What’s a monorepo? Imagine if every time you needed to make a new source control repository, you just made a new top-level folder in your current repository instead. You’re doing monorepo! All the software written by everyone in your company stored together, versioned together.
ᗧ•••ᗣᗣᗣᗣ•• #Python #SRE #DevOps #DevSecOps #ETH #CHFI #CEH #CISSP #RedTeam #BlueTeam
Why every development team needs continuous delivery....
Continuous delivery helps you move faster and retain talent. Yet only 28% of dev teams do it! Find out why continuous delivery could be your competitive advantage.
28%. That is the number of teams currently practicing continuous delivery (CD) across all projects, company wide. That means a whopping 72% of software teams are likely to feel dread instead of relief when they hear the term “release”
28%. That is the number of teams currently practicing continuous delivery (CD) across all projects, company wide. That means a whopping 72% of software teams are likely to feel dread instead of relief when they hear the term “release”
Monitoring Linux Logs with Kibana and Rsyslog
Monitoring Linux logs is crucial and every DevOps engineer should know how to do it. Here’s why :
- You have real-time visual feedback about your logs : probably one of the key aspects of log monitoring, you can build meaningful visualizations (such as datatables, pies, graphs or aggregated bar charts) to give some meaning to your logs.
- You are able to aggregate information to build advanced and more complex dashboards : sometimes raw information is not enough, you may want to join it with other logs or to compare it with other logs to identify a trend. A visualization platform with expression handling lets you perform that.
- You can quickly filter for a certain term, or given a certain time period : if you are only interested in SSH logs, you can build a targeted dashboard for it.
- Logs are navigable in a quick and elegant way : I know the pain of tailing and greping your logs files endlessly. I’d rather have a platform for it.
Python Modules and Packages
There are actually three different ways to define a module in Python:
- A module can be written in Python itself.
- A module can be written in C and loaded dynamically at run-time, like the
re(regular expression) module. - A built-in module is intrinsically contained in the interpreter.
A module’s contents are accessed the same way in all three cases: with the
importstatement.Absolute vs Relative Imports in Python
A Python module is a file that has a
.py extension, and a Python package is any folder that has modules inside it (or, in Python 2, a folder that contains an __init__.pyfile).
What happens when you have code in one module that needs to access code in another module or package? You import it!
Memory Management in Python
Memory Is an Empty Book
You can begin by thinking of a computer’s memory as an empty book intended for short stories. There’s nothing written on the pages yet. Eventually, different authors will come along. Each author wants some space to write their story in.
Since they aren’t allowed to write over each other, they must be careful about which pages they write in. Before they begin writing, they consult the manager of the book. The manager then decides where in the book they’re allowed to write.
Since this book is around for a long time, many of the stories in it are no longer relevant. When no one reads or references the stories, they are removed to make room for new stories.
Notificaciones de Grafana en Slack
Como ya tengo algo saturada la bandeja de correo, acabé decidiéndome por enviar las notificaciones de Grafana a Slack :D.
En primer lugar tendremos que crearnos una cuenta en Slack si no la tenemos todavía. Crearemos un espacio de trabajo (workspace) y un canal al que en mi caso he llamado #grafana. Todas las notificaciones de mi servidor Grafana irán a parar a ese canal.
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