The latest News and Information on Containers, Kubernetes, Docker and related technologies.
The PodSecurityPolicy API, initially deprecated in Kubernetes v1.21, was entirely removed in Kubernetes v1.25. Because the API was removed, you cannot create, edit or query PodSecurityPolicy resources in a Kubernetes v1.25 cluster. Also, because its admission controller was removed, your clusters can no longer enforce any PodSecurityPolicy rules that were created in Kubernetes v1.24 and prior.
In our previous blog, we discussed the difficulty in capturing all relevant diagnostics during an incident before a “band-aid” fix is applied. The most common, concrete example of this is an application running in a container and the container is redeployed—perhaps to a prior version or the same version—simply to solve the immediate issue.
Securing sensitive data is crucial for any application, but managing this data can be complex and error-prone. Docker secrets provide a reliable and secure way to handle sensitive information like passwords, API keys, and certificates in your Docker environment. In this introductory guide, we’ll explore what Docker secrets are, how to use them with practical examples, and share some best practices to help you safeguard your sensitive data effectively.
KubeCon + CloudNativeCon is the premier event that focuses on cloud-native technologies and Kubernetes. This year’s European edition took place in person and was completely sold out, with 10,000 attendees. Datadog joined the event as a platinum sponsor, and several of our engineers delivered talks on various topics, ranging from etcd to image signing and verification. In this post, we’ll share more details on these talks, along with our takeaways from the event.
So you want to spin up a Postgres database on your local machine, but you don't fancy having to install and manage everything manually? Running Postgres inside Docker is a great way to simplify the situation. It lets you: In this article I will explain how to do this step by step.
If you’re in DevOps, you know the word ‘Kubernetes’. While saying that mouthful of a word (generally shortened to k8s in text) would have gotten you a weird look and someone asking if you need to lie down before 2017, it’s been sacrilegious to even consider starting a project without architecting your solution on top of it in the last few years.
As engineers, we tend to pride ourselves on building a production-first mindset and operational excellence. According to a recent survey, 74% of executives believe that AI will deliver more efficient business processes, while 55% think that AI will help develop new business models and create new products and services. However, the reality is that 85% of ML projects fail to deliver, and 53% of machine learning prototypes don't make it to production.
