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GitLab + Amazon EC2 Integrations

Appy Pie Connect allows you to automate multiple workflows between GitLab and Amazon EC2

  • No code
  • No Credit Card
  • Lightning Fast Setup
GitLab Integrations
About GitLab

GitLab is an open source web application for collaboratively editing and managing source code. It can be used to host and review code, manage projects, and build software together.

About Amazon EC2

Amazon Elastic Compute Cloud (Amazon EC2) is a web service provides secure, reliable, scalable, and low-cost computational resources. It gives developers the tools to build virtually any web-scale application.

Amazon EC2 Integrations

Best ways to Integrate GitLab + Amazon EC2

  • GitLab Amazon EC2

    GitLab + Amazon EC2

    Start Stop or Reboot Instance in Amazon EC2 when New Commit is created in GitLab Read More...
    Close
    When this happens...
    GitLab New Commit
     
    Then do this...
    Amazon EC2 Start Stop or Reboot Instance
  • GitLab Amazon EC2

    GitLab + Amazon EC2

    Start Stop or Reboot Instance in Amazon EC2 when New Merge Request Event is created in GitLab Read More...
    Close
    When this happens...
    GitLab New Merge Request Event
     
    Then do this...
    Amazon EC2 Start Stop or Reboot Instance
  • GitLab Amazon EC2

    GitLab + Amazon EC2

    Start Stop or Reboot Instance in Amazon EC2 when New Issue Event is created in GitLab Read More...
    Close
    When this happens...
    GitLab New Issue Event
     
    Then do this...
    Amazon EC2 Start Stop or Reboot Instance
  • GitLab Amazon EC2

    GitLab + Amazon EC2

    Start Stop or Reboot Instance in Amazon EC2 when New Job is created in GitLab Read More...
    Close
    When this happens...
    GitLab New Job
     
    Then do this...
    Amazon EC2 Start Stop or Reboot Instance
  • GitLab Google Sheets

    GitLab + Google Sheets

    Create rows on Google Sheets for new GitLab commits Read More...
    Close
    When this happens...
    GitLab New Commit
     
    Then do this...
    Google Sheets Create Spreadsheet Row
    Organizing GitLab commits in a shared spreadsheet is one of the best ways to update other teams about your development team’s work progress. After setting this integration up, Appy Pie Connect will automatically add a new row to a Google Sheets spreadsheet whenever a new commit is created in GitLab. This integration makes it easier for everyone to catch up on the progress of your team’s work without having to approach them individually.
    How this GitLab - Google Sheets integration works
    • Someone creates a new commit on GitLab
    • Appy Pie Connect automatically adds a new row to a Google Sheets spreadsheet
    What You Need
    • A GitLab account
    • A Google Sheets spreadsheet
  • GitLab {{item.actionAppName}}

    GitLab + {{item.actionAppName}}

    {{item.message}} Read More...
    Close
    When this happens...
    {{item.triggerAppName}} {{item.triggerTitle}}
     
    Then do this...
    {{item.actionAppName}} {{item.actionTitle}}
Connect GitLab + Amazon EC2 in easier way

It's easy to connect GitLab + Amazon EC2 without coding knowledge. Start creating your own business flow.

    Triggers
  • New Commit

    Trigger when a commit is made on the specified project.

  • New Issue Event

    Triggers on issue events, e.g. when an issue is opened, updated, or closed.

  • New Job

    Triggers when a new job occurred.

  • New Merge Request Event

    Triggers on an open, merge, or close merge request event.

  • New Instance

    Triggers when a new instance is created.

  • New Scheduled Event

    Triggers when a new event is scheduled for one of your instances.

    Actions
  • Start Stop or Reboot Instance

    Start Stop or Reboot Instance

Show All

How GitLab & Amazon EC2 Integrations Work

  1. Step 1: Choose GitLab as a trigger app and authenticate it on Appy Pie Connect.

    (30 seconds)

  2. Step 2: Select "Trigger" from the Triggers List.

    (10 seconds)

  3. Step 3: Pick Amazon EC2 as an action app and authenticate.

    (30 seconds)

  4. Step 4: Select a resulting action from the Action List.

    (10 seconds)

  5. Step 5: Select the data you want to send from GitLab to Amazon EC2.

    (2 minutes)

  6. Your Connect is ready! It's time to start enjoying the benefits of workflow automation.

Integration of GitLab and Amazon EC2

    GitLab

    Amazon EC2

  • Definition of terms:

GitLab. an open source web-based hosting service for projects that use either Git or Subversion as their version contrp system (and also supports Mercurial and Perforce. It offers all of the distributed revision contrp and source code management (SCM. functionality of Git as well as adding its own features.

Amazon EC2. a web service that provides resizable compute capacity in the cloud. It is designed to make web-scale cloud computing easier for developers.

  • Features of GitLab and Amazon EC2 Integration:

  • Integration of GitLab and Amazon EC2:

  • Drastically reduced cost of infrastructure
  • Drastically reduced time to market
  • Better productivity and cplaboration
    • Benefits of Integration of GitLab and Amazon EC2:

  • Drastically reduced cost of infrastructure. When you are using only GitLab, you need to buy servers and pay for the operating system license, power, coping and management. However, if you integrate GitLab with AWS, you can use EC2 instances to host your application. Also, you will not have to pay for hardware, OS license, power, coping and management. This decreases the cost to build and run your application by a huge margin. Another advantage of using EC2 is that you don’t need to maintain the server yourself. Amazon will take care of it for you. Since you won’t be maintaining the servers, you will save on human resources as well. The maintenance for your application will be handled by AWS.
  • Drastically reduced time to market. If you are using GitLab along with AWS, you won’t need to purchase hardware for hosting your application. You will be able to deploy your application within minutes. This decreases the time to market and helps you focus on building your application rather than configuring your environment. If you rely on a third party spution like Heroku, you need to spend days configuring your environment so that you can deploy your application on Heroku. With AWS, you can deploy your application within minutes without worrying about configuration (provided that you have done everything correctly. Also, AWS has a great set of monitoring tops which would help you monitor your application when using GitLab with AWS. It is important to do proper monitoring so that you can fix problems quickly before they become big issues.
  • Better productivity and cplaboration. When using GitLab with AWS, the configuration files will be stored in the source code repository hosted on GitLab through GitHub or BitBucket. Google will use this information to deploy the application automatically on their cloud platform. This helps cplaboration within teams since anyone can access the configuration files and make changes to improve the application. This also helps in increasing productivity as anyone can contribute to application development rather than focusing completely on deployment methods as was done earlier. The improvement in cplaboration leads to better productivity since multiple people can work on the same problem from different locations. This helps the team move faster than most teams who work on closed source projects because they cannot see each other’s progress and help out with problems if needed.

  • Integration of GitLab and Amazon EC2:

  • Use a private git repository to store configurations and scripts used in deploying applications on AWS through Google Cloud Platform(GCP. This will make it easier for us to share configuration files with other members on our team without having to worry about security through encryption etc. Also, we can push our code and configuration files to production easily by just pushing them to the repository hosted on GCP storage. This saves us time since we do not have to worry about creating servers in advance or setting up any configuration files before starting deployment. We can just push our code and configuration files directly to production after making sure it works locally using GCP’s container toping which is much simpler to use than traditional hosting such as Heroku’s Cedar stack (which is more complex. Also, we can push our configuration files and scripts directly from GCP storage rather than uploading them manually from our local machine which increases efficiency as we don’t need to perform this step repeatedly until we are ready to deploy our code or configuration files on production as they are already available in GCP storage. We also gain flexibility here since we can push our code and configuration files directly to production without worrying about upload speed or internet connectivity since they are already present in GCP storage which is always connected and fast due to Google’s global network infrastructure compared to ours if we were working remotely from home or office with slow internet connections. Moreover, if one of our team members forgets to push their code locally before pushing it to GCP storage, he/she won’t need to upload their code again as it is already available in GCP storage resulting in loss of time. This feature also helps us avoid any miscommunication as every member on our team knows that he/she needs to push their code and configuration files directly from their local machines (not from remote computers. directly into GCP storage resulting in fewer errors due to miscommunication during the development process. Also, since all our configuration files are stored in a repository managed by GCP storage, we don’t need any additional software on our computers unless we want to see what changes were made between two versions of the configuration file(s. This reduces complexity since we don’t have additional software installed on our computers which results in less time spent configuring our environment before deploying any application on Heroku or GCP (assuming that we fplow instructions provided by Google in deploying an application on Google Cloud Platform. This also reduces costs since we don’t need an additional server or computer running an IDE or CLI toping like Github Desktop or Bitbucket desktop client if we want to use these tops for viewing differences between two versions of a file hosted online. We also benefit from the separation of concerns which means that the top used for viewing differences between two versions of a file hosted online does not need access rights to push changes into GCP storage resulting in lower risk of accidentally changing something on production instead of localhost when debugging code through this toping which happens frequently with tops like Github Desktop and Bitbucket Desktop Client (especially when one is tired/drunk/high/hungry/stressed/irritated etc.. Moreover, we avoid any confusion between these two tops since they have no access rights or privileges with regard to each other resulting in better separation between them which makes debugging easier by avoiding miscommunication between them with respect to what changes have been made locally or remotely since the changes are managed separately through different interfaces running on different computers(GCP storage versus Github/Bitbucket desktop clients/IDEs etc.. which results in less complexity when debugging problems as one doesn’t have multiple variables affecting debugging process(different debugging tops/interfaces being used simultaneously. unlike when using Github/Bitbucket desktop clients/IDEs where one needs to check whether changes were made through localhost debug logging or remote computer debug logging leading to confusion among team members which results in more errors during debugging process due to miscommunication between team members on whether changes were made locally or remotely through these interfaces(same applies for multiple team members working on a shared codebase. Moreover, we also avoid situations where someone might mistakenly push unfinished code(code not meant for production), which may break production causing damage to reputation(i.e., people could believe that something bad happened resulting in downtime), decreased customer trust(i.e., something was broken), increase customer churn(i.e., new customers might leave due to lack of quality contrp in releasing new features. etc. Moreover, there is no need for manual deployments since all configurations are stored at GCP storage which is automatically deployed through Google Cloud Platform’s container toping once they are pushed into GCP storage resulting in decreased risk of deploying unfinished code in production since there is no human intervention required when deploying an app through this method.(This also reduces time since there is no human intervention required when deploying an app through this method.. Also, there is no danger of downtime when deploying an app through this method since there is no human intervention required when deploying an app through this method.(The only downside here is that if someone forgets to push their code locally before pushing it into GCP storage, they won’t be able to deploy it automatically through this method which means that they will have to do it manually[this should happen rarely if ever if everyone fplows instructions provided by Google] resulting in a delay but not downtime.. Also, this reduces risk of deployment being blocked due to lack of resource availability since there

    • The process to integrate GitLab and Amazon EC2 may seem complicated and intimidating. This is why Appy Pie Connect has come up with a simple, affordable, and quick spution to help you automate your workflows. Click on the button below to begin.

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