Operations | Monitoring | ITSM | DevOps | Cloud

Earlier this month the development industry was preparing for rate limit changes at Docker Hub. Ultimately, any rate limit changes were put on hold. Many JFrog customers have asked us, “How would Docker Hub rate limit changes impact us?” In this post we’ll discuss what you can do to ensure uninterrupted usage of Docker, now and into the future, regardless of rate limits.

Over the past ten years, Azure has become one of the most prominent cloud computing platforms available, rivaled only by AWS. Part of Microsoft’s suite of Azure services, Azure web apps provide a packaged environment for hosting web applications built in many languages. Because this environment is fully managed by Azure, developers have limited options for control.

Jenkins is an open-source automation server widely used for continuous integration and continuous delivery (CI/CD), enabling developers to automate the building, testing, and deployment of software projects. Jenkins requires a good layer of visualization as it provides real-time visibility into pipeline performance, build statuses, test results, and deployment progress.

Deploying Large Language Model (LLM) applications can transform ideas into valuable services. But, deployment challenges can slow down even experienced developers. In this tutorial, you will build and deploy a LangChain application using LangServe and CircleCI on Google Cloud Run. You will create a text summarization tool powered by Google’s Gemini model. You will use Langserve to expose it as an API. You will automate testing and deployment to Google Cloud Run using CircleCI.

Test failures are inevitable. A broken condition, a missed edge case, or a last-minute refactor can trip up even the most careful changes. That’s part of shipping software. What shouldn’t be part of the job is spending half your afternoon parsing logs and chasing down the root cause. Now, there’s a faster way. This guide shows how to use the CircleCI MCP server to identify, understand, and resolve failing tests in a CI/CD build without ever leaving your editor.

Implementing robust data governance in microservices architectures presents unique challenges and opportunities. As organizations decompose monolithic applications into distributed services, traditional centralized data management approaches no longer suffice. Each microservice may manage its own data store, creating potential inconsistencies, compliance risks, and security challenges.

Monolithic and microservices architectures represent two fundamentally different approaches to software design. By understanding the benefits and drawbacks of each architectural style, developers can make informed decisions about which approach best fits their application needs. While monolithic architecture bundles all application functionality into a single deployable unit, microservices architecture breaks the application into smaller, independently deployable services.