Changelogs | Brainboard

Stay up to date with our product development by checking out our public roadmap changelog. We regularly ship new features and integrations, so be sure to check in weekly, monthly or quarterly to see what's new and how it can benefit you and your business.

Brainboard Feature Changelog - Week #4 - January 2023

We're excited to share with you the latest updates and improvements to our platform. Here's a summary of what we've been working on this week:

🐞 FIXED

We've resolved reported issues that were causing occasional crashes when, for example:
Pull Request by Brainboard
  1. Specify a different brand when doing a pull request:
    • We now allow you to specify a different branch in the base branch field in the pull request modal, when creating a pull request. This means that you are able to select which branch they want to merge their changes into, rather than being restricted to a specific branch such as “main”. This feature can be useful for organizations that use multiple branches for development and testing, as it allows developers to easily collaborate on code changes and merge them into the appropriate branch for deployment. Additionally, it can help to maintain the versioning and history of the Terraform codebase.
  2. GCP VPC and Subnet: 
    • They were not containers*. Now, they are… 
    • Containers* in the cloud refers to the use of containerization technology to deploy and manage applications in a cloud computing environment. Containers are a lightweight and portable way to package and deploy applications, and they can be run on a variety of platforms, including Google Cloud. Containers are isolated from one another, which helps to increase security and reduce the chances of conflicts between different applications. 
    • Google Cloud offers a service called Google Kubernetes Engine (GKE) which allows you to easily deploy, scale, and manage containerized applications on the cloud.
    • Google Compute Network (GCN) is a virtual network that allows you to create and manage a network topology for your Google Cloud resources. It allows you to create subnets, firewall rules, and routes to control how your resources communicate with each other and with the internet.
    • Google Compute Subnetwork (GCSN) is a subnet within a GCN that allows you to segment your network into smaller, more manageable pieces. It also enables you to control the IP ranges for resources in a subnet, and apply firewall rules and routes to specific subnets.
  3. Variable type not saved:
    • Problem: This bug fix addresses an issue where a new variable is not correctly saving the type information during the creation or modification process. This can cause problems with the functionality of the application, as the type of variable is important for determining how the application should handle and interact with the variable's value.
    • Solution: The fix involves updating the Terraform code that is responsible for handling the creation and modification of variables to properly save the type information. This could involve checking for missing or incorrect type information, and adding code to handle this properly. Additionally, it also involves testing the updated Terraform code to ensure that the bug is resolved and that the new variables are being created and modified correctly with the correct type information. 
  4. Custom group TF file broken:
    • Problem: The bug fix addresses an issue with the functionality that retrieves custom group files in Terraform. The bug is related to the fact that when a group starts with 'f' or 't' the retrieval of the custom group file is broken. The issue with the Terraform configuration for the “test” group, as the test.tf file should contain the necessary information for provisioning and managing the infrastructure for that group, but it is empty. 
    • Solution: Create an architecture or a blueprint of the infrastructure using Terraform. Add 3–4 nodes on the design canvas, which are servers or machines that make up the cloud infrastructure. Change the group of 2 of the nodes to “test” group. Now, retrieve the test.tf file, which should contain the Terraform configuration for the “test” group.
  5. Scroll through a big output:
    • Problem: The bug fix addresses an issue with the performance of scrolling through the output of the “plan” in Terraform. The bug is causing the scrolling to be slow and unresponsive, with a delay of 2–3 seconds before the update or the next lines are displayed.
    • Solution: We optimized the code that handles the output display and scrolling by reducing the number of updates and unnecessary calculations. We always make sure the data is being loaded and processed efficiently.
  6. Import Multiple strings:
    • Problem: The bug fix addresses an issue with the way Brainboard import Terraform code that contains "<<EOF" and "EOF" for a field. The bug causes these characters to be changed into strings which causes issues in the interpretation of the code.
    • Solution: Update the import code to properly handle these characters. We make sure the code that reads and interpret the imported Terraform code is able to handle these characters correctly.
  7. Feedback survey:
    • Problem: We noticed that the feedback form brought aggressive prompts to you, builders and cloud architects. 
    • Solution: We've disabled it for now. Please continue to contribute to the Slack community and contact us if any improvements need to be fixed. We generally respond within 6h. 
  8. Editing node title:
    Cloud Architecture Design canvas by Brainboard
    • Problem: The bug fixes you addresses an issue with the way the editing of the title of a node behaves in Brainboard's canvas. The bug causes the title of the selected node to change when editing the title of a different node that is not selected.
    • Solution: We added a check to verify that the correct node is being edited, or by making sure the system is keeping track of the correct selected node.
We apologize for any inconvenience this may have caused, and thank you for bringing it to our attention.
Please note that the above issues have been fixed in the latest version of Brainboard and should no longer occur. If you continue to experience any issues, please reach out to our support team on our Public Slack Channel.

🧼 IMPROVED

We've made some performance enhancements to the:


  1. CI/CD Engine: We've just introduced a feature for approval tasks, which allows users to request and receive approval before deploying code changes to a production environment. This can be useful for ensuring that code changes have been reviewed and tested properly before they are deployed to a live environment, and can help to prevent errors or issues that could negatively impact the performance or functionality of the system.
  2. Import: We continue to improve the import feature. This week, we've focused on database use case. Now, you can import schema and documentation. A schema is the structure of the database and the rules on how the data should be organized, while a document is a single unit of data stored within the database.
  3. Deleting cloud architectures: When soft-deleting cloud architectures, we now soft delete all related objects including workflow(s), pipelines, jobs, deployments, git integrations, and terraform settings.
This should result in faster load times and a smoother user experience.

As always, we value your feedback and suggestions. If you have any thoughts or ideas on how we can improve Brainboard, please don't hesitate to reach out to our support team.

📆 Replay: Understand CI/CD strategies & Best Practices 


You can now watch last Tuesday's webinar on the details and implications of what CI/CD means for the cloud infrastructure. This is a short preview of what you will learn in less than 70 minutes: 
🐞 Fixed
7 days ago

Brainboard Feature Changelog - Week #3 - January 2023

We're excited to share with you the latest updates and improvements to our platform. Here's a summary of what we've been working on this week:

🐞 FIXED

We've resolved reported issues that were causing occasional crashes when, for example:

Modules' catalog in Brainboard.


  1. Storage Container already exists issue:
    • Problem: When creating a new Storage Container in Brainboard, if the container already exists in AWS or Azure, the application would fail.
    • Solution: We have implemented a check that verifies if the container already exists in the specified cloud provider before attempting to create it. If the container already exists, Brainboard will no longer fail and will instead display a message indicating that the container already exists.
  2. Git Personal Token Editing Error:
    • Problem: When editing only one field in the Git Personal Token, an error occurred and the changes were not saved.
    • Solution: We have identified the problem and fixed the issue with the Git Personal Token editing process. Users should now be able to edit any field in the token without encountering errors.
  3. Terraform Block Removal:
    • Problem: When importing Terraform files, such as backend.tf that contains a Terraform block and many providers block, the Terraform block was automatically removed.
    • Solution: We have identified the problem and fixed the issue with the Terraform block removal during import. The Terraform block should now be retained and not removed during the import process.
  4. Map variable syntax issue:
    • Problem: When importing a Terraform file that contains a map as the type of variable and the values are defined in terraform.tfvars, the values were changed and replaced with an invalid Terraform syntax, causing the plan to fail,
    • Solution: We have identified the problem and fixed the issue with the map variable syntax. The values should now be imported correctly and retain their original syntax.
  5. Validation Block Import:
    • Problem: When importing from Git or files, for example, a Terraform code that contains a validation block, the variables validation block was not imported in Brainboard.
    • Solution: We have identified the problem and fixed the issue with the validation block import. The variables validation block should now be imported correctly and be visible in Brainboard.
  6. Terraform Variables Modal:
    • Problem: The Terraform variable modal was changing every time it was opened or when doing a pull request. This caused confusion and made it difficult to track changes.
    • Solution: We have made changes to the Terraform variable modal, so it will no longer change every time it is opened or when doing a pull request. This will make it easier to track changes and manage variables.
  7. Default Terraform Code File:
    • Problem: The default Terraform code file was main.tf, but it was causing confusion when working on a different resource file.
    • Solution: We have changed the default Terraform code file to be the resource file that the user is currently working on. This will make it easier to manage multiple resource files and keep track of changes.
We apologize for any inconvenience this may have caused, and thank you for bringing it to our attention.
Please note that the above issues have been fixed in the latest version of Brainboard and should no longer occur. If you continue to experience any issues, please reach out to our support team on our Public Slack Channel.

🧼 IMPROVED

  1. Terraform Code Generation: We have made significant improvements to its Terraform code automatic generation process, making it 2x faster and more reliable. By optimizing the code generation algorithms, Brainboard has made it possible to generate Terraform code from diagrams in a fraction of the time it used to take. Additionally, the code generated is more reliable and maintainable for the long term. The generated code is now more readable and easier to understand, making it simple to read changes and updates. The new generation process also includes a new error checking feature, which identifies and corrects errors before the code is generated, ensuring that the generated code is error-free. Overall, these improvements make Brainboard's Terraform code generation process one of the best in the industry, providing users with a fast, reliable, and maintainable solution.
  2. CI/CD Plugins: We have added more available arguments and options for CI/CD plugins. This will give users more flexibility and control when integrating with their CI/CD pipeline.
This should result in faster load times and a smoother user experience.

As always, we value your feedback and suggestions. If you have any thoughts or ideas on how we can improve Brainboard, please don't hesitate to reach out to our support team.

📆 Thursday, January 24th, 2022



Don't forget our live webinar on the details and implications of what CI/CD means for the cloud infrastructure:
  • The current state of CI/CD solutions and how they work
  • The challenges associated with it and how they impact your process
  • What are the best practices that apply to the infrastructure automation
  • What changes are needed to have a successful implementation
  • The most important part: what is expected from a CI/CD solution that is cloud infrastructure specific
🐞 Fixed
13 days ago

🔥 Id card is constantly improving

The ID card in Brainboard is a feature that enables users to easily configure cloud resources by dragging and dropping them onto the design canvas. These resources are not just visual representations but are actual, actionable resources that can be configured and deployed to the cloud. One step forward in breaking down the barriers between low-code and code-based approaches to cloud infrastructure management.

With the ID card, Brainboard is pushing the boundaries of visualizing cloud infrastructure to help you understand the bigger picture of your projects, environments, cloud architecture, and workflows. This makes it easier for users to manage your cloud resources and have a clear infrastructure overview. This can also help users to identify patterns, dependencies, and potential issues, making it easier to optimize your infrastructure.

Here at Brainboard, we constantly spot errors and improvements and focus on tackling them first. 
  • One of the improvements is that it eliminates missing fields when configuring specific cloud resources. You no longer have to worry about missing important information when setting up your cloud infrastructure. 
  • The ID card allows for multi-block everywhere, allowing for better customization options. This can be achieved by using hardcode, a powerful tool for making changes to the infrastructure. 

Overall, these improvements make it easier for you to configure and manage your cloud resources with Brainboard.
🐞 Fixed
20 days ago

↕ Connect multiple resources directly from the idcard

Use an attribute of a resource in the id card of another resource and connect resources — one step further to low coding your cloud infrastructures.

In Brainboard, you can connect multiple resources by using resource references. This can be done in several ways:
  1. Using the "depends_on" argument in resource blocks allows you to specify that a resource depends on another resource and must be created after it.
  2. Using the "${resource.name.attribute}" syntax allows you to reference the attributes of one resource in the configuration of another resource.
  3. Using the "data" blocks to retrieve information from external resources allows you to retrieve information from existing resources and use it to configure new resources.
  4. Terraform modules allow you to group resources and reuse them across multiple configurations. This is a way to organize your resources and share them with others.
  5. Using Terraform's variables: Terraform variables can store resource information and reference it in multiple places in your configuration.

It's important to note that connecting multiple resources depends on the resources themselves and the cloud provider you are using. It is recommended to check the resources and provider documentation to get the best practices.

🔎 ID card* search now returns nested fields (inside block)

Improvement to the ID card search functionality in a system. Specifically, the improvement allows for searching nested fields within an ID card.
*The ID cards would represent different cloud resources, such as virtual machines, load balancers, and storage volumes. By dragging and dropping these ID cards onto a canvas, users could quickly and easily design their desired cloud infrastructure.

Once the diagram is designed, it would also be actionable, meaning that the user could deploy their cloud infrastructure with a single click. Brainboard would then automatically provision and configure the necessary resources based on the ID cards that were used in the design.

Brainboard greatly simplify the process of designing and deploying cloud infrastructure, as it would provide users with a visual, intuitive way to work with the resources. Additionally, the use of ID cards could also enable users to easily share and reuse their cloud infrastructure designs with others.

Before

The previous version of the ID card search only returned the matches from the simple fields, but now the search has been updated to return matches even from the nested/block fields, which allows the user to find the ID card with all the information they need.

Test it for yourself on Brainboard!

📥 Import modules, revamped!

Now, we manage better import modules. We continue to support public and private repo as usual.
Don't hesitate to report a bug or share your honest feedback with the team [email protected]

There are several benefits to working with Terraform modules:

  1. Reusability: Modules allow you to group resources and reuse them across multiple configurations. This can significantly reduce the code you need to write and maintain.
  2. Organization: Modules provide a way to organize your resources and make your Terraform configurations more readable and maintainable.
  3. Versioning: Modules can be versioned, which allows you to track changes and roll back to a specific version if needed.
  4. Collaboration: Modules can be shared and used as a building block for other people's configurations. This allows for better collaboration within a team or community.
  5. Abstracting complexity: Modules can help abstract away complexity by breaking down large configurations into smaller, more manageable pieces.
  6. Better testing: By using modules, you can quickly test a specific part of your infrastructure without affecting other parts.
  7. Scalability: Modules can help to scale your infrastructure more efficiently. They can be used to create reusable and composable infrastructure patterns which can be used across different environments.
  8. Simplifying the management: Modules help to simplify the management of infrastructure by breaking down complex infrastructure into smaller, more manageable components.

It's essential to keep in mind that modules should be designed with a clear purpose and with the ability to be easily reused. This can help you to create a library of modules that can be quickly composed to create complex infrastructure.

Import your Terraform modules on Brainboard.

Import modules

🔥 See template details when tags are defined

No more. Your experience with the Templates catalog continue to improve since the launch of the new UI.
Don't hesitate to report a bug or share your honest feedback with the team [email protected] 

Discover the new templates' catalog on Brainboard.
🐞 Fixed
4 months ago

🐞 W38 Updates

This week, we are pleased to announce the release of several updates for our Brainboard cloud management solution. These updates address a number of issues that have been brought to our attention by our valued customers.
  • The location/Region field has been fixed to ensure that it accurately reflects the real value.
  • We have fixed an issue where variables locals were not retained during the cloning process.
  • The reminder form has been fixed to ensure proper functionality.
  • The custom code field is now fully usable, as it was previously causing issues.
  • The architecture cloning process now also retains locals values.
  • We have resolved an issue where the deletion of modules from the catalog was not working as expected.
We are committed to constantly improving our product, and we are grateful for the feedback we receive from our customers.

Furthermore, we strive to provide the best possible experience for our users and we will continue to work on addressing any issues that arise. Thank you for choosing Brainboard for your cloud management needs.

Discover Brainboard today.
🐞 Fixed
5 months ago

🐞 W34 Updates

The following bugs were fixed: 
  • Fixed: When I delete my current architecture, the interface freezes / infinite loop with error in console
  • Fixed: When I add an Azure virtual network for e.g. and I remove a chip from tags, the interface resets, the code generated is completely broken and I have no way to open the resource again to fix it.
  • Fixed: We can’t change the selected TF file to another one (other group tf file, variables, outputs, …)
  • Fixed: When a user configure a block (set) then deletes all the value the block is generated empty. 
  • Fixed: Subnet IDs double added
  • Fixed: Automatically generate the connectors between resources when I reference an existing resource.
  • Fixed: when I connect, it shows the owner as an extra user
  • Fixed: With some attribute type like SelectList (array), changes do not trigger the TF code refresh
  • Fixed: Sign up page on Safari browser 
  • Fixed: In the README modal, the save button doesn’t work at all, so if I write content it is automatically saved and there is no need for this button.
🐞 Fixed
7 months ago

🏌🏻‍♂️ Connected people show many times

The bug being fixed in this statement pertains to the display of connected users in Brainboard, a cloud management solution. Specifically, the issue is that when the same person connects from different tabs, Brainboard was showing their avatar multiple times in the top bar. This can cause confusion for users, as it may not be immediately clear how many unique users are currently connected.

The development team has fixed this issue by implementing a system that detects when the same user connects from multiple tabs and only displays their avatar once in the top bar. This ensures that the number of connected users displayed in the top bar is accurate and reduces confusion for users.

In summary, the bug that was fixed is that when the same person connects from different tabs, Brainboard was showing their avatar multiple times in the top bar, which caused confusion for users. The development team has fixed this issue by implementing a system that detects when the same user connects from multiple tabs and only displays their avatar once in the top bar, ensuring that the number of connected users displayed in the top bar is accurate.
🐞 Fixed
7 months ago

➕ Invite users during onboarding

The bug fix being mentioned in this statement pertains to the onboarding process in Brainboard, a cloud management solution. The issue being addressed is that users were not able to invite their colleagues during the onboarding process.

This bug has been fixed and now users can invite their colleagues during the onboarding process on Brainboard. This means that users can now collaborate with their team members during the setup and configuration of their cloud architecture, which can increase the overall efficiency of the design process.

Collaboration allows multiple users to work on the same project simultaneously, which can save time and reduce the chances of errors. By having multiple team members working on the same architecture diagram, for example, one team member can work on the design while another team member can work on the configurations. This can lead to a faster and more efficient design process.

Additionally, collaboration also allows team members to share their knowledge and expertise, which can lead to better and more innovative solutions. By working together, team members can bounce ideas off of one another and provide constructive feedback, which can result in a more robust and effective architecture.

In summary, the bug fix allows users to invite their colleagues during the onboarding process in Brainboard, which enables them to collaborate with their team members during the setup and configuration of their cloud architecture. Collaboration can increase the overall efficiency of the design process by allowing multiple users to work on the same project simultaneously, sharing knowledge and expertise, and providing constructive feedback.
🐞 Fixed
7 months ago

🚀 Do not commit/push .terraform/ folder during PR/MR

The feature being mentioned in this statement is related to the management of the .terraform/ folder in Brainboard, a cloud management solution. The issue being addressed is that when a pull request (PR) or merge request (MR) is made, too many files were being pushed, including the .terraform/ folder and its contents, such as terraform.tfstates.

The development team has implemented a feature that prevents the .terraform/ folder from being committed or pushed during a PR or MR. This means that when a user makes a PR or MR, the .terraform/ folder and its contents will not be included in the changes being pushed to the remote repository.

The .terraform/ folder is used to store the state of the resources in your Terraform configuration and it's sensitive data. So, it's not recommended to share it with others. By not committing/pushing this folder during PR/MR, it ensures that sensitive data is not accidentally shared with others, and it also reduces the amount of data being pushed, which can improve the performance of the PR/MR process.

In summary, the feature prevents the .terraform/ folder from being committed or pushed during a pull request or merge request in Brainboard. This ensures that sensitive data is not accidentally shared with others, and it also reduces the amount of data being pushed, which can improve the performance of the PR/MR process.
🐞 Fixed
7 months ago

☁️ GCP tags broken

The feature being mentioned in this statement pertains to the handling of tags in the Google Cloud Provider (GCP) for Terraform, a tool for building, changing, and versioning infrastructure. The issue being addressed is that GCP Terraform tags were not working correctly, resulting in broken functionality.

The development team has fixed this issue and now GCP Terraform tags are correctly handled, meaning that users should no longer experience issues with broken functionality.

In Terraform, tags are used to organize and categorize resources within the cloud infrastructure. 

  • In GCP, Terraform tags are used to add metadata to resources such as virtual machines, disk, and networks. These tags can be used to identify, organize and manage resources within GCP. For example, you can use tags to organize resources by environment, application, or project, and you can also use tags to identify resources for billing and cost management.
  • In AWS, tags are used similarly to GCP, but they are referred to as resource tags. AWS tags provide a way to organize and categorize resources within an AWS account.

In summary, the feature fixed the handling of tags in the Google Cloud Provider (GCP) for Terraform, which were not working correctly, resulting in broken functionality. Terraform tags are used to add metadata to resources such as virtual machines, disk, and networks within GCP, and in AWS it's referred to as resource tags. They are used to organizing and categorize.

Start using tags the proper way with Brainboard.
🐞 Fixed
7 months ago

␡ Deleting an item in map deletes all items

The issue being addressed is that when a user added key-value items into a map-like tag and then removed only one item, it would delete all the items in the map.

The development team has fixed this issue and now when a user removes one item from a map, it will only delete that specific item and not all the items in the map. This ensures that users have greater control over the items in their maps and can make changes to them without accidentally deleting all the items.

In summary, this feature addresses a bug in Brainboard where when a user added key-value items into a map-like tag and then removed only one item, it would delete all the items in the map. The development team has fixed this issue and now when a user removes one item from a map, it will only delete that specific item, ensuring that users have greater control over the items in their maps and can make changes to them without accidentally deleting all of the items.
🐞 Fixed
7 months ago

🔥 Fix Terraform version change in deployment*

The issue being addressed is that when a user changes the version of Terraform to a newer one, the backend prompts them to migrate the state, but the version of Terraform is not updated in the frontend.

The development team has fixed this issue and now when a user changes the version of Terraform, the version is also updated in the frontend, and the user is able to perform actions such as plan, apply and destroy. This ensures that the user is always working with the correct version of Terraform, which can prevent errors and improve the stability of the platform.
*Terraform deployment is the process of creating, updating and deleting resources in an infrastructure, using Terraform HashiCorp Configuration Language (HCL) and Terraform API.

When you run terraform plan command, it compares the current state of infrastructure with the desired state, defined in the Terraform code, and it shows the changes that will be made to the infrastructure.

When you run terraform apply command, it applies the changes, defined in the plan to the infrastructure.

When you run terraform destroy command, it removes all resources, defined in the Terraform code from the infrastructure.

During this process, Terraform keeps track of the current state of the infrastructure in a state file, which is usually stored in a remote backend, such as AWS S3, and it can also be stored in a local file.

In summary, the feature fixed the issue with Terraform version change in deployment, where the version of Terraform is not updated in the frontend, causing difficulties for users to perform actions like plan, apply and destroy. 

Version and deploy your cloud architecture with Brainboard.
🐞 Fixed
7 months ago

␡ Can’t delete a local*

The issue being addressed is that users were unable to delete locals, which are variables with a scope of "local".

The development team has fixed this issue and now users are able to delete locals. This means that users can now delete variables with a scope of "local" without encountering any errors.
*In Terraform, a local is a way to assign a value to a variable, and it's only accessible within the same module where it's defined. A local variable can't be accessed outside of the module where it's defined. It can be used to store temporary values that are used within a module and it's not exposed to other modules.
For example, in Brainboard, a user could define a local variable to store the name of a resource and use it throughout the module, and then delete it when it's no longer needed.

In summary, the bug fix addresses an issue where users were unable to delete locals in Brainboard. Now, users can delete variables with a scope of "local" without encountering any errors. Locals are variables with a scope of "local" in Terraform, and it's used to store temporary values that are used within a module and it's not exposed to other modules.
🐞 Fixed
8 months ago

🐞 AWS Gov regions alias

The issue being addressed is that in the providers.tf file, the AWS GovCloud regions were not included.

The development team has fixed this issue and now the GovCloud regions are listed with their own alias in the providers.tf file. This means that users can now use the appropriate alias to specify the GovCloud region they want to work with, instead of having to manually enter the region's endpoint.
AWS GovCloud (US-West) and AWS GovCloud (US-East) are regions that are specifically designed to host sensitive data and regulated workloads in the cloud, and they are isolated to the US Government's infrastructure. These regions provide a high level of security and compliance.

Examples of the regions include:
  • us-gov-east-1
  • us-gov-west-1

In summary, the bug fix addresses an issue where in the providers.tf file, the AWS GovCloud regions were not included. The development team has fixed this issue and now the GovCloud regions are listed with their own alias, which allows users to use the appropriate alias to specify the GovCloud region they want to work with, and it's more convenient, instead of having to manually enter the region's endpoint. AWS GovCloud regions are designed to host sensitive data and regulated workloads in the cloud, and they are isolated to the US Government's infrastructure.

Use AWS GovCloud resources with Brainboard.
🐞 Fixed
8 months ago

🐞 Auto-generate the Terraform code

The issue being addressed is that the code was not being generated for a new architecture.

The development team has fixed this issue and implemented auto-generation of Terraform code, which is a first in the cloud computing industry. This means that when a user creates a new architecture in Brainboard, the platform will automatically generate the corresponding Terraform code for that architecture diagram.

This auto-generation feature can help cloud architects go faster in designing and deploying cloud architectures. By having the Terraform code automatically generated, cloud architects can save time and effort that would have been spent on manually writing the code. This allows them to focus on other important tasks, such as designing and testing their architectures.

Additionally, the auto-generation feature can also help to reduce the chances of errors that can occur when manually writing code. By having the code automatically generated, the chances of typos, syntax errors and other issues are greatly reduced, which can lead to a more stable and reliable infrastructure.

In summary, the feature fixed the issue where the code was not generated for a new architecture and implemented auto-generation of Terraform code, the first in the cloud computing industry. This auto-generation feature can help cloud architects go faster in designing and deploying cloud architectures by saving time and effort that would have been spent on manually writing the code, and reducing the chances of errors.
🐞 Fixed
8 months ago

♻️ Frontend reload system*

*Frontend reload system refers to a technology that allows for automatic updating of the front-end (client-side) of a web application. It is used to ensure that users always have the most recent version of the application, without the need for manual updates.
The feature being mentioned in the statement is that Brainboard, a cloud management solution, has implemented a frontend reload system. This means that when updates are made to the application, the frontend of the application will automatically reload and update to the newest version. This ensures that users are always working with the most recent version of the application, which can improve the stability and security of the platform, and provides users with the latest features and improvements.

One of the advantages of this feature is that it eliminates the need for users to manually update their application, reducing the chances of errors and downtime. It also makes it easier for the development team to roll out new features and bug fixes, as users will receive them automatically, without the need for manual intervention.

In summary, the frontend reload system is a technology that allows for automatic updating of the front-end of a web application, ensuring that users always have the most recent version of the application, and making it easier for the development team to roll out new features and bug fixes. Brainboard has implemented this feature, which ensures that users always have the newest app version.
🐞 Fixed
8 months ago

🐞 ResourceName in the module’s code

When you edit the resource name of a module, it’s added in the code (cloudConfig)
  1. Add a module
  2. Edit the ResourceName
  3. The change is applied and the new ResourceName just appeared in the code
🐞 Fixed
11 months ago

⬇ Export your diagram into svg, png or pdf

The feature being mentioned in this statement is the ability to export architecture diagrams in Brainboard, a cloud management solution, into various file formats, such as SVG, PNG, or PDF. This feature allows users to save their diagrams in a format that is compatible with various image editing and presentation software.

The export feature allows users to take a snapshot of their current architecture diagram and save it as an image file, which can be useful for sharing with others, such as a boss or team members, or for keeping a record of the diagram for later reference.

Additionally, this feature also allows users to export their diagrams in different formats, like SVG, PNG and PDF. SVG format is vector based format which can be zoomed without losing quality, PNG format is raster based format which can be used for images, PDF format is used for document sharing. Users can choose the format according to their needs.

The statement also mentions that the export feature has been reintroduced, indicating that it may have been removed or absent in previous versions of Brainboard. This feature is also useful for those who missed the Screenshot feature, which is now back and improved. With the export feature, users can quickly export their cloud architecture diagrams and drop it anywhere they would like, such as in a presentation or in an image editing software for further annotation.

In summary, this feature allows users to export their architecture diagrams in Brainboard into various file formats, such as SVG, PNG and PDF, enabling them to save and share their diagrams in a format that is compatible with various image editing and presentation software, and it also allows users to take a snapshot of their current architecture diagram and save it as an image file.

Start exporting your cloud architecture on Brainboard.
Screenshot 2022-03-08 at 10.51.18.png 115.92 KB

You can export your architecture as an image (svg, png or pdf).