DevOps technologies enable the fast and efficient implementation of new features in a complex cloud architecture. This increases both the speed and quality of productive deployments and thus generates ever greater added value for your cloud product and your customers.
DevOps technologies enable the fast and efficient implementation of new features in a complex cloud architecture. This increases both the speed and quality of productive deployments and thus generates ever greater added value for your cloud product and your customers.
DevOps technologies enable the fast and efficient implementation of new features in a complex cloud architecture. This increases both the speed and quality of productive deployments and thus generates ever greater added value for your cloud product and your customers.
The core principles of DevOps include close collaboration between development/operations teams and use of unified software solutions to automate various manual tasks. The typical work cycle in the DevOps model consists of the following phases: Plan, Implement, Test, Deploy, Operate, Monitor, Feedback. The individual phases form a highly iterative flow over time in order to fulfill emerging customer requirements as quickly as possible. Translated with www.DeepL.com/Translator (free version)
Use existing know-how in combination with cloud-native services from Azure, AWS and GCP.
Systematic recording and planning of tasks with Scrum and Kanban boards.
Code versioning for both the product and the underlying infrastructure.
Automated deployment and testing through continuous integration and continuous delivery (CI/CD) pipelines.
Saving build artifacts in a cloud-native artifacts repository or container image registry.
Dedicated microservices and container services for modern distributed applications.
Unlimited memory and compute resources for upscalability and flexibility.
Previous posts in this series addressed two recurring challenges when working with nested data in Spark SQL. This post focuses on nested data ...
When working with data, change is inevitable. Event producers adjust formats, add attributes, or modify data types as systems evolve. While th...
As a data engineer, data analyst, or Spark SQL practitioner, you have probably encountered nested data in Spark SQL in the form of objects nest...
While cloud solutions are increasingly becoming the standard, many companies continue to rely on their existing on-premises systems – driven...
You will shortly receive an email to activate your account.
