and more.

Ensure Lifecycle Management of Key Data Services

Replace Manual Operational Effort With Operators

DKP automates many of the manual tasks required to maintain fast data pipelines through operators, or embedded run-books, that are provided and validated by D2iQ. Anytime you need to make a change to an application, upgrade software, deploy updates, and more, operators tell you the order in which you need to do things to successfully make a change to a complex system. By replacing human effort with code, you'll have peace of mind in the lifecycle management of these key data services.

Unify Disparate Data Sources From a Single Point of Control

Provide Centralized Visibility Across the the Kubernetes Landscape

DKP's federated management plane provides centralized visibility and monitoring of any CNCF-compliant Kubernetes cluster or distribution from a single, central point of control. This simplified bird's eye view helps organizations better understand where their data comes from, where it moves to, and where it ends up. As a result, you and your team can manage fast data pipelines with consistency and reliability, without interfering with the day-to-day business functions and requirements that different clusters support.

Minimize the Costs of Transporting Data

Run Kubernetes on any Infrastructure

DKP is infrastructure agnostic, meaning that software developed on one type of infrastructure will work the same wherever it is run. The ability to run Kubernetes on many different infrastructures makes it easier to bring compute resources closer to the data. It also allows the use of existing on-premise infrastructure in place of public cloud resources that can quickly become expensive. This versitability reduces overall costs and increases ROI for on-premise IT infrastructure.

Much like what VMware does for hosting virtual machines, D2iQ does for containerized applications. With D2iQ, we support our multi-tenancy and security needs, gain a base for future functionality as a data broker, and can easily extend our platform with more nodes.

Luc Van Maldeghem

General Manager, MYCSN

Key Features and Benefits


Operational Dashboard

Provide instant visibility and operational efficiency into the Kubernetes landscape from a single, centralized point of control.


Centralized Observability

Provide enhanced visibility and control at an enterprise level with comprehensive logging and monitoring across all clusters.


Declarative Automated Installer

Accelerate time-to-production on any infrastructure with a highly automated installation process that includes all of the fast data components needed for production.


Lifecycle Automation

Make changes to an application, upgrade software, deploy updates, scale out, scale in, roll back after failures, and more, through Operators that are provided and validated by D2iQ.


Service Catalog

Quickly and easily deploy complex data services from the Kommander platform application catalog to specific or multiple clusters, with governance.


Governance Policy Administration

Meet the requirements of security and audit teams with centralized cluster policy management.


Centralized Authorization and Authentication

Enable single sign-on (SSO) across an organization's cluster footprint and govern authorization with RBAC and Open Policy Access to enhance security and reduce risk.

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