The latest News and Information on DevOps, CI/CD, Automation and related technologies.
Testing early and often in the development cycle is a must for ensuring that your application meets user expectations. Poor performance and errors can alienate users and prevent you from meeting crucial benchmarks and OKRs. Additionally, having to constantly implement fixes after new, under-tested features are added can fatigue developers and strain your resources, making your organization less nimble overall.
Netdata just launched a Pandas collector. Pandas is a de-facto standard in reading and processing most types of structured data in Python so if you have some csv/json/xml data, either locally or via some HTTP endpoint, containing metrics you’d like to monitor, chances are you can now easily do this by leveraging the Pandas collector without having to develop your own custom collector as you might have in the past.
Cloud Service Providers (CSPs) offer an ever-expanding array of instance types, ensuring that for any given workload there exists the perfect hosting option that matches the exact needs of that app or business service. But with this expansion comes an ever-increasing challenge to match the workloads to the offerings – there are many things to consider.
Nowadays, the software development paradigm is based on containerizing applications to deploy on pods to let Kubernetes manage it. Containerized applications can then allow Kubernetes to manage its deployment, replication, high availability, metrics and other capabilities so that the application can focus on doing what it was designed to do. This technology is used for projects and by customers all over the globe.
