Datadog announced an integration with Nessus from Tenable.
It is extremely important for DevOps teams to build a Continuous Delivery Pipeline in which they have complete confidence to help them deliver quality software efficiently and faster.
Among one of the first things that the team can do to increase the quality, frequency, and velocity of delivering software is to automate everything they can. Automation ensures repeatability, reduces human errors, and accelerates routine tasks that are conducted repeatedly. Once a task is automated, the machine will keep performing it the same way until it is instructed to do it another way – unlike a human operator whose efficiency at the task can vary depending on various external factors and disruptions.
An excellent example of applying automation to increase efficiency and reducing errors in DevOps is the automation of deploying applications. Applications are complex and the knowledge of all the components and how they fit together usually lies with the enterprise architects and developers as they are the ones that design the application. However, once designed and coded, applications are deployed tens and sometimes hundreds of times in the delivery pipeline before being deployed to end users. As each team (QA, security, production, and others) deploy the application in their environments, more often than not, the deployments fail due to the lack of insight and knowledge of the architect or developer that initially designed the application.
Capturing this critical knowledge, storing it in a source code repository, and then automating the application deployment through automation helps eliminate deployment failures, speeds up the delivery process, and of course, leads to consistent results each time. Application Deployment automation is a must-have capability that each team adopting DevOps principles must incorporate as one of the steps towards building confidence in the Continuous Delivery Pipeline.
Ashish Kuthiala is Senior Director, Strategy & Marketing, DevOps, Hewlett Packard Enterprise.