To manage large infrastructures, efficient solutions for both making changes and observing the current state are necessary. As most information (inventory) about hosts is quite predictable and static, there are many opportunities for optimizations in terms of compression and avoiding re-transmission of the same data. In the CFEngine team, we are improving our reporting systems with a focus on correctness and low bandwidth consumption. This will benefit many users, both large data centers where bandwidth (networking equipment) is costly, as well as small IoT devices with limited connectivity.
For CFEngine we manage several public and private repositories of code in GitHub for our Open Source and Enterprise products. In order to ensure quality we run many checks on the code both with nightly builds as well as on each pull request. We use a Jenkins server for nightlies which also includes more extensive deployment tests on all of the platforms we support. Previously we had used Travis for many of these checks but that system started to show its age and limitations.
The license of our in-house C utility and compatibility library libntech was recently changed from GPLv3 to Apache License Version 2.0 which makes the library suitable for more projects thanks to the more permissive license. While GPLv3 practically required any project using libntech to be licensed under GPLv3 as well, the Apache License v2.0 allows any open source as well as proprietary software to utilize our utility library, keeping the copyright attributions.
Opening and reading files may cause your program to block indefinitely. In this blogpost we'll discuss how to work around this issue.
This guide is designed for the novice user of CFEngine who wishes to explore the power of Emacs while developing CFEngine policy files – and will introduce the use of some Emacs features and plugins along the way.
There are two types of editors available in the Unix and Linux world: line and visual. Examples of line editors are ed and sed. These allow you to edit a file one line at a time.
As a person who tries to work with as few resources as possible, whether it’s editing everything with ed(1) or using old laptops without screens for servers or turning off computers as much as possible I am happy to announce nightly packages are available for the aarch64 (ARM 64-bit) architecture.
This enables low-power, low-cost devices such as the Raspberry Pi and many others to run CFEngine Enterprise.
Why run CFEngine? It is lean on resources and rich in features!
What’s autorun?
Autorun is a feature of the Masterfiles Policy Framework (MPF)1 that simplifies the process of adding and executing new policy.
We have talked about Modular policies with autorun and the Augments before. This time, we dig into autorun a bit deeper to explore some of its current features and look at how to implement your own as we did during The Agent is In, Episode 15 - Extending Autorun
This is the second blog post in a short series about processes on UNIX-like systems. It is a followup to the previous post which focused on basic definitions, creation of processes and relations between them. This time we analyze the semantics of two closely related system calls that play major roles in process creation and program execution.
fork() and exec() The UNIX-based operating systems provide the fork() system call1 to create a clone of an existing process and the execve() system call to start executing a program in a process.
While working on the integration of CFEngine Build into Mission Portal we came to the point where we needed to start executing separate tools from our recently added daemon - cf-reactor. Although it may seem like nothing special, knowing a bit about the process creation and program execution specifics (and having to fight some really hard to solve bugs in the past) we spent a lot of time and effort on this step.
Databases are great for data processing and storage. However, in many cases it is better or easier to work with data in files on a file system, some tools even cannot access the data in any other way. When a database (DB) is created in a database management system (DBMS) using a file system as its data storage, it of course uses files on the given file system to store the data.