When you want to inspect both the return code and output from a command execresult_as_data() might be the function you are searching for. Most CFEngine policy writers have used execresult() and returnszero(). They are useful when you want to do something based on the output of a command or based on its successful execution (returning zero). For example: /tmp/feature-friday-3.cf command output But, sometimes, you care about specific return codes.

Patch management software automatically applies updates to software, firmware, and other system components. Patching makes sure resources are up to date with the latest security and performance improvements to keep software protected and performing as expected.

So, you’ve been tasked with automating one or more of your tedious, time-consuming IT processes… but, what exactly does that mean? And perhaps more importantly, where on earth do you start? IT process automation (ITPA) can cover a broad spectrum of potential use-cases, ranging everywhere from the Service Desk, to the NOC, to Infrastructure, and well beyond.

Platform engineering metrics and/or platform engineering KPIs (Key Performance Indicators) can help us measure the success of this evolving approach and its impact on DevOps. According to our 2024 State of DevOps Report: The Evolution of Platform Engineering — 43% of organizations report that they have had a platform team from 3-5 years already. With this maturity, it’s important to measure what’s working and what isn’t working using the same indicators of success across the board.

The IT landscape is currently evolving faster than ever before, and the move to cloud-based solutions has emerged as a game-changer for businesses looking to future proof their infrastructure. However, the move to cloud solutions is not always straightforward and comes with challenges due to changes in management access.

Machine learning operations (MLOps) has become the backbone of efficient artificial intelligence (AI) development. Blending ML with development and operations best practices, MLOps streamlines deploying ML models via continuous testing, updating, and monitoring. But as ML and AI use cases continue to expand, a need arises for specialized tools and best practices to handle the particular conditions of complex AI apps — like those using large language models (LLMs).

Ever wanted to manipulate a string - temporarily - for an individual promise? Check out the with attribute and its special, $(with) variable. Sometimes you need some variation on a string for a specific case. Traditionally, to achieve this you’d simply define another variable. Here is a contrived example: I have a string, nginx and I want to emit a report that contains both the string itself and the upper case version of the string.

In today’s increasingly complex and rapidly evolving business landscape, the integration of automation technologies has become a crucial strategy for organizations aiming to enhance efficiency, reduce costs, and stay competitive. However, convincing stakeholders and key decision makers to invest in IT automation initiatives requires more than just highlighting its potential benefits.