Operations | Monitoring | ITSM | DevOps | Cloud

The latest News and Information on Continuous Integration and Development, and related technologies.

Migrating to the Cloud at Scale with Fidelity

At swampUP 2023, JFrog’s annual user conference, Gerard McMahon, Head of Application Lifecycle Management (ALM) Tools and Platforms at Fidelity Investments, shared Fidelity’s cloud migration story and how it supports the overall company philosophy. He explored the company’s focus on ensuring employee satisfaction while delivering great software and value to customers.

Kubernetes Services & Types

Kubernetes stands out as a powerful tool for managing, scaling, and deploying containerized applications. At the heart of Kubernetes lies its service management capabilities, which play a crucial role in facilitating communication between various components within a cluster. In this guide, we delve into Kubernetes services, exploring their types, functionalities, and best practices.

Improve Cloud Visibility with JFrog's SaaS Log Streamer

The beauty of deploying SaaS-based applications is that you don’t have to worry about building the infrastructure, hiring engineers to maintain it, staying on top of upgrades or worry about application security. Indeed, these are some of the main benefits you get by using a SaaS offering. However, the world of software is full of trade-offs, so, what do you lose out on?

Build and test LLM applications with AIConfig and CircleCI

The power of LLMs to solve real-world problems is undeniable, but unfortunately, in some cases, only theoretical. What’s stopping us from getting the most out of OpenAI’s text completion capabilities in production apps? One common problem is the inability to confidently guard against bad outputs in production the way we’re used to doing with non-AI test suites. Let’s go one step deeper. There is no equivalent of code coverage for an LLM.

The testing pyramid: Strategic software testing for Agile teams

The testing pyramid model untangles the complexity of software testing by fitting it into an efficient hierarchical structure. By focusing on unit tests at the base, integration tests in the middle, and end-to-end tests at the top, the testing pyramid ensures that most testing efforts are spent on tests that are fast, reliable, and easy to maintain. This allows for quicker iterations, improved code quality, and more stable releases.

Integrating AI and DevOps for Software Development Teams

For a long time, the domains of Machine Learning and AI on one side, and software development on the other side, were separate kingdoms. Sometimes, they touched, and something magical would happen. But more often, things didn’t really work out. They faced challenges stemming from a lack of mutual understanding, shared language, and compatible tools. With the meteoric rise and increased accessibility of powerful generative AI and LLMs, the need for collaboration to achieve real-world engineering and customer value has never been more vital.