Cloud-Native

MOVE QUICKLY AND GET IDEAS TO MARKET FAST

Unlock digital agility and efficient development practices. Build applications in container-based environments

Cloud-native technologies are used to develop applications built with services packaged in containers, deployed as microservices and managed on elastic infrastructures through agile DevOps processes and continuous delivery workflows.

The purpose is to improve the speed, scalability, and margin of applications.

Spark Equation assists our clients in taking full advantage of cloud-native solutions to create rich user experiences, bring new ideas to market fast, and decrease response time to customer demands.

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case study

Opening New Revenue Streams Through SaaS

Our cloud applications are built from the ground up, designed as loosely coupled systems, optimized for cloud-scale and performance to be used as managed services. We enable our clients to harness continuous delivery to achieve application reliability and faster time to market. Adopting cloud-native technologies and practices enables our clients to create software in-house, allows for a close collaboration between IT and non-IT teams, keep up with competitors and deliver better services to their customers.

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Our Method

The cloud-native strategy is about handling technical risk and moving quickly by taking small, reversible and low-risk steps. We use an open-source software stack to deploy applications as microservices, packaging each part into its own container and dynamically orchestrating those containers to optimize resource utilization.

Process

Successfully delivering cloud-native solutions with these core facets

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Packaged as lightweight containers

Containers can scale-out and scale-in rapidly, meaning infrastructure utilization is optimized

Developed with best-of-breed languages and frameworks

Each solution is developed and paired with the language and framework best suited for functionality

Designed as loosely coupled microservices

Elastic infrastructure and application architectures, when integrated correctly, can be scaled-out with efficiency and high performance

Efficient lifecycle management

Each service is maintained independently and with clear ownership, the Spark team can focus on the core functionality of each service to deliver fine-grained functionality

Stateless and scalable

Underlying infrastructure allows the app to run in a highly distributed manner and still maintain its state, independent of the underlying infrastructure.

Maintained through agile DevOps processes

Creating a production environment within days or hours, rather than weeks or months

Automated capabilities

Infrastructure automation at scale eliminates downtime due to human error and provides consistency in applying guidelines across any size deployment

Continuous delivery

Software is released rapidly because of tighter feedback loops and can respond more effectively to user needs

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