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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.
Search bar is added in the documentation. Find everything you need to get you started with Brainboard.
CI/CD terminal output can be as fast as your local environment. With all infrastructure-as-code IDE tools under one roof, there is no impact on velocity.
Marketplace: You can now use your own Azure or AWS billing account / credits.
🐞 FIXED
We've resolved reported issues that were causing occasional crashes when, for example:
The Terraform code refresh triggering event was completely revamped. If you encountered any issues regarding that, this is now fixed.
Modules’ configuration have been fixed. You should always have your up-to-date modules’ variables.
Variables and locals with the same name were conflicting. Now, enjoy the Brainboard override system (Organization → Project → Environment → Architectures).
Locals & Variables 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 resolved in the latest version of Brainboard and should no longer occur.
Drift Detection: We will release the first alpha version.
Resource's left bar: We completely redesigned the design area’s left bar thanks to our in-house designer.
🔥 Coming up next month
Migration (ex- Import): All cloud migration will be reviewed by our Cloud Architect experts before you get, use & scale it.
Security: Improve the Brainboard and Cloud providers integrations with the latest and validated protocols to centralize your cloud infrastructures securely.
🎉 We're thrilled to announce that Brainboard now supports Terraform Cloud remote backend! With this feature, you can easily manage your infrastructure state remotely, making it easier and more secure to collaborate with your team.
ℹ️ The remote backend is a storage that hosts the Terraform state of your cloud infrastructure after it is provisioned.
📡 Brainboard uses Terraform as the provisioning engine and so the concept of the remote backend comes from the configuration of Terraform that allows you to specify which storage system you want to use and how to access it.
Inheritance now supports multiple resources - While designing your cloud architecture, you can now move 2+ resources at the same time into a container.
The Brainboard migration tool supports multi-lines strings.
Export architecture as JSON - We added the export feature to allow all our users to either backup their architecture, to migrate them from one account to another one, to share them with the support when needed. You are now able to export and import any Brainboard architecture easily.
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:
Migrate Azure:
Migrating your existing cloud infrastructure from Azure to Brainboard is better day after day. With more complex use cases coming to us, we are able to improve the quality and the compliance of all cloud resources available in Terraform provider Microsoft Azure. We also improved the error messages, clarifying the reason behind it. Also, when migrating your terraform infrastructure, everything included terraform states, are successfully supported and imported in to Brainboard.
In the CI/CD Engine, we've been adding approval tasks enabling cloud architects to ask for review / approval before, during or after the deployment. Now, this task has improved, enabling seamless email notifications.
Overall, we've been working hard in enhance your experience when designing your cloud architecture. Now, drag & drop and configuring is a matter of seconds with faster terraform code generation and improvements of navigating your canvas.
When deploying your cloud architecture, we improved the output of your Terraform code, CI/CD workflow and Terraform actions. That will enable you to make clearer decisions, apart from all distractions, having all your cloud environment in one solution.
We apologize for any inconvenience this may have caused, and thank you for bringing it to our attention.
New year, new design system: We've been shipping a lot lately. Our image you perceive of Brainboard count for us. So we heard your feedback and designed internally our new logo, images, and experience across the website, the onboarding, and the application with new colors and visual improvements.
Documentation: A new documentation was just released, improving product clarification and explanation. This improved documentation will help users better understand our product and how to best use it. Get excited about next week's website launch, featuring brand-new features and a more modern design! You can visit the documentation here.
We are excited to announce the brand lifting of Brainboard's website!
After 2 months of hard work and dedication, the new website is now live 🎉 Thanks to the whole Brainboard team, we were able to review all the content on time and deliver the best experience possible, maintaining the high quality we value for our customers, users and FFFs.
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: CI/CD Engine by Brainboard
Import errors:
The import functionality has been improved to address the problem of internal errors. Error handling has been optimized and the dependencies between resources are now managed more effectively.
CI/CD Approval task — List of suggested users:
The user experience when deploying cloud infrastructure through the CI/CD Engine has been improved. Users now have the ability to choose from a list of suggested users when approving a task, eliminating mis-suggestions.
Configuring resources when selecting a node
The user experience has been improved when selecting resources through the Design Area or TF Code. Now, the ID Card will open automatically when clicking on a resource name.
Data inheritance not implemented when importing:
The inheritance of data sources when importing TF files has been implemented. For example, when a data subnet is inside a data virtual network, it will now be depicted as such in the TF code.
Templates' catalog ownership:
The "by" section in the Template Catalog has been updated to include all relevant authors. This ensures proper attribution and recognition.
Initiator name is missing in pipeline output:
The name of the person triggering the pipeline is now included in the pipeline View, providing visibility into who is responsible for launching which pipeline and when.
We apologize for any inconvenience this may have caused, and thank you for bringing it to our attention.
Performance: Performance in the canvas area of Brainboard has been improved gradually, especially with small architecture and very big architectures (500+ nodes). This should result in faster load times and a smoother user experience.
Documentation: A new documentation was just released, improving product clarification and explanation. This improved documentation will help users better understand our product and how to best use it. Get excited about next week's website launch, featuring brand-new features and a more modern design! You can visit the documentation here.
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
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.
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.
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.
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.
ImportMultiple 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.
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.
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.
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.
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.
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.
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:
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.
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.
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.
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.
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.
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.
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.
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.
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.
When working with Brainboard, users can navigate between the visual representation of their infrastructure (the "resource") and the code that defines it (the "configuration") in a seamless way.
Before
When a user selects a node in the visual representation of their infrastructure, they may not know where in the code for that specific node is located.
Now
When a user clicks on a resource in the visual interface, Brainboard solves this problem by automatically highlighting the corresponding section of code when a node is selected, making it easy for the user to find and understand the configuration for that node. This feature allows for more efficient and intuitive management of infrastructure.
⧮ Improve PR/MR* creation flow with clear error messages!
* PR = Pull Requests
MR = Merge Requests
Brainboard's tech team has significantly improved the error messaging experience when performing pull or merge requests.
To accomplish this, we have changed the backend to provide more detailed and informative error messages. These error messages are now displayed directly on the front end, making it easy for you to understand and resolve any issues that may arise. We have also made improvements to the modal's User Experience (UX) to make it more intuitive and user-friendly.
These enhancements will make it easier for you to manage and troubleshoot your code changes.
About
Merge requests (MRs) & pull requests (PR) in a version control system (VCS) like Git can save your cloud infrastructure project by allowing you to:
Collaborate effectively with team members: PR/MR provide a way for team members to propose changes to the infrastructure codebase and review and discuss them with other team members before merging them into the main branch. This allows for better collaboration and communication within the team.
Implement code review and testing processes: PR/MR provides a way to implement a code review process, where other team members review changes to the infrastructure codebase before being merged. This can help identify and fix bugs and issues before they are deployed to production.
Track changes to the infrastructure codebase: PR/MR provides a way to track changes to the codebase, including who made the change and why making it easier to understand how the infrastructure has evolved.
Rollback changes: PR/MR provides a way to roll back changes to the infrastructure codebase if something goes wrong. This can be done by reverting the merge commit or using version control tools like Git to revert specific changes.
Isolate changes: PR/MR provides a way to isolate changes, meaning that changes are committed and tested in a separate branch before merging into the main branch. This allows for keeping the main branch stable and ready to deploy at all times.
Implement automated testing and integration: PR/MR provides a way to implement an automated testing and integration process. This can be done by integrating the VCS with a continuous integration and deployment tool, which can run automated tests and deploy changes to different environments.
One step forward binary way of working the infrastructure on Brainboard.
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.
↕ 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:
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.
Using the "${resource.name.attribute}" syntax allows you to reference the attributes of one resource in the configuration of another resource.
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.
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.
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.
In Brainboard, this applied for all cloud providers supported (Azure, OCI, GCP, Scaleway)
You can now use variables in multi-region AWS diagram design :)
Terraform variables in Brainboard can be used to create a multi-region AWS diagram design in several ways:
Use variables to define the regions you want to deploy your infrastructure in: By using Terraform variables; you can specify which regions you want to deploy your infrastructure in and make it easy to change or add regions in the future.
Use variables to define the specific resources in each region: By using Terraform variables, you can specify the specific resources you want to deploy in each region. This allows you to create different resource configurations for different regions easily.
Use variables to define the AMI ID: By using Terraform variables, you can specify the AMI ID (Amazon Machine Image) you want to use in each region. This allows you to use different AMIs for different regions.
Use variables to define the subnets and availability zones: By using Terraform variables, you can specify the subnets and availability zones that you want to use in each region. This allows you to use different subnets and availability zones for different regions.
Use variables to define the security group: Terraform variables can specify the security group you want to use in each region. This allows you to use different security groups for different regions.
Here is an example of how you can use Terraform variables to define a variable for the region:
variable "region" {
default = "us-west-2"
}
You can use this variable in your resource definition like this:
resource "aws_instance" "example" {
ami = var.ami
instance_type = "t2.micro"
region = var.region
}
Improve the error handling in the CI/CD (Continuous Integration/Continuous Deployment) engine of Brainboard. Specifically, the improvement is related to the handling of errors that occur during the use of web sockets.
*Web sockets are a technology that allows for real-time, two-way communication between a client and a server over a single, long-lived connection. In the context of CI/CD, web sockets may facilitate communication between Brainboard's CI/CD engine and other system components, such as the version control repository or the deployment pipeline.
The improved error handling in this feature ensures that any errors that occur during web sockets are handled more effectively, allowing a seamless CI/CD process to continue functioning even in the event of an error.
A brand new Single Tenant version with CI/CD included and up-to-date versions is available for enterprises. Please contact us if interested.
*Single tenant refers to a software as a service (SaaS) solution where each customer or client has their dedicated instance of the software running on a separate infrastructure. This contrasts with a multi-tenant SaaS solution, where multiple customers or clients share the same software instance, running on a shared infrastructure.
In a single-tenant SaaS solution, the customer's data and configuration are isolated from other customers and not shared with any other organization. This provides a higher level of security, compliance, and customization. Customers have more control over their data, and the software can be tailored to the customer's specific needs.
Single-tenant SaaS solutions are typically used by larger organizations with more stringent security and compliance requirements or organizations requiring a high level of customization. They may also be used by organizations with sensitive data that they do not want to share with other organizations.
It's important to note that Single tenant solutions are often more expensive than multi-tenant solutions because the hardware and infrastructure costs are spread across fewer customers. Additionally, because each customer requires its own infrastructure, there are more operational costs to manage and maintain the different instances.
🔎 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.
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:
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.
Organization: Modules provide a way to organize your resources and make your Terraform configurations more readable and maintainable.
Versioning: Modules can be versioned, which allows you to track changes and roll back to a specific version if needed.
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.
Abstracting complexity: Modules can help abstract away complexity by breaking down large configurations into smaller, more manageable pieces.
Better testing: By using modules, you can quickly test a specific part of your infrastructure without affecting other parts.
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.
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.
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.
Visually design and orchestrate your deployment workflows without a single line of code.
Connect your automation ecosystem with OPA, Infracost, Checkov, or Terrascan…
Centralize your custom automation strategies and remote-run deployments.
Execute, optimize and manage workflows for successful outputs.
One of the biggest added values in terms of deployment is that Brainboard manages the upgrades and maintenance of the supported plugins: Infracost, OPA…
One feature that enables engineers to create repeatable templates of cloud architectures is using infrastructure as code (IAC) tools such as Brainboard.
Brainboard is a tool that allows you to define, provision, and manage infrastructure as code. You can use Brainboard to create templates, called modules, that define specific cloud architecture patterns and configurations. These modules can be shared with other team members, allowing them to use the same templates to provision and manage their own infrastructure.
With Brainboard, engineers can create repeatable templates. These files can be version controlled and shared through various means, such as Git. This allows other team members to view, use, and modify the templates, making it easy for them to spin up similar infrastructure quickly.
Brainboard allows you to use variables, which can be defined in a separate file (tfvars) or passed through the command line, making it easy to parameterize the templates and adjust them to specific use cases or environments.
* tfvars files are Terraform configuration files that store variables for a Terraform configuration. They typically have the file extension .tfvars and are used to set values for variables that are used in Terraform configuration files. These files allow you to store sensitive information like credentials and other sensitive data, which you can use in your Terraform configuration, but without having to hard-code them in your .tf files.
This bug fix likely addresses an issue where users were unable to set values for variables when they were importing resources into Brainboard. An import allows a user to take an existing resource that was not created by Terraform and bring it under Brainboard management. However, if there is a bug that prevents users from setting variable values during an import, it would make it difficult for them to properly manage these resources.
The bug fix likely addressed this issue by allowing users to provide variable values during an import, allowing them to properly manage the imported resources. This would enable the users to import resources, and also set values for the variables that they want to use to manage these resources.
This summer, while many were enjoying their vacations, the development team at Brainboard was hard at work. They were focused on enhancing every aspect of the platform, and one of the most highly-anticipated features was the ability to import from Azure, now available to the public.
Introducing Import Azure
To celebrate this new feature, we are excited to offer you 50 free credits to import 50 Azure cloud resources and transform your Azure infrastructure into Terraform code and a live diagram. If you require additional credits, please don't hesitate to let us know. We are here to help you every step of the way.
The transition between design and code has been made easier, more responsive and more flexible. Cloud resources can be opened and closed to focus on designing the architecture diagram and Terraform code can be opened and closed to focus on configuration. This new feature was recently developed by our front-end experts and I was impressed with it after trying it out. It's truly amazing and I wanted to share it in this month's newsletter. Try it out for yourself!
Brainboard have made significant improvements to the process of configuring cloud resources, specifically in regard to the identification and management of each resource. This is an essential task when building an architecture diagram, and we recognized the need for a more streamlined and efficient approach.
We have completely redesigned the concept of configuring a cloud resource, with a focus on simplifying the process and reducing the number of steps required. This has been achieved through the integration of more advanced automation techniques and the use of more intuitive user interfaces.
In addition to this, we have also made improvements to the design to code feature, which allows for a more seamless transition between designing the architecture diagram and configuring the relevant code. The combination of these two features results in a much smoother overall experience for the user.
I have personally tested these new features and can confidently say that it is a significant improvement from the previous version. I highly recommend giving it a try for yourself and see the difference.
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.
This feature release pertains to the new id card that has been introduced in the Brainboard cloud management solution. With this new feature, users are now able to directly edit the icon of any resource when configuring it.
To do this, the user simply needs to hover their cursor over the existing icon and a prompt will appear, allowing them to upload a custom icon. This feature allows for a greater degree of customization and organization when building and managing architecture diagrams within Brainboard. Additionally, it gives users the ability to easily identify resources in diagrams by custom icons.
Start configuring your cloud resources with Brainboard.
This feature release pertains to the import feature in the Brainboard cloud management solution. The development team has been working on improving the user experience and the output of this feature.
A new and improved version of the import feature has just been released. With this new version, users are now able to start configuring their cloud resources while they are dragging and dropping them onto their architecture diagram. This means that users no longer have to complete the configuration process after the resources have been imported, they can now do it in real-time as they are adding resources to the diagram. This allows for a more efficient and streamlined workflow, and can save users valuable time.
The team is encouraging users to try out this new feature and provide feedback on their experience with it. This will help the team continue to improve the product and provide the best experience for the users.
This feature release pertains to the redesign of the id card in the Brainboard cloud management solution. The development team has completely rethought the concept of the id card to improve productivity and readability for the users.
The new id card has been redesigned with the goal of providing a more efficient and streamlined workflow when configuring cloud resources. One of the key changes is that users can now start configuring their cloud resources while they are dragging and dropping them onto their architecture diagram. This eliminates the need to switch back and forth between configuring resources and adding them to the diagram, allowing for a more efficient workflow.
In addition to this, the new id card has been optimized for smoother readability. This includes improvements to the layout, typography, and color scheme. The new design is intended to make it easier for users to quickly and easily identify the relevant information for each resource, which can save valuable time when building and managing architecture diagrams.
The new id card also includes advanced automation techniques and more intuitive user interfaces which makes the overall process of configuring cloud resources faster and more user-friendly.
Overall, the redesign of the id card is aimed at improving the productivity and readability of the Brainboard cloud management solution, and providing a better experience for the users.
Start configuring your first resources on Brainboard.
At Brainboard, we've worked hard to take your experience with the Cloud to the next level, especially while managing Git credentials in teams.
We've enabled you to:
As an individual contributor, you can add personal git tokens for any supported git provider - Azure DevOps, Gitlab, Bitbucket - and specify the scope of the creds and have visibility on where they are used.
As the owner of the organization, you can add Github app integration and users perform git actions based on their authorization on Github.
What do you need to do:
The Git credentials of your organizations are assigned to the owner of the organization. So you need to add your personal token in order to do pull requests.
If you use GitHub, there is nothing to do. Your pull requests work as before.
Pull requests: Choose the git provider to use from the supported ones - Azure DevOps, Gitlab, Bitbucket, GitHub, and add the description, project, folder, and base branch within the service.
Modules: You can choose which git credentials you want to use to import your private modules and use them.
Generate your diagram from the terraform code: Choose the git credentials you want to use and import your existing terraform code.
Both categories, git apps and personal tokens, are available on the 'Account' configurations, here:
This new set-up capability enables the seamless performance of tasks without switching between accounts and re-authenticating accesses, and so work independently and well.
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.
*Keycloak is an open-source identity and access management solution. It is designed to provide a centralized location for managing user authentication and authorization. Keycloak provides features such as Single Sign-On (SSO), user management, and access control for applications and services.
The feature being mentioned in the statement is the integration of Keycloak with Brainboard, a cloud management solution. With this integration, users of Brainboard have the ability to use Keycloak as the authentication system for their Brainboard account. This allows users to use their Keycloak credentials to log in to Brainboard, rather than having to create and manage separate login information.
By using Keycloak as the authentication system, Brainboard users can take advantage of Keycloak's advanced security features and user management capabilities. This can improve the security of the Brainboard platform and make it easier for users to manage access to their cloud resources.
In summary, the integration of Keycloak with Brainboard allows users to use Keycloak as the authentication system for their Brainboard account, which improves security and user management capabilities.
✅ Import templates that you or your team have created into the same design and combine them to create complex architectures and use-cases 😱 The Terraform code is instantly & automatically created.
👉 In this video: clone-in-arch.mp429.19 MB - I was creating an #AWS bastion - Then I added a serverless stack to it - I also added a layer of a landing zone All in the same design...and I can keep building it this way.
😍 Turn your complex workloads into a collaborative diagram + code where anyone in your team can understand it & work on it without pain.
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.
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.
SSOSingle Sign-On is an authentication scheme that allows a user to log in with a single ID to any of several related, yet independent, software systems. True single sign-on allows the user to log in once and access Brainboard services without re-entering authentication factors.
🚀 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.
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.
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.
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.
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.
We noticed that users often forget to click on apply so they lose their changes.
Making editing the ID card saves the configuration automatically without clicking on the apply button. We also give the possibility to cancel/roll back the changes if the user wants it.
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.
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.
*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.
*Bitbucket is a Git-based source code repository hosting service owned by Atlassian. It allows users to store, manage, and collaborate on their source code projects, using Git as the version control system. Bitbucket supports both public and private repositories, and provides features such as pull requests, code review, and issue tracking to help teams collaborate on code development.
The feature of integrating Bitbucket into the workflow means that users can now connect their Bitbucket repositories to other tools and services that they use, so that their code and development process can be seamlessly integrated into their overall workflow. This could include integrating Bitbucket with continuous integration and continuous delivery (CI/CD) tools, project management tools, or other code collaboration tools.
For example, users could connect their Bitbucket repository with a CI/CD tool like Jenkins to automate the process of building, testing, and deploying their code. They could also connect Bitbucket with a project management tool like Jira to track issues and tasks related to their code development process.
By integrating Bitbucket into Brainboard, users can streamline their development process and increase efficiency by eliminating the need to manually switch between different tools and services. Additionally, it can also facilitate collaboration and communication among team members by connecting their tools and services.
You can replicate with an automatic sync the same diagram in different environments.
This is useful in cases where you want to have the same architecture diagram on multiple environments: dev, staging, and production... and any graphical change you make to either environment will be automatically replicated into the other ones.
To do it, click on the switch of syncing architectures in the cloning wizard as follows
Allow the user to change the remote backend setting at the architecture level. ℹ️ For users/clients that want to manage multiple clients over multiple clouds and use a dedicated remote backend per client.
🔥 Cloud architects, network architect & DevOps people build cloud infrastructures in a way that allow others to reuse their work with the minimum interaction possible → and if they use Terraform, they do it through modules.
✅ In Brainboard.co (YC W22), we allow you now to scale this workflow: - Import any module by just providing its source path
- You build your internal module's catalog 💪 you build your self-serve modules
- Combine modules to build cloud infrastructures that are aligned with your workflows 🔥
- Customize the icon of every module you import to make understandable diagrams 😍
Terraform Reverse is a feature that allows users to automatically generate Terraform diagrams and code from their existing resources on AWS and Azure, which is now available for early access. This means that users can now convert their existing resources on these cloud providers into actionable diagrams and Terraform code, which can be used to manage and maintain their infrastructure as code.
The feature is designed to save users time and money by allowing them to quickly and easily migrate their existing resources to Terraform. It takes less than 30 minutes to migrate 2500 resources instead of 6 months, which represents a significant time savings. Additionally, the feature can save users money by reducing the cost per resource migrated, which can add up to thousands of dollars at scale.
The feature also allows users to achieve a much faster time to infrastructure as code (IaC) and automation, with up to 100x faster time. This allows users to quickly and easily automate the management of their infrastructure, which can lead to increased efficiency and reduced human error.
Overall, Terraform Reverse is designed to help users save time and money by making it easy to migrate their existing resources to Brainboard and automate the management of their infrastructure. With this feature, users can take advantage of the benefits of IaC, such as increased efficiency and reduced human error, while minimizing the time and effort required to do so.
We updated your onboarding process to include more explanation materials at first login, accessible anytime, directly from your interface. We’ve also launched a brand-new tutorial gallery so that anyone can learn how to build their cloud architecture, more efficiently.
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.
Information security is a reason of concern for all of us, and has been in our DNA and a top priority from day one.
With that in mind, we’re on our way to getting our SOC Certification 🔒
We strive to make our platform seamless and secure for all of our users and partners.
We’ve been working with Vanta to help achieve our #SOC2 certification.
We use Vanta’s automation platform to continuously monitor different security aspects across the organization, be it internal security controls, employee training, secure development, etc. against the recommended standards.
This feature is a tool that allows users to import Terraform, a tool used for infrastructure as code, and manage it visually. We've been collecting feedback from users since its release last month and has been making improvements and releasing new versions daily.
Reverse Terraform is a feature of Brainboard that allows users to automatically generate Terraform diagrams and code from an existing Terraform file, a public or private repository, and connect to their cloud provider's credentials. This feature enables users to create visual representations of their infrastructure and quickly understand the relationships between resources, as well as generate Terraform code for those resources, making it easier to manage and maintain their infrastructure. Additionally, by connecting to cloud provider credentials, Brainboard can also pull in information about existing resources and use that to generate the Terraform code, allowing users to easily import their existing infrastructure into Terraform.
The new versions include features such as:
Private Repositories (Only GitHub): This fix allows users to connect to their private GitHub repositories and import their Terraform code. This is useful for users who want to keep their infrastructure code private and only accessible to authorized users.
Supports count, timeouts, depends_on (add connector with the dedicated connector.link.type): This fix enables the tool to support count, timeouts, and depends_on Terraform resources, which are used to create multiple instances of a resource, set timeouts for resources, and specify dependencies between resources. The tool also allows users to add connectors with the dedicated connector.link.type.
Supports terraform functions (like format, substr, ...), string interpolation (like “aaa$[var.test]”): This fix enables the tool to support Terraform functions, such as format and substr, and string interpolation. Terraform functions are used to perform various operations on strings and variables, while string interpolation allows users to include variables within strings.
Some resource attributes not parsed: This refers to an issue where some resource attributes were not being parsed correctly by the tool. This fix addresses this issue, ensuring that all resource attributes are parsed correctly.
Create module idcard on the fly: This fix allows users to create module idcards on the fly. A module idcard is a summary of a module's inputs, outputs, and resources. This allows users to quickly understand the purpose and structure of a module without having to examine its code.
Import code with module fails: bad source, no version: This refers to an issue where importing code with modules would fail if the source or version was not specified correctly. This fix addresses this issue, allowing users to import code with modules correctly.
Git root/base repo URL doesn't work: This refers to an issue where the git root or base repo URL was not working correctly. This fix addresses this issue, ensuring that the git root/base repo URL works correctly.
Support EOF in resource attribute: This fix enables the tool to support EOF in resource attribute. EOF, short for End-of-file, is a control code used to indicate the end of a file or stream. This fix allows the tool to correctly handle EOF in the resource attribute.
Migrate your cloud infrastructure on Brainboard for a better process standardization.
As per Terraform definition: Data sources allow Terraform to use information defined outside of Terraform, defined by another separate Terraform configuration, or modified by functions.
They are heavily used in architecture to reference and/or get information about a resource already deployed. Data resources could be
A common resource shared between multiple architecture
For security reason (read-only access)
Managed by another team
⚠️ Note that each provider may offer data sources alongside its set of resource types.
Turn your Terraform code into an actionable Diagram in seconds! 🎉
This feature is brand-new to the Brainboard app, enabling everyone to upload the Terraform .tf code and auto-generate a diagram. It eases migration into Brainboard.
Please note, this feature is new and will definitely be improved 🙂
Please don't hesitate to share your feedback, and we'll make sure to take it into consideration for further updates 😉
We've seen some of you needing to use Modules in your diagrams. With this feature, you are able to reuse any modules you find online / you create yourselves as a brick of reused codes directly from the Design brick of Brainboard. We made it easy to import, drag & drop and configure your modules directly on your dashboard. Let us know what you think 😇
Integration of GitHub and GitLab with Brainboard. Brainboard is a tool that allows users to design and manage their infrastructure as code. With this new native integration, users can now automatically push the code generated by Brainboard to their preferred Git-based repository, such as GitHub or GitLab.
This integration allows users to benefit from the capabilities of Brainboard, such as visualizing their infrastructure and generating Terraform code, while also being able to store their code in a trusted repository. By storing their code in a repository, users can take advantage of features such as version control, code review, and collaboration.
Brainboard already supports other Git-based repository hosting services, such as Bitbucket and Azure DevOps. This means that users have multiple options for where to store their code and can choose the repository hosting service that best fits their needs and workflow.
The feature also states that Brainboard continues to integrate the infrastructure with today's workforce, without jumping the whole team into Gits. This means that users can use Brainboard to design and manage their infrastructure as code, without needing to be experts in Git or other repository hosting services. This feature is meant to make it easy for users to take advantage of the benefits of infrastructure as code, even if they don't have a lot of experience with Git or other repository hosting services.
It's now possible to flag variables as secrets and that is also reflected on the generated Terraform code. Also, you can define outputs in Brainboard, use them and/or push the outputs.tf files into your Git repo. Screenshot 2022-03-04 at 13.05.48.png6.42 KB
Last week, you discovered our new pricing plan, based on the number of users. You are not limited to the numbers of Infrastructures you or your team will create. Now, you'll be able to add multiple credentials for every cloud provider, especially matching: Cloud Provider = Credentials <> Project.
As you all know, Cloud Providers update their resources very regularly. Now, we are thrilled to announce that, starting today, you'll be able to use the newest version or/and switch from older to newest.
Directly onto the Brainboard platform, you can now chat with our support team. The chat support is also available on the website and the documentation.
The synchronization process compares your local Designer workspace, the remote Decision Center database, and a reference that computes the state of the synchronization. This reference state is created as a connection entry in your workspace when you connect to Decision Center.
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