rostrovsky

## autoRowSpan.js
function autoRowSpan(tableId) {
    var table = document.getElementById(tableId);
    var rows = table.rows;

    // Iterate through each column
    for (var colIndex = 0; colIndex < rows[0].cells.length; colIndex++) {
        var prevCell = null;
        var prevCellText = '';
        var rowspan = 1;

## terragrunt.md

      
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                rostrovsky
                / terragrunt.md
            
            
              Created
              November 9, 2023 20:41
            
          
    Question

i would like to use terragrunt. what i dont like in it is this structure it enforces:
└── live
    ├── prod
    │   ├── app
    │   │   └── main.tf
 │ ├── mysql


## f.md

      
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                rostrovsky
                / f.md
            
            
              Last active
              September 2, 2023 19:28
            
              
                Basic setup of zsh + nvim on Ubuntu 22.04 WSL2
              
          
    sudo apt install zsh
chsh -s $(which zsh)
exit
Log on again
sh -c "$(curl -fsSL https://raw.githubusercontent.com/ohmyzsh/ohmyzsh/master/tools/install.sh)"

  
## prom.md

      
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                rostrovsky
                / prom.md
            
            
              Created
              July 7, 2023 12:40
            
              
                Prometheus storage analysis
              
          
    Prometheus itself doesn't provide built-in tools to directly analyze which metrics are using the most storage. However, there are several ways you can get an idea of which metrics are taking up a lot of space:


Cardinality: A single Prometheus metric with high cardinality (a large number of unique timeseries) can take up a lot of storage. You can use PromQL queries to find metrics with high cardinality. One such query might be count({__name__=~".+"}) by (__name__), which will count the number of unique timeseries for each metric.


Metric volume: You can also check the rate at which metrics are ingested into Prometheus, using a query like rate(prometheus_tsdb_head_samples_appended_total[5m]). This will give you an idea of how many samples are being ingested, which could be a good proxy for understanding which metrics are taking up a lot of space. However, this query won't directly tell you which metrics are responsible for the volume, but will tell you how quickly you're accumulating data ove


## wdioSpecificityBug.html
<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <title>test page</title>
</head>
<body>
<div class="first-nav">
    <ul class="nav-list">
        <li class="nav-list-item">first-nav item 0</li>
	function autoRowSpan(tableId) {
	var table = document.getElementById(tableId);
	var rows = table.rows;

	// Iterate through each column
	for (var colIndex = 0; colIndex < rows[0].cells.length; colIndex++) {
	var prevCell = null;
	var prevCellText = '';
	var rowspan = 1;
	<!DOCTYPE html>
	<html lang="en">
	<head>
	<meta charset="UTF-8">
	<title>test page</title>
	</head>
	<body>
	<div class="first-nav">
	<ul class="nav-list">
	<li class="nav-list-item">first-nav item 0</li>