The emergence of DevOps has changed the way enterprises handle software delivery processes, leading to faster and improved quality. After DevOps has been coined, other practices such as DataOps, MLOps, and AIOps have emerged. In the podcast, Michelle and Andreea, Data PM and AI Product Managers, respectively, will be discussing the significance of these Ops processes in streamlining and optimizing enterprise data, machine learning, and AI projects and use cases.
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In the ever-evolving landscape of software development, testing plays a crucial role in ensuring the quality, reliability, and performance of applications. As technology continues to advance, the future of testing is deeply intertwined with automation, offering immense potential for improving efficiency, speed, and accuracy in the testing process.
There is no getting away from it, automation can be complicated. First, it is working out where to start, and it isn’t as simple as installing an application or signing up to a service and configuring it once. Automation is a journey not made easier by the drive for AI (check out this webinar on Automation & AI), which will aid productivity but could actually increase manual work performed today by surfacing more insights that need to be manually addressed.
For enterprises using both hybrid- and multi-cloud architectures, Software Defined Cloud Interconnects (SDCIs) are increasingly well-recognised as the most advantageous approach to private cloud connectivity. In fact, by 2027 Gartner® predicts 30% of enterprises will employ SDCI services to connect to public cloud service providers. This is a threefold increase from less than 10% in 2022.
Already a quarter of the way into 2024, we’re seeing a lot of shake-up in on-call best practices. We’re excited to see AI in the mix, but we’re also seeing a renewed focus on existing and neglected best practices. Some current topics in on-call best practices include: In this article, we’ll review some best practices and explore the 2024 trends.
Ashan Senevirathne is an experienced Product Owner and Senior DevOps Engineer with a proven track record in driving innovation and efficiency in telecommunications. Currently with Swisscom, leading the development of a cloud-native orchestration framework for 5G Core using Kubernetes. Adept at optimizing release engineering processes, championing CI/CD workflows, and fostering cross-functional collaboration. Recognized for his expertise in Kubernetes, GitOps, cloud-native principles, and network orchestration.
As businesses increasingly migrate to the cloud, understanding the intersections of data transfer expenses is very important. In this article, we’ll break down what Azure Data Transfer Costs entail, explore various types of data transfers, explore Azure Bandwidth pricing, identify the possible factors influencing data transfer costs, and some strategies for optimizing expenses.
Document retention is a critical component of modern data governance, requiring meticulous strategy and precise execution. In today’s digital age, businesses are inundated with vast quantities of data, making effective document management not just advisable but essential. This is particularly true when considering the legal and compliance obligations that organizations must navigate.