Container security orchestration allows to define within your security policy how you are going to respond to your different container security incidents. These responses can be automated in what is called security playbooks. This way, you can define and orchestrate multiple workflows involving different software both for sourcing and responding. This is how Falco and Splunk Phantom can be integrated together to do this.

While you’re likely familiar with role-based access control, Sysdig teams introduce the concept of service-based access control. With service-based access control, administrators can define groups of users that have access to policy events, policy configuration, and scanning data limited to a service or set of services, as defined by your orchestration system (think Kubernetes, Mesos, and the like).

One of the most common security use cases, is the ability to identify connections generated by malicious actors, or internal components connecting to suspicious servers (e.g malware C&Cs). In this post, we will show how to leverage the Falco engine, to identify connections made to IPs that were flagged by multiple security sensors, and are streamed as a feed to the Falco engine.

In the following tutorial you can learn how to implement container security as code. You probably have a CI/CD pipeline to automatically rebuild your container images. What if you could define your container security as code, push it into a Git repository to version control changes and then enforce your policy in your container orchestration tool like Docker or Kubernetes using Sysdig Secure?

Looking forward to the new Kubernetes 1.13 features? At Sysdig we follow Kubernetes development closely and here we bring you a brief intro to what’s new and features that you will find in the next version of Kubernetes. Kubernetes 1.13 will be out on December 03 2018, so here we go: What’s new in Kubernetes 1.13?

Before the release of Java 9 and 10, there were several limitations to deploying and monitoring Java in Docker. This post explores how the latest versions of Java address the most common of these limitations, and includes examples of how to make the most of monitoring Java in Docker.