With digital technologies transforming industries, companies adopt Agile and other practices to gain a competitive advantage. DevOps is one such method that has changed software development as we know it. The new-age approach helps accelerate productivity and also enables better collaboration between the development and operation teams. But the biggest benefit of adopting DevOps is faster time-to-market. It has helped around 83% of organizations unlock business value and deliver customer value faster.

The customer is one of the largest private-sector banks in India that has been leading the way in innovation and customer service. With a network of over 5,500 branches and 15,000 ATMs across the country, this bank offers a range of financial products and services to its customers, including personal banking, corporate banking, wealth management, insurance, and investment banking.

Data movement is an essential aspect of modern computing, as it involves the transfer of data from one location to another. This process is critical for data processing, storage, and analysis, and it can be performed in various ways, including network transfers, file transfers, and memory transfers.

In today’s fast-paced world of software development, it’s crucial to ensure that the products you build meet the needs and expectations of your users. This is where testing comes in, and there are various types of testing that you can perform to achieve this goal. The two important types of testing are API and UI testing.

Customizing exceptions is usually not a common concern during software development. But if you catch an error in an observability tool and can't correctly and quickly identify the problem, you may need more information and details about an exception. This article will show you how to customize exceptions in Ruby and mitigate potential future problems due to a lack of error information. Let's dive straight in!

Traditionally, manual test management and automated testing generate independent quality reporting data that has to be either manually integrated in spreadsheets or programmatically via scripts and reporting tools. This process takes valuable QA time away from actual testing and can also create inconsistency and inaccuracy when reporting on release readiness due to both the lag time in combining data from both sources and general human error.

We recently rolled out our very own GPU autoscaler in Collaboration with Genesis Cloud and it has been quite a success. Also recently, YOLOv8 by Ultralytics was unveiled, the new king of object detection, segmentation and classification. In this blogpost we’ll see that you can train a computer vision model using the ClearML/Genesis Cloud autoscaler at a fraction of the cost of competing cloud services like AWS or GCP. And it even runs 100% off of green energy! 😎

Every engineering leader wants to build a high-performance team that can set the standard for velocity, quality, and innovation. Yet, to do that, you need to focus on creating a culture of continuous improvement where everyone in the team is committed to learning and growing.

We are announcing BigQuery ML inference engine, which allows you to run predictions on a broad range of models hosted across multiple locations.

Deciding where to run your enterprise workloads is one of the biggest business decisions you’ll make. That’s because your chosen deployment model influences how you access software and systems, scale your business, and safeguard sensitive data. There are three main deployment methods you need to know about: Self-hosted, on-premises, and cloud. All three models have pros and cons, so it’s important to do your research before investing in new infrastructure and/or services.