Loma  Baumbach

Loma Baumbach

1601120400

Using the Four Keys to measure your DevOps performance

Through six years of research, the DevOps Research and Assessment (DORA) team has identified four key metrics that indicate the performance of a software development team:

  • Deployment Frequency - How often an organization successfully releases to production
  • Lead Time for Changes - The amount of time it takes a commit to get into production
  • Change Failure Rate - The percentage of deployments causing a failure in production
  • Time to Restore Service - How long it takes an organization to recover from a failure in production

At a high level, Deployment Frequency and Lead Time for Changes measure velocity, while Change Failure Rate and Time to Restore Service measure stability. And by measuring these values, and continuously iterating to improve on them, a team can achieve significantly better business outcomes. DORA, for example, uses these metrics to identify Elite, High, Medium and Low performing teams, and finds that Elite teams are twice as likely to meet or exceed their organizational performance goals.1

Baselining your organization’s performance on these metrics is a great way to improve the efficiency and effectiveness of your own operations. But how do you get started? The journey starts with gathering data. To help you generate these metrics for your team, we created the Four Keys open source project, which automatically sets up a data ingestion pipeline from your Github or Gitlab repos through Google Cloud services and into Google DataStudio. It then aggregates your data and compiles it into a dashboard with these key metrics, which you can use to track your progress over time.

To use the Four Keys project, we’ve included a setup script in the repo to make it easy to collect data from the default sources and view your DORA metrics. For anyone interested in contributing to the project or customizing it to their own team’s use cases, we’ve outlined the three key components below: the pipeline, the metrics, and the dashboard.

The Four Keys pipeline

The Four Keys pipeline is the ETL pipeline which collects your DevOps data and transforms it into DORA metrics.

One of the challenges of gathering these DORA metrics, however, is that, for any one team (let alone all the teams in an organization), deployment, change, and incident data are usually in different disparate systems. How do we develop an open-source tool that can capture data from these different sources—as well as from sources that you may want to use in the future?

With Four Keys, our solution was to create a generalized pipeline that can be extended to process inputs from a wide variety of sources. Any tool or system that can output an HTTP request can be integrated into the Four Keys pipeline, which receives events via webhooks and ingests them into BigQuery.

Four Keys pipeline.jpg

Click to enlarge

In the Four Keys pipeline, known data sources are parsed properly into changes, incidents and deployments. For example, GitHub commits are picked up by the changes script, Cloud Build deployments fall under deployments, and GitHub issues with an ‘incident’ label are categorized as incidents. If a new data source is added and the existing querie s do not categorize it properly, the developer can recategorize it by editing the SQL script.

#google cloud platform #open source #devops & sre #devops

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Buddha Community

Using the Four Keys to measure your DevOps performance

How to Create an Image Clip Animation with Slider Controls using Only HTML & CSS

In this blog you’ll learn how to create an Image Clip Animation with Slider Controls using only HTML & CSS.

To create an Image Clip Animation with Slider Controls using only HTML & CSS. First, you need to create two Files one HTML File and another one is CSS File.

1: First, create an HTML file with the name of index.html

<!DOCTYPE html>
<html lang="en" dir="ltr">
  <head>
    <meta charset="utf-8">
    <title>Image Clip Animation | Codequs</title>
    <link rel="stylesheet" href="style.css">
  </head>
  <body>
    <div class="wrapper">
      <input type="radio" name="slide" id="one" checked>
      <input type="radio" name="slide" id="two">
      <input type="radio" name="slide" id="three">
      <input type="radio" name="slide" id="four">
      <input type="radio" name="slide" id="five">
      <div class="img img-1">
        <!-- <img src="images/img-1.jpg" alt="">
      </div>
      <div class="img img-2">
        <img src="images/img-2.jpg" alt="">
      </div>
      <div class="img img-3">
        <img src="images/img-3.jpg" alt="">
      </div>
      <div class="img img-4">
        <img src="images/img-4.jpg" alt="">
      </div>
      <div class="img img-5">
        <img src="images/img-5.jpg" alt="">
      </div>
      <div class="sliders">
        <label for="one" class="one"></label>
        <label for="two" class="two"></label>
        <label for="three" class="three"></label>
        <label for="four" class="four"></label>
        <label for="five" class="five"></label>
      </div>
    </div>
  </body>
</html>

2: Second, create a CSS file with the name of style.css

*{
  margin: 0;
  padding: 0;
  box-sizing: border-box;
}
body{
  min-height: 100vh;
  display: flex;
  align-items: center;
  justify-content: center;
  background: -webkit-linear-gradient(136deg, rgb(224,195,252) 0%, rgb(142,197,252) 100%);
}
.wrapper{
  position: relative;
  width: 700px;
  height: 400px;
}
.wrapper .img{
  position: absolute;
  width: 100%;
  height: 100%;
}
.wrapper .img img{
  height: 100%;
  width: 100%;
  object-fit: cover;
  clip-path: circle(0% at 0% 100%);
  transition: all 0.7s;
}
#one:checked ~ .img-1 img{
  clip-path: circle(150% at 0% 100%);
}
#two:checked ~ .img-1 img,
#two:checked ~ .img-2 img{
  clip-path: circle(150% at 0% 100%);
}
#three:checked ~ .img-1 img,
#three:checked ~ .img-2 img,
#three:checked ~ .img-3 img{
  clip-path: circle(150% at 0% 100%);
}
#four:checked ~ .img-1 img,
#four:checked ~ .img-2 img,
#four:checked ~ .img-3 img,
#four:checked ~ .img-4 img{
  clip-path: circle(150% at 0% 100%);
}
#five:checked ~ .img-1 img,
#five:checked ~ .img-2 img,
#five:checked ~ .img-3 img,
#five:checked ~ .img-4 img,
#five:checked ~ .img-5 img{
  clip-path: circle(150% at 0% 100%);
}
.wrapper .sliders{
  position: absolute;
  bottom: 20px;
  left: 50%;
  transform: translateX(-50%);
  z-index: 99;
  display: flex;
}
.wrapper .sliders label{
  border: 2px solid rgb(142,197,252);
  width: 13px;
  height: 13px;
  margin: 0 3px;
  border-radius: 50%;
  cursor: pointer;
  transition: all 0.3s ease;
}
#one:checked ~ .sliders label.one,
#two:checked ~ .sliders label.two,
#three:checked ~ .sliders label.three,
#four:checked ~ .sliders label.four,
#five:checked ~ .sliders label.five{
  width: 35px;
  border-radius: 14px;
  background: rgb(142,197,252);
}
.sliders label:hover{
  background: rgb(142,197,252);
}
input[type="radio"]{
  display: none;
}

Now you’ve successfully created an Image Clip Animation with Sliders using only HTML & CSS.

#html #css 

How to Extend your DevOps Strategy For Success in the Cloud?

DevOps and Cloud computing are joined at the hip, now that fact is well appreciated by the organizations that engaged in SaaS cloud and developed applications in the Cloud. During the COVID crisis period, most of the organizations have started using cloud computing services and implementing a cloud-first strategy to establish their remote operations. Similarly, the extended DevOps strategy will make the development process more agile with automated test cases.

According to the survey in EMEA, IT decision-makers have observed a 129%* improvement in the overall software development process when performing DevOps on the Cloud. This success result was just 81% when practicing only DevOps and 67%* when leveraging Cloud without DevOps. Not only that, but the practice has also made the software predictability better, improve the customer experience as well as speed up software delivery 2.6* times faster.

3 Core Principle to fit DevOps Strategy

If you consider implementing DevOps in concert with the Cloud, then the

below core principle will guide you to utilize the strategy.

  • It is indispensable to follow a continuous process, including all stages from Dev to deploy with the help of auto-provisioning resources of the target platform.
  • The team always keeps an eye on major and minor application changes that can typically appear within a few hours of development to operation. However, the support of unlimited resource provisioning is needed at the stage of deployment.
  • Cloud or hybrid configuration can associate this process, but you must confirm that configuration should support multiple cloud brands like Microsoft, AWS, Google, any public and private cloud models.

Guide to Remold Business with DevOps and Cloud

Companies are now re-inventing themselves to become better at sensing the next big thing their customers need and finding ways with the Cloud based DevOps to get ahead of the competition.

#devops #devops-principles #azure-devops #devops-transformation #good-company #devops-tools #devops-top-story #devops-infrastructure

Houston  Sipes

Houston Sipes

1603177200

Measuring DevOps Metrics: A How-To Guide

DevOps is supposed to help streamline the process of taking code changes and getting them to production for users to enjoy. But what exactly does it mean for the process to be “streamlined”? One way to answer this is to start measuring metrics.

Why metrics are important to track

Metrics give us a way to make sure our quality stays the same over time because we have numbers and key identifiers to compare against. Without any metrics being measured, you don’t have a way to measure improvements or regressions. You just have to react to them as they come up.

When you know the indicators that show what condition your system is in, it lets you catch issues faster than if you don’t have a steady-state to compare to. This also helps when you get ready for system upgrades. You’ll be able to give more accurate estimates of the number of resources your systems use.

After you’ve recorded some key metrics for a while, you’ll start noticing places you could improve your application or ways you can reallocate resources to where they are needed more. Knowing the normal operating state of your system’s pipeline is crucial and it takes time to set up a monitoring tool.

The main thing is that you decide to watch some metrics to get an idea of what’s going on when you start the deploy process. In the beginning, it might seem hard to figure out what the best metrics for a pipeline are.

Figuring out which metrics are important to you

You can conduct chaos engineering experiments to test different conditions and learn more about which metrics are the most important to your system. You can look at things like, time from build to deploy, number of bugs that get caught in different phases of the pipeline, and build size.

Thinking about what you should measure can be one of the harder parts of the effectiveness of the metrics you choose. When you’re considering metrics, look at what the most important results of your pipeline are.

Do you need your app to get through the process as quickly as possible, regardless of errors? Can you figure out why that sporadic issue keeps stopping the deploy process? What’s blocking you from getting your changes to production with confidence?

That’s how you’re going to find those key metrics quickly. Running experiments and looking at common deploy problems will show you what’s important early on. This is one of the ways you can make sure that your metrics are relevant.

#devops #devops-principles #devops-tools #devops-challenges #devops-adoption-challenges #devops-adoption #continuous-deployment #continuous-integration

DevOps Basics: What You Should Know

Once an industry term becomes popular, particularly in technology, it can be difficult to get an accurate definition. Everyone assumes that the basics are common knowledge and moves on. However, if your company has been discussing DevOps, or if you are interested in learning more about it, here are some basics you should know.

What Is DevOps?

DevOps refers to the restructuring of the traditional software application cycle to support Agile development and continuous improvement/continuous delivery. Traditionally, the software was created in large-scale, monolithic bundles. New features and new releases were created in large packages and released in full-scale, infrequent, major deployments.

This structure is no longer effective in the modern business environment. Companies are under increasing pressure to be agile. They must respond rapidly to changes in the business environment to remain competitive. Software development needs to be completely changed as a process so that incremental improvements can be made frequently – ideally, several times per day.

However, changing a development lifecycle completely requires major changes – in people and culture, process, and enabling tooling – to be effective. DevOps was created by the breaking down of cycles between development and operations, combining two separate functions in application development. These changes intend to support agile, secure, continuous improvements, and frequent releases.

#devops #devops adoption #devops benefits #q& #a #devops goals #devops migration #devops questions

Loma  Baumbach

Loma Baumbach

1601120400

Using the Four Keys to measure your DevOps performance

Through six years of research, the DevOps Research and Assessment (DORA) team has identified four key metrics that indicate the performance of a software development team:

  • Deployment Frequency - How often an organization successfully releases to production
  • Lead Time for Changes - The amount of time it takes a commit to get into production
  • Change Failure Rate - The percentage of deployments causing a failure in production
  • Time to Restore Service - How long it takes an organization to recover from a failure in production

At a high level, Deployment Frequency and Lead Time for Changes measure velocity, while Change Failure Rate and Time to Restore Service measure stability. And by measuring these values, and continuously iterating to improve on them, a team can achieve significantly better business outcomes. DORA, for example, uses these metrics to identify Elite, High, Medium and Low performing teams, and finds that Elite teams are twice as likely to meet or exceed their organizational performance goals.1

Baselining your organization’s performance on these metrics is a great way to improve the efficiency and effectiveness of your own operations. But how do you get started? The journey starts with gathering data. To help you generate these metrics for your team, we created the Four Keys open source project, which automatically sets up a data ingestion pipeline from your Github or Gitlab repos through Google Cloud services and into Google DataStudio. It then aggregates your data and compiles it into a dashboard with these key metrics, which you can use to track your progress over time.

To use the Four Keys project, we’ve included a setup script in the repo to make it easy to collect data from the default sources and view your DORA metrics. For anyone interested in contributing to the project or customizing it to their own team’s use cases, we’ve outlined the three key components below: the pipeline, the metrics, and the dashboard.

The Four Keys pipeline

The Four Keys pipeline is the ETL pipeline which collects your DevOps data and transforms it into DORA metrics.

One of the challenges of gathering these DORA metrics, however, is that, for any one team (let alone all the teams in an organization), deployment, change, and incident data are usually in different disparate systems. How do we develop an open-source tool that can capture data from these different sources—as well as from sources that you may want to use in the future?

With Four Keys, our solution was to create a generalized pipeline that can be extended to process inputs from a wide variety of sources. Any tool or system that can output an HTTP request can be integrated into the Four Keys pipeline, which receives events via webhooks and ingests them into BigQuery.

Four Keys pipeline.jpg

Click to enlarge

In the Four Keys pipeline, known data sources are parsed properly into changes, incidents and deployments. For example, GitHub commits are picked up by the changes script, Cloud Build deployments fall under deployments, and GitHub issues with an ‘incident’ label are categorized as incidents. If a new data source is added and the existing querie s do not categorize it properly, the developer can recategorize it by editing the SQL script.

#google cloud platform #open source #devops & sre #devops