Другими словами, фрактальность – это похожесть части на целое, и наоборот. Очень многие объекты в живой природе фрактальны, то есть самоподобны. Фрактал Мандельброта (на картинке) — пожалуй, самый известный в широких кругах фрактал. Его назвали по имени человека, который, как считается, сделал наиболее весомый вклад в исследования принципа фрактальности. Рынки, как часть живой природы, как отражение особенностей работы человеческого мозга — тоже нелинейны и фрактальны.
Объективно, принцип фрактальности будет актуален всегда, и изучение его применения на финансовых рынках стоит потраченного времени. Человеческий мозг, в данном смысле, тоже хаотичен, его работа подчинена организующим принципам, хотя на первый взгляд может казаться беспорядочной. Рынки – это продукт человеческого мозга, и они хаотичны по своей природе. Для описания хаотичных процессов должна применятся нелинейная логика, фрактальная геометрия. Если посмотреть на биржевые графики, то они могут быть подобны многим фрактальным проявлениям, например береговой линии, волнам моря, движению реки. Если на рынке присутствует восходящий тренд, и внутри дня цена пробила верхний фрактал, выйдя из области Value area — то, скорее всего, движение вверх продолжится.
Прибыльная торговля с помощью фрактальности существует?
Окружающий нас мир — многообразный и невероятно сложный, и наблюдение за окружающей нас природой открывает перед человечеством удивительные математические закономерности. Очень много учёных черпали свои вдохновения для новых открытий из уже существующих творений в природе. Или математические открытия подтверждались явлениями в окружающем нас мире. Так, например, произошло с числами Фибоначи и фрактальностью. В своей книге “Фрактальная геометрия природы” (1982) Бенуа Мандельброт ввел термин фракталы, и создал математику для их описания.
Как следствие, там скапливается большое количество защитных ордеров и коварный рынок часто “заглядывает” туда, чтобы “вытряхнуть” трейдеров. В таких случаях еще говорят — “происходит захват ликвидности”. По классике Билла Уильямса, фракталы предлагается торговать на пробой (идея отображена на картинке ниже).
Фракталы на биржевых графиках
Рынки — это «живой» эволюционирующий организм, который описать с помощью простых формул или геометрических фигур крайне сложно. На таймфрейме М5 установите индикатор Dynamic Levels, который показывает в динамике в течение дня уровень РОС ( максимального объёма за день) и Value area (области накопления 70% объёма за день). Этот индикатор может быть хорошим фильтром для ваших сделок. Своей карьерой трейдера, и многочисленными примерами успехов последователей, Билл Уильямс подтвердил состоятельность подхода, основанного на фрактальности и подобию окружающему миру. Хотя, конечно, у каждого таймфрейма есть свои особенности, но общий характер рыночных движений сохраняется благодаря фрактальности.
Что такое фрактал простыми словами?
fractus — дроблёный, сломанный, разбитый) — множество, обладающее свойством самоподобия (объект, в точности или приближённо совпадающий с частью себя самого, то есть целое имеет ту же форму, что и одна или более частей).
Чтобы не “уйти с рынка по стоп-лоссу”, нужно торговать в гармонии с крупным игроком. Для этого требуется анализировать объемы с целью поиска тренда, который формируется важными https://g-forex.net/chto-takoe-strategiya-fraktal/ участниками рынка. Тогда придет понимание, в каком направлении, вероятнее всего, направится цена. Но важно понимать ограничения любых книг, написанных о финансовых рынках.
Фрактальность в трейдинге
Как следствие, фракталы не могут появиться на самом правом краю графика. Примеры того, какими могут быть фракталы, вы можете увидеть на картинке из книги “Торговый хаос”. Стрелками на графике показаны фракталы, которые являются экстремумами — то есть, локальными минимумами или максимумами на текущем графике. Для понимания нелинейности (фрактальности) рынка гораздо более подходят методы анализа текущего состояния рынка. Появление и развитие компьютерной техники дало толчок в применении принципа фрактальности в науке.
Это и есть принцип фрактальности на биржевых графиках — малое подобно большому, и наоборот.
Если на рынке присутствует восходящий тренд, и внутри дня цена пробила верхний фрактал, выйдя из области Value area — то, скорее всего, движение вверх продолжится.
Определите тренд (в каком направлении перемещается объём) и торгуйте в течение дня только в направлении тренда.
Рынки — это «живой» эволюционирующий организм, который описать с помощью простых формул или геометрических фигур крайне сложно.
Для описания хаотичных процессов должна применятся нелинейная логика, фрактальная геометрия.
Чтобы собрать информацию для книги, написать ее, отредактировать и издать — чаще всего необходимо несколько лет. Точного и общепринятого определения фрактала в научной среде не существует. По классической теории, трейдерам рекомендуется располагать стоп-лоссы за максимумы и минимумы на текущем графике.
Важной идеей в трудах Билла Уильямса является теория хаоса. С помощью теории хаоса ученые пытаются описать окружающий нас мир и процессы в нем происходящие. В данной теории хаос – это не синоним беспорядка, а наоборот — высшая степень порядка, в которой процессы и явления происходят не спонтанно, а подчинены организующим принципам. Но стороннему наблюдателю, не понимающему этих принципов, кажется, что процесс беспорядочный (хаотичный). Могут устареть торговые системы, начать хуже работать и запаздывать торговые индикаторы, но базовые принципы, чаще всего остаются неизменными. Поэтому при чтении любой книги по трейдингу, важно искать и осознавать именно базовые принципы, а не конкретные торговые системы или индикаторы.
Интересно, что биржевая торговля, как часть существующего мира, очень даже гармонично вписывается в теорию фракталов. Определите тренд (в каком направлении перемещается объём) и торгуйте в течение дня только в направлении тренда. Исходя из этого простого наблюдения, можно выставлять отложенные ордера на пробой фракталов в соответствии с перемещением объема. Основная проблема торговли по фракталам — это многочисленные пробои фракталов-экстремумов. С целью построения стратегии торговли, основанной на фракталах, Билл Уильямс вводит также правила сигнального и стартового фракталов.
Финансовые рынки состоят из миллионов людей, соответственно являются «живыми», постоянно изменяющимися, эволюционирующими, как и человеческое общество. Соответственно, закономерности, которые мы наблюдаем в живой природе, могут быть применены для описания и прогнозирования финансовых рынков. Это и есть принцип фрактальности на биржевых графиках — малое подобно большому, и наоборот.
Как использовать фракталы в торговле?
— Чтобы использовать фракталы наилучшим образом, их следует комбинировать с другими индикаторами на рынке Форекс или торговыми стратегиями. Трейдерам не рекомендуется полагаться только на этот индикатор. -Несколько таймфреймов всегда являются лучшим решением для построения фракталов.
Что такое Фрактальность в трейдинге?
Фракталом в трейдинге принято называть локальный экстремум, состоящий из нескольких баров. Стрелками на графике показаны фракталы, которые являются экстремумами — то есть, локальными минимумами или максимумами на текущем графике.
Since we’re using unlevered free cash flow, this section is actually not that important to the DCF model. It is, however, important if you are looking at things from the perspective of an equity investor or equity research analyst. Investment bankers typically focus on enterprise value, as it’s more relevant for M&A transactions, https://accounting-services.net/what-s-the-best-way-to-take-payment-for-my-used/ where the entire company is bought or sold. The way this section is built will depend largely on what type of DCF model you’re building. The most common approach is to simply keep the company’s current capital structure in place, assuming no major changes other than things that are known, such as debt maturity.
Overall, Walmart seems modestly undervalued because its implied share price in most of the sensitivity tables is above its current share price of ~$140. Sure, you could make it more complicated, but I would argue it’s a waste of time in a case study or modeling test unless they specifically ask for it. And Levered Beta tells you how volatile this stock is relative to the market as a whole, factoring in both business risk and risk from leverage (Debt). The problem with this approach is that you need quick DCF Model Training: 6 Steps to Building a DCF Model in Excel access to data for comparable companies, which may be tricky without Capital IQ, FactSet, or similar services. And if you are dealing with a rapidly changing company or a tech startup (e.g., Uber or Snap), it’s often more useful to get KPIs and financial stats from similar companies that were once growing quickly but have since matured. Companies grow and change over time, and often they are riskier with higher growth potential in earlier years, and then they mature and become less risky later on.
From the course: Financial Modeling Foundations
A discounted cash flow (DCF) model is a financial model used to value companies by discounting their future cash flow to the present value. In this guide, we’ll provide you with an overview of the components of a DCF model. This will serve as a reference tool for before or after our financial modeling course where we build a DCF model on public company.
This calculation gives us what is known as the enterprise value, or the value of the entire company. However, more often than not, we are more interested in the stock price than in this value. A DCF model is a specific type of financial modeling tool used to value a business. DCF stands for Discounted Cash Flow, so a DCF model is simply a forecast of a company’s unlevered free cash flow discounted back to today’s value, which is called the Net Present Value (NPV). The Discounted Cash Flow (DCF) is a valuation method that estimates today’s value of the future cash flows taking into account the time value of money. Our Discounted Cash Flow template in Excel will help you to determine the value of the investment and calculate how much it will be in the future.
Discounted Cash Flow (DCF) Analysis
This guide is quite detailed, but it stops short of all corner cases and nuances of a fully-fledged DCF model. The bad news is that we rarely have enough insight into the nature of the non-controlling interests’ operations to figure out the right multiple to use. The good news is that non-controlling interests are rarely large enough to make a significant difference in valuation (most companies don’t have any). There are several actions that could trigger this block including submitting a certain word or phrase, a SQL command or malformed data.
Part of projecting free cash flows is estimating a company’s capital expenditures for each period. Here is a demo video from our financial statement modeling course illustrating the linking of cash flows to the three statements which is one of the final steps in the process. Using one of these two methods, determine the company’s terminal value so that we can adequately discount cash flows. A company is worth more when its cash flows and/or cash flow growth rate are higher, and it’s worth less when those are lower. In this Excel tool, the Cash Flow Projection parameters calculate automatically, but you can enter any parameter value manually.
Issues with the DCF model
To accomplish this, we project cash flows for each year until the company reaches a steady state. A steady-state is when the company is growing at a constant rate, and all of its revenues and expenses are moving forward in proportion indefinitely. Once most of the income statement is in place, then it’s time to forecast the capital assets. PP&E is often the largest balance sheet item, and capital expenditures (CapEx), as well as depreciation, need to be modeled in a separate schedule.
Constant fluxes in the economy and developments within an organization would lead to increases and decreases in both these rates. When considering the cost of debt (i.e. the interest rate on debt) we need to multiply by (1-tax rate). This is because the cost of debt is tax deductible, and companies receive a tax break directly proportional to that cost.
Calculating Unlevered Free Cash Flows (FCF)
Therefore, if we had more time and resources, we might create a few operating scenarios, similar to the Uber and Snap models, to assess the results in “growth” vs. “stagnant” vs. “decline” cases. You could also estimate the Terminal Value with an EBITDA multiple based on median multiples from the comparable companies, but we don’t recommend that as the primary method. The Cost of Debt represents returns on the company’s Debt, mostly from interest, but also from the market value of the Debt changing. You could also search for industry data from companies like IDC, Gartner, and Forrester, but it’s not necessary for a quick analysis of a mature company.
Of course, the usefulness of this assessment depends heavily on how accurate its outcome is.
If the cost of equity is 8% and the cost of debt is 5%, we calculate the weighted average, 50% of 8% plus 50% of 5% to determine the WACC.
Investment bankers typically focus on enterprise value, as it’s more relevant for M&A transactions, where the entire company is bought or sold.
For example, having $20 today would be worth more than having $20 in the future.
However, this is not foolproof because growth is anything but constant over a long period. Focusing on the discount rate also presents the issue of how an analyst chooses to calculate it. While using the WACC is a common method, there are other ways to determine the discount rate, creating the complication of different analysts and firms using different ways of finding the discount rate.
DCF vs. Cash flow vs. Free cash flow
This linked nature of DCF models also introduces difficulties as analysts making assumptions for the later years have less accurate information to base off, increasing the degree of uncertainty. Since DCF models are intended to provide long-term valuations instead of short-term ones, this is a prominent drawback of the model. However, let’s suppose that the model is being created from scratch in which case, we must project it first from the balance sheet (BS) and income statement (IS), as well as the supporting schedules. This approach is often used in a cost-cutting environment or when financial controls are being imposed.
In that case, their terminal value will be calculated as $100m ($10 million / (11% – 1%)).
It’s important to pay close attention to the timing of cash flows in a DCF model, as not all the time periods are necessarily equal.
Additionally, the cash outflow (making the actual investment) is typically a spate time period before the stub is received.
We also made sure that CapEx as a percentage of revenue stays ahead of D&A as a percentage of revenue in each year because Walmart’s cash flows are growing.
GitHub has a large and active community of developers contributing to open-source projects. GitHub is the largest development platform in the world, with over 100 million developers and more than 372 million repositories. Founded in 2008 by Tom Preston-Werner, Chris Wanstrath, P. J. Hyett, and Scott Chacon, it was acquired by Microsoft for $7.5 billion in 2018. Discover the accessibility features within our new navigation and code search which make it easier to use for many more people. Explore how using GitHub and HashiCorp together enables enterprises to develop and ship to their customers faster and more secure with consistent workflows and actions. Many of us are aware of the benefits that a strong focus on automation can bring, particularly in our development workflow and DevOps lifecycle.
Notable projects and customers of GitLab include Goldman Sachs, Ticketmaster, the Cloud Native Computing Foundation (CNCF), and more. Although many adoptions of Git are available today, two hosted solutions have become widely popular with developers and businesses alike – GitHub vs GitLab. Get visibility into workflow status, duration, credit consumption, flaky tests, and costs with our Insights dashboard and enjoy more green builds faster. However, GitHub Actions provides more granular control, exposing many commands that CircleCI abstracts.
This will give you greater control over the hardware, software, and operating system than what GitHub-hosted runners will provide. It’s important to note not all the services support the same build environments. Generally, a Linux environment is enough, but sometimes, you may also need other environments like macOS or Windows to build apps. If that’s the case, you’ll be happy to know that both GitHub Actions and GitLab CI support this feature.
Overall, if speed is your primary concern and you’re on a budget, then Circle CI is the clear choice. If you’re not looking to run a ton of builds each month and your code is already in Github, then Github Actions can offer similar performance with the added convenience of having everything under one service. As you can see, Jenkins is a relatively mature product and is quite capable of providing great functionality for teams looking to implement a CI/CD pipeline smoothly. The platform has several issues that may prove significant enough for your team to turn elsewhere for CI/CD automation.
Teams that want confidence in every commit choose CircleCI over GitHub Actions
Enabling continuous testing in GitHub Actions works much the same way as in CircleCI, except that a prebuilt container is often used for testing purposes instead of an orb. In CircleCI, you can add continuous testing into a pipeline as a series of steps within a job. Alternatively, as with Sauce Labs, you can use an orb from the CircleCI library that will handle most of the heavy lifting, and the test suite can be run in a single step.
CircleCI and GitHub Actions offer three main delivery options—self-hosting on-premises, Software as a Service (SaaS), or a hybrid option. Choosing the SaaS option means the repository must have continuous access to the platform so it can retrieve the application’s source code. CircleCI works with private or public repositories stored on Bitbucket or GitHub. However, GitHub Actions works with repositories stored on GitHub only. Organizations can use the platform’s integrated suite of SCM, CI, CD and CS&C features to reduce costs and deliver better software faster. It comes as no surprise that Atlassian, the company behind popular software development tools such as Bitbucket, Jira, Trello, and Opsgenie, also provides CI/CD capabilities.
When programmers use CircleCI, they’ll likely discover that the platform provides the parameters to form an operation and the orb can handle the rest. Contrastingly, GitHub Actions requires more input and specifically requires the Docker commands. CircleCI’s design could be considered cleaner and simpler, while GitHub Actions offers more granular control by exposing commands that CircleCI keeps behind the curtain. Earlier this year, we at Earthly embarked on a journey to bring better builds to the world. As creators of a new approach to build automation, we have always strived to create products that we ourselves would have wished we had.
Nira currently works with Google Workplace with more integrations coming in the near future.
Customers include companies of all sizes from hundreds to thousands of employees.
An immense array of turnkey Actions coupled with the ease of configuration and maintenance offered by the standard Git flow make it a significant step forward for CI/CD automation practices.
It can also execute arbitrary code in the specified repository when an event occurs, and package code in Docker containers running on GitHub servers.
Developers relying on the CIRCLE_PULL_REQUEST env var for certain scripts might run into issues. You can enable “Build Pull Requests Only” in the project’s advanced settings. Auto DevOps provides a predefined CI/CD configuration that helps you automatically detect, build, test, deploy, and monitor applications. It can be a big time saver because you don’t have to write all the YAML files from scratch. Continuous Integration (CI) and Continuous Delivery (CD) pipelines automate tasks of building, testing, and deploying changes to the application. GitLab offers GitLab Web IDE, a development environment that enables
users to edit, review, and merge files.
What is the difference between Harness CI Vs. GitHub Actions?
In addition, GitHub Actions has a marketplace with a large selection of actions, while CircleCI offers a smaller selection. [1] Storage refers to the amount of data you can store on GitLab, including code, files, and images. [2] Transfer refers to the amount of data that can be transferred to and from GitLab each month. GitLab provides a unified toolchain that allows teams to iterate quickly and innovate together, minimizing complexity and risk. GitHub offers more storage, more CI/CD minutes per month, and lets you work with the unlimited number of contributors. It currently has 30 million users and its long-term goal is to become the default choice for
DevSecOps value stream platforms in the enterprise market.
Because both GitLab and GitHub implement a Git server, if Git is the right solution for your team or organization then either vendor can be expected to be a good fit. GitHub Actions and CircleCI provide reusable, simplified commands that ensure pipelines can extract predefined, common processes. This feature is called actions in GitHub Actions and orbs in CircleCI.
GitHub vs. GitLab: Key Similarities and Differences – ITPro Today
GitHub vs. GitLab: Key Similarities and Differences.
Running my app in a production (or production-like) environment was already a solved problem, because everything was already in some form of “everything as code”. Having a test environment where the only difference was adding the Buildkite agent was a trivial addition. GitHub Actions is the CI/CD functionality within the GitHub platform. GitHub’s platform is the most widely used Git platform on the planet, and it has extensive functionality beyond just Actions – including defect and project tracking, image repositories, and analytics. Both systems enable you to include additional containers for databases, caching, or other dependencies.
GitLab CI/CD syntax for jobs
With SSH access, programmers will find it easy to debug issues with nonpresent commands or files in unexpected directories. Public repository users will have free and unlimited compute times on GitHub Actions. However, private repository users of GitHub Action’s free tier are limited to 2,000 minutes of compute time per month. We live in an era of continuous delivery, containers, automation, rich set of programming languages, varying code structures (mono/poly-repos) and open-sour… Remember, we only looked at the free tiers offered by these services. Also, each service scales differently so even though you may like the convenience of Github Actions, you may find that Travis CI becomes more cost-effective as you run larger and more complicated pipelines.
For example, see the documentation about integrations with Sauce Labs. GitLab CI/CD extends the GitLab platform to allow developers to run continuous integration and delivery pipelines against their code repositories. Much like GitHub, GitLab offers a full suite of functionality that developers can leverage throughout their development cycles. When teams compare the two platforms, they’ll find that GitHub Actions is more cost-effective for users of public repositories. However, CircleCI can offer a better deal for projects with private repositories.
Best of all, nearly every page of the docs included code examples, usually entire example files. When running using GitLab CI/CD you need to set the credentials/secrets
and update the script .gitlab-ci.yml directory, which is executed when code is commited/pushed. While GitHub Actions is not limited to GitHub SCM it is indeed finely tuned to it so, the experience of using GitHub Actions with any other source code management provider will differ considerably.
When running using GitHub Actions you need to set the credentials/secrets
and add a script under the .github/workflows/ directory, which is executed when the code is commited/pushed. It’s described as an “extensible automation server”—mainly used to power continuous integration and delivery processes behind the scenes. gitlab ci cd vs github actions Jenkins boasts a self-contained design allowing it to be deployed in many different operating system environments, and it’s highly extensible. GitHub was the first Cloud-hosted Git solution, launching in 2008 and setting the standard for such solutions; one notable exception being SourceForge which was founded in 1999.
Although many adoptions of Git are available today, two hosted solutions have become widely popular with developers and businesses alike – GitHub vs GitLab.
Gogs is an open-source Git server written in Golang and designed to be a simple and stable way to self-host a Git service (ironically the project is hosted on GitHub).
Keep in mind that predicting the pricing for GitHub Actions can be a hassle, especially because it varies quite a bit depending on the commits to the project.
We live in an era of continuous delivery, containers, automation, rich set of programming languages, varying code structures (mono/poly-repos) and open-sour…
While GitHub Actions supports Linux, Windows Server, and macOS, GitLab CI supports Linux and the beta versions of macOS and Windows Server.
In addition, GitHub Actions can be used to trigger other actions in response to specific events, such as when a code change is pushed to a remote repository. In today’s fast-paced world, being able to deploy applications quickly is essential for success. However, setting up a CI/CD pipeline can be a tedious and time-consuming task. Fortunately, GitHub Actions can help simplify and automate your workflow, making it easier than ever to get your applications up and running in no time. In this blog post, we’ll take a look at how to set up a React application with GitHub Actions and explore the benefits of using this tool for your CI/CD needs.
As Cloud-focused services, including GitHub, gained in popularity, more businesses moved to adopt the model and looked to leaders such as GitHub for support. Taking a more self-managed approach, the GitHub platform supports a wide range of community-developed solutions to provide for the DevOps lifecycle. It’s built on Argo for declarative continuous delivery, making modern software delivery possible at enterprise scale. This orb tells CircleCI to build a Docker image and push it automatically to the desired ECR repository.
Usually, you would use the clone step to get access to your GH repository. Since we have not provided the required Account token in the variables, the workflow will not run. Note that this test command ran against my staging policy set up in Datree.
GitLab offers GitLab Tabnine, an AI-powered code completion technology
that integrates with GitLab repositories. GitHub offers GitHub Copilot, an AI-powered pair programming tool that
speeds up the coding process. How to verifiably link npm packages to their source repository and build instructions.
This can free up time for other tasks, such as writing documentation or working on other features. All four tools integrate tightly with their respective hosting platforms. GitLab CI also provides integration with third party tools, such as Kubernetes and AWS, making it a great choice for organizations using these technologies. When building pipelines, you typically want to run as many things as possible in parallel. If the CI system only supports fan in/out, all jobs in a given “stage” need to complete for the next batch of jobs to run.
Best Software Tools for GitHub Secrets Detection – Analytics Insight
There is no “one size fits all” tool, so consider what best suits your project (and organization) needs. Ultimately, the real goal of any tool you implement is to empower your teams to deliver great quality software. The “Actions” feature from Microsoft-owned GitHub was initially announced in 2019 and became generally available in 2020. As a long-time home for many open-source and commercial projects, there https://traderoom.info/ was a natural interest in taking advantage of GitHub’s CI/CD capabilities. In this article, we’ll help you navigate seven of the most popular CI/CD tools currently available so you can make the best decision for your development teams. The major public cloud providers are also increasing their CI/CD capabilities, making it worthwhile to watch Microsoft Azure DevOps, AWS CodeStar, and Google Cloud Build.
As a result, a lot of the tutorials and documentation are written for users who are hosting their own GitLab runners. It took a little more digging and some outside sources to get started without having to host our own runner. Getting set up and running with Circle Ci’s free tier was pretty straightforward.
What is the difference between GitLab CI CD and GitHub action?
Both GitLab CI/CD and GitHub Actions allow you to run workflows at a specific interval. In GitLab CI/CD, pipeline schedules are configured with the UI, while in GitHub Actions you can trigger a workflow on a scheduled interval with the ‘on’ key. For more information, see ‘Events that trigger workflows.’
Any of the tools discussed here will enable you to implement a working CI/CD pipeline, but the effort and operational overhead varies. When drawing comparisons between them, it’s important to consider your current status quo. Ask yourself what your team’s strengths and blind spots are when it comes to developing pipelines as code and organization policies (e.g., SaaS versus self-hosted). Both services offer modern capabilities, such as container and multi-platform support. The Jenkins agent can be installed in different types of machines (physical, virtual, containers) and runs on top of different OSs (Windows, Linux, OSX).
For example, programmers in GitHub Actions can create multiple YAML files; a team may split up the files based on the environment for which a team has tested and built an application. This feature can help developers create a cleaner design for applications that use a different build process for a development and production environment. GitHub Actions is a continuous integration/continuous delivery (CI/CD) platform that lets you automate build, test, and deployment pipelines. It can also execute arbitrary code in the specified repository when an event occurs, and package code in Docker containers running on GitHub servers. It is compatible with any programming language and can run both on local servers and public clouds. A team that opts for the paid tier of CircleCI will benefit from larger compute instance sizes and more credits per month.
Is GitHub action a CI CD?
At its core, GitHub Actions is designed to help simplify workflows with flexible automation and offer easy-to-use CI/CD capabilities built by developers for developers.
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