Effective DevOps strategy – Improved customer experience and agile organizational culture

DevOps is a combination of tools, practices, and culture that enables an organization to deliver high-quality software at high velocity. DevOps has evolved tremendously and it plays a pivotal role across all industries.

Agile principles serve as a driver for DevOps implementation, as there are shorter release cycles and automation helps to achieve faster speed to market. Agile principles, cloud computing, and DevOps practices (Continuous Integration, Continuous Testing, and Continuous Delivery) accelerate digital transformation/innovation and faster growth in organizations.

DevOps improves efficiency by:

  • Establishing a unified organizational culture
  • Speeding up review cycles and tightening feedback loops
  • Encouraging collaboration, and
  • Implementing repeatable, automated, auditable infrastructure configurations

As a Google Cloud partner, we are leveraging Google Cloud services to build sophisticated DevOps pipelines.

Our DevOps Implementation experience with a Retail customer

To speed up code delivery and enable the customer to reduce time to market, our team leveraged their DevOps expertise to create cloud-native CI/CD pipelines for Apache Beam jobs on the Google Cloud Platform.

CI/CD pipeline implementation

Using GitHub as a source code repository and Jenkins as a CI/CD automation tool, DevOps engineers designed a CI/CD pipeline to accelerate the processes of developing, testing, and releasing the updates and bug fixes for the customer’s data ingestion/processing pipelines. For enabling continuous review and testing, pipelines were integrated with SONARQube to perform the automatic reviews with static analysis of code to detect bugs, code smells, and generate the test coverage metrics.

Upon clearing the quality gates, code is packaged and uploaded to Google Cloud Storage/Artifact Repository and then deployed the job to Google Cloud Dataflow runner. With the use of Terraform, our team managed to provision or maintain the required infrastructure on the cloud for running the Dataflow jobs.

DevOps drawio

Results

With the DevOps practices that SpringML introduced and applied, the customer got the proper management of their data pipelines & infrastructure and benefited from the high availability. As a result of SpringML’s DevOps engineers’ work, the customer got the possibility to enhance their data feed pipelines (both batch & streaming) frequently without any disruptions.

Get started with the DevOps journey

Partner with SpringML to gain the advantage of access to diverse talent certified in DevOps and other Google Cloud specializations. The list below is growing and as an organization, we are focussed on upskilling our teams to meet the business needs

  • Google Cloud Professional DevOps Engineer x 38
  • Google Cloud Professional Data Engineer x 116
  • Google Cloud Associate Cloud Engineer x 111
  • Google Cloud Professional Cloud Architect x 13
  • Google Cloud Digital Leader x 17
  • TensorFlow Developer Certificate x 4
  • Google Cloud Certified Professional Cloud Security Engineer x 13
  • Google Cloud Certified Professional Networking Engineer x 4
  • HashiCorp Certified: Terraform Associate x 1
  • LookerML Developer x 1
  • Professional Machine Learning Engineer x 9

Thought Leadership