内容简介:This timeBesides terrific autocomplete feature, one of the greatest use cases I’ve discovered recently is the preview window. Say you want to quickly browse contents of all files that match your fuzzy search query. Normally, you do that by applying a
TMWL February 20' — fzf, Datadog & Teraform
Programmers say what they’ve learned
Mar 23 ·3min read
This time Marcin and Michał have shared their discoveries from February:
- how to launch a preview window in fzf;
- how to automate with Datadog & Terraform.
Marcin Baraniecki — Frontend Engineer
fzf is a great tool to quickly find a file or autocomplete the command arguments — by name or pattern. It’s quick, it’s handy and it performs well when you don’t know the exact filename you’re looking for (by applying “fuzzy” search, match & completion).
Besides terrific autocomplete feature, one of the greatest use cases I’ve discovered recently is the preview window. Say you want to quickly browse contents of all files that match your fuzzy search query. Normally, you do that by applying a cat <filename>
command. However, you can join both functionalities:
After issuing a command above ( fzf — preview ‘cat {}’
), a regular fzf search prompt shows up. This time, however, it additionally comes with a right-hand side preview window!
Navigating through a list of files changes the output of the preview window. Additionally, that box can be scrolled independently (by hovering over it with your mouse)!
Preview window is a great feature that can be used with other bash commands, too. Displaying contents of a file ( cat
command) is but a simplest one. What will YOU use it for?
Michał Matłoka — Senior Software Engineer & Architect
It is good to automate. There are things that are just quite obvious — deployments — CI & CD, environments set up etc. However there happen to be some small little things which people tend to omit. One of those things are Datadog dashboards. During this month, I’ve learned that it is pretty simple to bring dashboard definition to your codebase and “deploy” it automatically to Datadog.
Terraform documentation includes a clean description how you can define your dashboards. The definition format is quite similar to the export you can download, from the Datadog website. The main difference is that export is in JSON and terraform uses yaml. How does a single-widget dashboard definition look like? It is pretty simple:
provider “datadog” { api_key = “${var.datadog_api_key}” app_key = “${var.datadog_app_key}” }resource “datadog_dashboard” “ordered_dashboard” { title = “Potato service” layout_type = “ordered” is_read_only = true widget { timeseries_definition { title = “avg meal time (ms)” show_legend = false request { q = “avg:patato_service.meals.avg{service:patato_service,$environment}” display_type = line } } } }
Terrafrom Datadog integration does not offer only support for dashboards. You can define there logs indexes, monitors and a lot of other things. If you are using Datadog, then definitely you should take a look at the Datadog integration .
以上所述就是小编给大家介绍的《This month we've learned: fzf, Datadog and Teraform》,希望对大家有所帮助,如果大家有任何疑问请给我留言,小编会及时回复大家的。在此也非常感谢大家对 码农网 的支持!
猜你喜欢:本站部分资源来源于网络,本站转载出于传递更多信息之目的,版权归原作者或者来源机构所有,如转载稿涉及版权问题,请联系我们。
Algorithms in C, Parts 1-4
Robert Sedgewick / Addison-Wesley Professional / 1997-9-27 / USD 89.99
"This is an eminently readable book which an ordinary programmer, unskilled in mathematical analysis and wary of theoretical algorithms, ought to be able to pick up and get a lot out of.." - Steve Sum......一起来看看 《Algorithms in C, Parts 1-4》 这本书的介绍吧!
图片转BASE64编码
在线图片转Base64编码工具
RGB CMYK 转换工具
RGB CMYK 互转工具