Alternatives to Sympli

The tool we use for editing UI is React Storybook. It is the perfect place to make sure your work aligns with designs to the pixel across breakpoints. You get fast hot module reloading and a couple checkboxes to enable/disable browser features like Flexbox.

The only tricks I apply to Storybook are loading the stories with the mock data we’ve extracted from the API. If your mock data really covers all the various various possible states for your UI, you are good to go. Beyond that, if you have alternative states you want to account for, perhaps loading or error states, you can add them in manually.

This is the crux of the matter for Storybook. This file is entirely generated from Yeoman (discussed below), and it delivers the examples from the Alps Journey by default. getSectionsFromJourney() just filters the sections.

One other hack you’ll notice is that I added a pair of divs to bookend my component vertically, since Storybook renders with whitespace around the component. That is fine for buttons or UI with borders, but it’s hard to tell precisely where your component starts and ends, so I hacked them in there.

Since we are talking about how all these fabulous tools work so well together to help you be productive, can I just say what a delight it is to work on UI with Zeplin or Figma side by side with Storybook. Digging into UI in this abstract way takes all the chaos of this madcap world away one breakpoint at a time, and in that quiet realm, you are good down to the pixel every time.

To supply Storybook and our unit tests with realistic mock data, we want to extract the mock data directly from our Shared Development Environment. As with codegen, even a small change in a query fragment should also trigger many small changes in mock data. And here, similarly, the hard part is tackled entirely by Apollo CLI, and you can stitch it together with your own code in no time.

Coming back to Zeplin and Figma briefly, they're both built to allow engineers to extract content directly to facilitate product development.

Extracting the copy for an entire paragraph is as simple as selecting the content in Zeplin and clicking the “copy” icon in the Content section of the sidebar. In the case of Zeplin, images can be extracted by selecting and clicking the “download” icon in the Assets section of the sidebar.

Hey,

We are a diverse group of in-house UX/UI-designers who currently work in different software; XD/Sketch/InVision and so on. We need an efficient way to manage our workflow to build, share, and maintain a consistent yet dynamic design library and a smooth, less time-consuming developer hand-off. There are lots of things to consider, and where we're at the moment, it's "design in your preferred program, but joint library and handoffs should happen through Zeplin or Avocode." Which one of these two should we go for? Any other solutions?

Thanks!

Hey,

We are a diverse group of in-house UX/UI-designers who currently work in different software; XD/Sketch/InVision and so on. We need an efficient way to manage our workflow to build, share, and maintain a consistent yet dynamic design library and a smooth, less time-consuming developer hand-off. There are lots of things to consider, and where we're at the moment, it's "design in your preferred program, but joint library and handoffs should happen through Zeplin or Avocode." Which one of these two should we go for? Any other solutions?

Thanks!

How we ended up choosing Confluence as our internal web / wiki / documentation platform at Katana.

It happened because we chose Bitbucket over GitHub . We had Katana's first hackaton to assemble and test product engineering platform. It turned out that at that time you could have Bitbucket's private repositories and a team of five people for free - Done!

This decision led us to using Bitbucket pipelines for CI, Jira for Kanban, and finally, Confluence. We also use Microsoft Office 365 and started with using OneNote, but SharePoint is still a nightmare product to use to collaborate, so OneNote had to go.

Now, when thinking of the key value of Confluence to Katana then it is Product Requirements Management. We use Page Properties macros, integrations (with Slack , InVision, Sketch etc.) to manage Product Roadmap, flash out Epic and User Stories.

We ended up with using Confluence because it is the best fit for our current engineering ecosystem.

I am working on a project for a client, I need to provide them with ideas and prototypes. They all have Adobe XD, but not InVision - I am the only one who will have that if purchased. I am trying to decide what would be the best tool to hand off the work to a developer who in terms will be working in PySide (Qt related) or Tkinter. Is there any benefits to me or the developer to work in Adobe XD or InVision. I am just trying to use the best tool to get the job done between the two.

Thank you in advance! Nadia

I was building a personal project that I needed to store items in a real time database. I am more comfortable with my Frontend skills than my backend so I didn't want to spend time building out anything in Ruby or Go.

I stumbled on Firebase by #Google, and it was really all I needed. It had realtime data, an area for storing file uploads and best of all for the amount of data I needed it was free!

I built out my application using tools I was familiar with, React for the framework, Redux.js to manage my state across components, and styled-components for the styling.

Now as this was a project I was just working on in my free time for fun I didn't really want to pay for hosting. I did some research and I found Netlify. I had actually seen them at #ReactRally the year before and deployed a Gatsby site to Netlify already.

Netlify was very easy to setup and link to my GitHub account you select a repo and pretty much with very little configuration you have a live site that will deploy every time you push to master.

With the selection of these tools I was able to build out my application, connect it to a realtime database, and deploy to a live environment all with $0 spent.

If you're looking to build out a small app I suggest giving these tools a go as you can get your idea out into the real world for absolutely no cost.

Our whole DevOps stack consists of the following tools:

• GitHub (incl. GitHub Pages/Markdown for Documentation, GettingStarted and HowTo's) for collaborative review and code management tool
• Respectively Git as revision control system
• SourceTree as Git GUI
• Visual Studio Code as IDE
• CircleCI for continuous integration (automatize development process)
• Prettier / TSLint / ESLint as code linter
• SonarQube as quality gate
• Docker as container management (incl. Docker Compose for multi-container application management)
• VirtualBox for operating system simulation tests
• Kubernetes as cluster management for docker containers
• Heroku for deploying in test environments
• nginx as web server (preferably used as facade server in production environment)
• SSLMate (using OpenSSL) for certificate management
• Amazon EC2 (incl. Amazon S3) for deploying in stage (production-like) and production environments
• PostgreSQL as preferred database system
• Redis as preferred in-memory database/store (great for caching)

The main reason we have chosen Kubernetes over Docker Swarm is related to the following artifacts:

• Key features: Easy and flexible installation, Clear dashboard, Great scaling operations, Monitoring is an integral part, Great load balancing concepts, Monitors the condition and ensures compensation in the event of failure.
• Applications: An application can be deployed using a combination of pods, deployments, and services (or micro-services).
• Functionality: Kubernetes as a complex installation and setup process, but it not as limited as Docker Swarm.
• Monitoring: It supports multiple versions of logging and monitoring when the services are deployed within the cluster (Elasticsearch/Kibana (ELK), Heapster/Grafana, Sysdig cloud integration).
• Scalability: All-in-one framework for distributed systems.
• Other Benefits: Kubernetes is backed by the Cloud Native Computing Foundation (CNCF), huge community among container orchestration tools, it is an open source and modular tool that works with any OS.

I have mixed feelings on GitHub as a product and our use of it for the Zulip open source project. On the one hand, I do feel that being on GitHub helps people discover Zulip, because we have enough stars (etc.) that we rank highly among projects on the platform. and there is a definite benefit for lowering barriers to contribution (which is important to us) that GitHub has such a dominant position in terms of what everyone has accounts with.

But even ignoring how one might feel about their new corporate owner (MicroSoft), in a lot of ways GitHub is a bad product for open source projects. Years after the "Dear GitHub" letter, there are still basic gaps in its issue tracker:

• You can't give someone permission to label/categorize issues without full write access to a project (including ability to merge things to master, post releases, etc.).
• You can't let anyone with a GitHub account self-assign issues to themselves.
• Many more similar issues.

It's embarrassing, because I've talked to GitHub product managers at various open source events about these things for 3 years, and they always agree the thing is important, but then nothing ever improves in the Issues product. Maybe the new management at MicroSoft will fix their product management situation, but if not, I imagine we'll eventually do the migration to GitLab.

We have a custom bot project, http://github.com/zulip/zulipbot, to deal with some of these issues where possible, and every other large project we talk to does the same thing, more or less.

We use GitLab CI because of the great native integration as a part of the GitLab framework and the linting-capabilities it offers. The visualization of complex pipelines and the embedding within the project overview made Gitlab CI even more convenient. We use it for all projects, all deployments and as a part of GitLab Pages.

While we initially used the Shell-executor, we quickly switched to the Docker-executor and use it exclusively now.

We formerly used Jenkins but preferred to handle everything within GitLab . Aside from the unification of our infrastructure another motivation was the "configuration-in-file"-approach, that Gitlab CI offered, while Jenkins support of this concept was very limited and users had to resort to using the webinterface. Since the file is included within the repository, it is also version controlled, which was a huge plus for us.

I use GitLab when building side-projects and MVPs. The interface and interactions are close enough to those of GitHub to prevent cognitive switching costs between professional and personal projects hosted on different services.

GitLab also provides a suite of tools including issue/project management, CI/CD with GitLab CI, and validation/landing pages with GitLab Pages. With everything in one place, on an #OpenSourceCloud GitLab makes it easy for me to manage much larger projects on my own, than would be possible with other solutions or tools.

It's petty I know, but I can also read the GitLab code diffs far more easily than diffs on GitHub or Bitbucket...they just look better in my opinion.

A bit difference in GitHub and GitLab though both are Version Control repository management services which provides key component in the software development workflow. A decision of choosing GitHub over GitLab is major leap extension from code management, to deployment and monitoring alongside looking beyond the code base hosting provided best fitted tools for developer communities.

• Authentication stages - With GitLab you can set and modify people’s permissions according to their role. In GitHub, you can decide if someone gets a read or write access to a repository.
• Built-In Continuous Integrations - GitLab offers its very own CI for free. No need to use an external CI service. And if you are already used to an external CI, you can obviously integrate with Jenkins, etc whereas GitHub offers various 3rd party integrations – such as Travis CI, CircleCI or Codeship – for running and testing your code. However, there’s no built-in CI solution at the moment.
• Import/Export Resources - GitLab offers detailed documentation on how to import your data from other vendors – such as GitHub, Bitbucket to GitLab. GitHub, on the other hand, does not offer such detailed documentation for the most common git repositories. However, GitHub offers to use GitHub Importer if you have your source code in Subversion, Mercurial, TFS and others.

Also when it comes to exporting data, GitLab seems to do a pretty solid job, offering you the ability to export your projects including the following data:

• Wiki and project repositories
• Project uploads
• The configuration including webhooks and services
• Issues with comments, merge requests with diffs and comments, labels, milestones, snippets, and other project entities.

GitHub, on the other hand, seems to be more restrictive when it comes to export features of existing GitHub repositories. * Integrations - #githubmarketplace gives you an essence to have multiple and competitive integrations whereas you will find less in the GitLab.

So go ahead with better understanding.