What is Atlassian Stash and what are its top alternatives?
Atlassian Stash, now known as Bitbucket Server, is a Git repository management solution designed for enterprises. It allows teams to securely store and collaborate on code, with features such as pull requests, branching strategies, and integration with JIRA Software. However, some limitations include the need for a license fee for more than 5 users, limited support for large-scale deployments, and a potentially steep learning curve for new users.
- GitLab: GitLab is a robust DevOps platform that includes Git repository management, CI/CD pipelines, and a project management tool. Key features include code review, issue tracking, and built-in CI/CD pipelines. Pros include a free tier for unlimited users, while cons may include a more complex setup compared to Atlassian Stash.
- GitHub: GitHub is a popular platform for hosting Git repositories and collaborating on code. Key features include pull requests, code review, and integrations with various third-party tools. Pros include a large community and marketplace, while cons may include limitations on private repositories for free accounts.
- Bitbucket: Bitbucket is Atlassian's cloud-based Git repository hosting service, providing similar features to Stash. Key features include pull requests, branching strategies, and integration with JIRA. Pros include seamless integration with other Atlassian products, while cons may include limitations on the free tier.
- GitKraken: GitKraken is a cross-platform Git client with a visually appealing interface and powerful collaboration features. Key features include seamless Git integration, code visualization, and integrations with popular services. Pros include a free tier for individuals, while cons may include a steeper learning curve compared to Stash.
- Azure DevOps: Azure DevOps is a comprehensive DevOps platform that includes Git repository hosting, CI/CD pipelines, and project management tools. Key features include code collaboration, automated testing, and deployment pipelines. Pros include seamless integration with Microsoft services, while cons may include a potentially higher cost compared to Stash.
- SourceTree: SourceTree is a free Git client with an intuitive interface for managing and collaborating on code. Key features include Git-flow support, branching strategies, and visual diff tools. Pros include a user-friendly interface, while cons may include limited advanced features compared to Stash.
- Perforce: Perforce is a version control system designed for enterprises with a focus on large-scale development and collaboration. Key features include robust branching and merging capabilities, high performance, and scalability. Pros include support for large teams and complex workflows, while cons may include a potentially higher cost compared to Stash.
- Plastic SCM: Plastic SCM is a distributed version control system that offers high performance and scalability for teams of all sizes. Key features include branching visualization, code review, and Git integration. Pros include a user-friendly interface, while cons may include limitations on the free version compared to Stash.
- GitBucket: GitBucket is an open-source Git platform that provides a lightweight alternative to Atlassian Stash. Key features include pull requests, issue tracking, and user management. Pros include being open-source and customizable, while cons may include potential limitations on features compared to Stash.
- Gitea: Gitea is a self-hosted Git service that offers a lightweight and easy-to-use alternative to Atlassian Stash. Key features include code collaboration, issue tracking, and integration with various third-party services. Pros include being open-source and lightweight, while cons may include potential limitations on scalability compared to Stash.
Top Alternatives to Atlassian Stash
- Bitbucket
Bitbucket gives teams one place to plan projects, collaborate on code, test and deploy, all with free private Git repositories. Teams choose Bitbucket because it has a superior Jira integration, built-in CI/CD, & is free for up to 5 users. ...
- GitHub
GitHub is the best place to share code with friends, co-workers, classmates, and complete strangers. Over three million people use GitHub to build amazing things together. ...
- GitHub Enterprise
GitHub Enterprise lets developers use the tools they love across the development process with support for popular IDEs, continuous integration tools, and hundreds of third party apps and services. ...
- GitLab
GitLab offers git repository management, code reviews, issue tracking, activity feeds and wikis. Enterprises install GitLab on-premise and connect it with LDAP and Active Directory servers for secure authentication and authorization. A single GitLab server can handle more than 25,000 users but it is also possible to create a high availability setup with multiple active servers. ...
- SourceTree
Use the full capability of Git and Mercurial in the SourceTree desktop app. Manage all your repositories, hosted or local, through SourceTree's simple interface. ...
- JavaScript
JavaScript is most known as the scripting language for Web pages, but used in many non-browser environments as well such as node.js or Apache CouchDB. It is a prototype-based, multi-paradigm scripting language that is dynamic,and supports object-oriented, imperative, and functional programming styles. ...
- Git
Git is a free and open source distributed version control system designed to handle everything from small to very large projects with speed and efficiency. ...
- Python
Python is a general purpose programming language created by Guido Van Rossum. Python is most praised for its elegant syntax and readable code, if you are just beginning your programming career python suits you best. ...
Atlassian Stash alternatives & related posts
Bitbucket
- Free private repos904
- Simple setup397
- Nice ui and tools348
- Unlimited private repositories341
- Affordable git hosting240
- Integrates with many apis and services123
- Reliable uptime119
- Nice gui87
- Pull requests and code reviews85
- Very customisable58
- Mercurial repositories16
- SourceTree integration14
- JIRA integration12
- Track every commit to an issue in JIRA10
- Deployment hooks8
- Best free alternative to Github8
- Automatically share repositories with all your teammates7
- Compatible with Mac and Windows7
- Source Code Insight6
- Price6
- Login with Google5
- Create a wiki5
- Approve pull request button5
- Customizable pipelines4
- #2 Atlassian Product after JIRA4
- Also supports Mercurial3
- Unlimited Private Repos at no cost3
- Continuous Integration and Delivery3
- Academic license program2
- Multilingual interface2
- Teamcity2
- Open source friendly2
- Issues tracker2
- IAM2
- IAM integration2
- Mercurial Support2
- Not much community activity19
- Difficult to review prs because of confusing ui17
- Quite buggy15
- Managed by enterprise Java company10
- CI tool is not free of charge8
- Complexity with rights management7
- Only 5 collaborators for private repos6
- Slow performance4
- No AWS Codepipelines integration2
- No more Mercurial repositories1
- No server side git-hook support1
related Bitbucket posts
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.
GitHub
- Open source friendly1.8K
- Easy source control1.5K
- Nice UI1.3K
- Great for team collaboration1.1K
- Easy setup867
- Issue tracker504
- Great community486
- Remote team collaboration482
- Great way to share451
- Pull request and features planning442
- Just works147
- Integrated in many tools132
- Free Public Repos121
- Github Gists116
- Github pages112
- Easy to find repos83
- Open source62
- It's free60
- Easy to find projects60
- Network effect56
- Extensive API49
- Organizations43
- Branching42
- Developer Profiles34
- Git Powered Wikis32
- Great for collaboration30
- It's fun24
- Clean interface and good integrations23
- Community SDK involvement22
- Learn from others source code20
- Because: Git16
- It integrates directly with Azure14
- Standard in Open Source collab10
- Newsfeed10
- It integrates directly with Hipchat8
- Fast8
- Beautiful user experience8
- Easy to discover new code libraries7
- Smooth integration6
- Cloud SCM6
- Nice API6
- Graphs6
- Integrations6
- It's awesome6
- Quick Onboarding5
- Reliable5
- Remarkable uptime5
- CI Integration5
- Hands down best online Git service available5
- Uses GIT4
- Version Control4
- Simple but powerful4
- Unlimited Public Repos at no cost4
- Free HTML hosting4
- Security options4
- Loved by developers4
- Easy to use and collaborate with others4
- Ci3
- IAM3
- Nice to use3
- Easy deployment via SSH3
- Easy to use2
- Leads the copycats2
- All in one development service2
- Free private repos2
- Free HTML hostings2
- Easy and efficient maintainance of the projects2
- Beautiful2
- Easy source control and everything is backed up2
- IAM integration2
- Very Easy to Use2
- Good tools support2
- Issues tracker2
- Never dethroned2
- Self Hosted2
- Dasf1
- Profound1
- Owned by micrcosoft53
- Expensive for lone developers that want private repos37
- Relatively slow product/feature release cadence15
- API scoping could be better10
- Only 3 collaborators for private repos8
- Limited featureset for issue management3
- GitHub Packages does not support SNAPSHOT versions2
- Does not have a graph for showing history like git lens2
- No multilingual interface1
- Takes a long time to commit1
- Expensive1
related GitHub posts
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.
StackShare Feed is built entirely with React, Glamorous, and Apollo. One of our objectives with the public launch of the Feed was to enable a Server-side rendered (SSR) experience for our organic search traffic. When you visit the StackShare Feed, and you aren't logged in, you are delivered the Trending feed experience. We use an in-house Node.js rendering microservice to generate this HTML. This microservice needs to run and serve requests independent of our Rails web app. Up until recently, we had a mono-repo with our Rails and React code living happily together and all served from the same web process. In order to deploy our SSR app into a Heroku environment, we needed to split out our front-end application into a separate repo in GitHub. The driving factor in this decision was mostly due to limitations imposed by Heroku specifically with how processes can't communicate with each other. A new SSR app was created in Heroku and linked directly to the frontend repo so it stays in-sync with changes.
Related to this, we need a way to "deploy" our frontend changes to various server environments without building & releasing the entire Ruby application. We built a hybrid Amazon S3 Amazon CloudFront solution to host our Webpack bundles. A new CircleCI script builds the bundles and uploads them to S3. The final step in our rollout is to update some keys in Redis so our Rails app knows which bundles to serve. The result of these efforts were significant. Our frontend team now moves independently of our backend team, our build & release process takes only a few minutes, we are now using an edge CDN to serve JS assets, and we have pre-rendered React pages!
#StackDecisionsLaunch #SSR #Microservices #FrontEndRepoSplit
GitHub Enterprise
- Expensive - $$$4
- Code security2
- CDCI with Github Actions2
- Both Cloud and Enterprise Server Versions available1
- Draft Pull Request1
- User experience0
- $$$2
related GitHub Enterprise posts
Hi all,
I would like some information regarding the benefits an aspiring start-up company may have, while using GitHub Enterprise vs the regular GitHub package. On a separate issue, I'd like to understand whether GitLab may have some DevOps-related advantages GitHub does not.
Thank you in advance, Matt
We are using a Bitbucket server, and due to migration efforts and new Atlassian community license changes, we need to move to a new self-hosted solution. The new data-center license for Atlassian, available in February, will be community provisioned (free). Along with that community license, other technologies will be coming with it (Crucible, Confluence, and Jira). Is there value in a paid-for license to get the GitHub Enterprise? Are the tools that come with it worth the cost?
I know it is about $20 per 10 seats, and we have about 300 users. Have other convertees to Microsoft's tools found it easy to do a migration? Is the toolset that much more beneficial to the free suite that one can get from Atlassian?
So far, free seems to be the winner, and the familiarization with Atlassian implementation and maintenance is understood. Going to GitHub, are there any distinct challenges to be found or any perks to be attained?
- Self hosted508
- Free430
- Has community edition339
- Easy setup242
- Familiar interface240
- Includes many features, including ci137
- Nice UI113
- Good integration with gitlabci84
- Simple setup57
- Has an official mobile app34
- Free private repository34
- Continuous Integration31
- Open source, great ui (like github)22
- Slack Integration18
- Full CI flow15
- Free and unlimited private git repos11
- User, group, and project access management is simple10
- All in one (Git, CI, Agile..)9
- Built-in CI8
- Intuitive UI8
- Full DevOps suite with Git6
- Both public and private Repositories6
- So easy to use5
- CI5
- Integrated Docker Registry5
- It's powerful source code management tool5
- Build/pipeline definition alongside code5
- Issue system4
- Dockerized4
- Unlimited free repos & collaborators4
- Security and Stable4
- On-premises4
- It's fully integrated4
- Mattermost Chat client4
- Excellent4
- Great for team collaboration3
- Built-in Docker Registry3
- Low maintenance cost due omnibus-deployment3
- I like the its runners and executors feature3
- Free private repos3
- Because is the best remote host for git repositories3
- Not Microsoft Owned3
- Opensource3
- Groups of groups2
- Powerful software planning and maintaining tools2
- Review Apps feature2
- Kubernetes integration with GitLab CI2
- It includes everything I need, all packaged with docker2
- Multilingual interface2
- HipChat intergration2
- Powerful Continuous Integration System2
- One-click install through DigitalOcean2
- The dashboard with deployed environments2
- Native CI2
- Many private repo2
- Kubernetes Integration2
- Published IP list for whitelisting (gl-infra#434)2
- Wounderful2
- Beautiful2
- Supports Radius/Ldap & Browser Code Edits1
- Slow ui performance28
- Introduce breaking bugs every release8
- Insecure (no published IP list for whitelisting)6
- Built-in Docker Registry2
- Review Apps feature1
related GitLab posts
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.
- Visual history and branch view205
- Beautiful UI164
- Easy repository browsing134
- Gitflow support87
- Interactive stage or discard by hunks or lines75
- Great branch visualization22
- Ui/ux and user-friendliness18
- Best Git Client UI/Features8
- Search commit messages7
- Available for Windows and macOS5
- Log only one file1
- Search file content1
- Crashes often12
- So many bugs8
- Fetching is slow sometimes7
- No dark theme (Windows)5
- Extremely slow5
- Very unstable5
- Can't select text in diff (windows)4
- Freezes quite frequently3
- Can't scale window from top corners3
- UI blinking2
- Windows version worse than mac version2
- Installs to AppData folder (windows)2
- Diff makes tab indentation look like spaces2
- Windows and Mac versions are very different2
- Diff appears as if space indented even if its tabs2
- Doesn't have an option for git init2
- Useless for merge conflict resolution2
- Doesn't differentiate submodules from parent repos2
- Requires bitbucket account2
- Generally hard to like1
- No reflog support1
- Bases binary check on filesize1
- Can't add remotes by right clicking remotes (windows)1
related SourceTree posts
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.
Tower appears to be between GitKraken and SourceTree in detail, but gave two scary error dialogs when attempting to merge resulted in a conflict. Doing the same in SourceTree just worked and showed the conflict in its handy file view that's always visible (unlike Tower's mere "Merge branch 'X' into develop" message when the commit is selected).
Both GitKraken and Tower lack the commit hash in their history overview, requiring one to select a commit to see it.
GitKraken appears to be the only Windows 10 Git GUI suitable for night shifts, but like Tower is only free for 30 days, unlike SourceTree.
JavaScript
- Can be used on frontend/backend1.7K
- It's everywhere1.5K
- Lots of great frameworks1.2K
- Fast897
- Light weight745
- Flexible425
- You can't get a device today that doesn't run js392
- Non-blocking i/o286
- Ubiquitousness237
- Expressive191
- Extended functionality to web pages55
- Relatively easy language49
- Executed on the client side46
- Relatively fast to the end user30
- Pure Javascript25
- Functional programming21
- Async15
- Full-stack13
- Setup is easy12
- Future Language of The Web12
- Its everywhere12
- Because I love functions11
- JavaScript is the New PHP11
- Like it or not, JS is part of the web standard10
- Expansive community9
- Everyone use it9
- Can be used in backend, frontend and DB9
- Easy9
- Most Popular Language in the World8
- Powerful8
- Can be used both as frontend and backend as well8
- For the good parts8
- No need to use PHP8
- Easy to hire developers8
- Agile, packages simple to use7
- Love-hate relationship7
- Photoshop has 3 JS runtimes built in7
- Evolution of C7
- It's fun7
- Hard not to use7
- Versitile7
- Its fun and fast7
- Nice7
- Popularized Class-Less Architecture & Lambdas7
- Supports lambdas and closures7
- It let's me use Babel & Typescript6
- Can be used on frontend/backend/Mobile/create PRO Ui6
- 1.6K Can be used on frontend/backend6
- Client side JS uses the visitors CPU to save Server Res6
- Easy to make something6
- Clojurescript5
- Promise relationship5
- Stockholm Syndrome5
- Function expressions are useful for callbacks5
- Scope manipulation5
- Everywhere5
- Client processing5
- What to add5
- Because it is so simple and lightweight4
- Only Programming language on browser4
- Test1
- Hard to learn1
- Test21
- Not the best1
- Easy to understand1
- Subskill #41
- Easy to learn1
- Hard 彤0
- A constant moving target, too much churn22
- Horribly inconsistent20
- Javascript is the New PHP15
- No ability to monitor memory utilitization9
- Shows Zero output in case of ANY error8
- Thinks strange results are better than errors7
- Can be ugly6
- No GitHub3
- Slow2
related JavaScript posts
Oof. I have truly hated JavaScript for a long time. Like, for over twenty years now. Like, since the Clinton administration. It's always been a nightmare to deal with all of the aspects of that silly language.
But wowza, things have changed. Tooling is just way, way better. I'm primarily web-oriented, and using React and Apollo together the past few years really opened my eyes to building rich apps. And I deeply apologize for using the phrase rich apps; I don't think I've ever said such Enterprisey words before.
But yeah, things are different now. I still love Rails, and still use it for a lot of apps I build. But it's that silly rich apps phrase that's the problem. Users have way more comprehensive expectations than they did even five years ago, and the JS community does a good job at building tools and tech that tackle the problems of making heavy, complicated UI and frontend work.
Obviously there's a lot of things happening here, so just saying "JavaScript isn't terrible" might encompass a huge amount of libraries and frameworks. But if you're like me, yeah, give things another shot- I'm somehow not hating on JavaScript anymore and... gulp... I kinda love it.
How Uber developed the open source, end-to-end distributed tracing Jaeger , now a CNCF project:
Distributed tracing is quickly becoming a must-have component in the tools that organizations use to monitor their complex, microservice-based architectures. At Uber, our open source distributed tracing system Jaeger saw large-scale internal adoption throughout 2016, integrated into hundreds of microservices and now recording thousands of traces every second.
Here is the story of how we got here, from investigating off-the-shelf solutions like Zipkin, to why we switched from pull to push architecture, and how distributed tracing will continue to evolve:
https://eng.uber.com/distributed-tracing/
(GitHub Pages : https://www.jaegertracing.io/, GitHub: https://github.com/jaegertracing/jaeger)
Bindings/Operator: Python Java Node.js Go C++ Kubernetes JavaScript OpenShift C# Apache Spark
- Distributed version control system1.4K
- Efficient branching and merging1.1K
- Fast959
- Open source845
- Better than svn726
- Great command-line application368
- Simple306
- Free291
- Easy to use232
- Does not require server222
- Distributed27
- Small & Fast22
- Feature based workflow18
- Staging Area15
- Most wide-spread VSC13
- Role-based codelines11
- Disposable Experimentation11
- Frictionless Context Switching7
- Data Assurance6
- Efficient5
- Just awesome4
- Github integration3
- Easy branching and merging3
- Compatible2
- Flexible2
- Possible to lose history and commits2
- Rebase supported natively; reflog; access to plumbing1
- Light1
- Team Integration1
- Fast, scalable, distributed revision control system1
- Easy1
- Flexible, easy, Safe, and fast1
- CLI is great, but the GUI tools are awesome1
- It's what you do1
- Phinx0
- Hard to learn16
- Inconsistent command line interface11
- Easy to lose uncommitted work9
- Worst documentation ever possibly made7
- Awful merge handling5
- Unexistent preventive security flows3
- Rebase hell3
- When --force is disabled, cannot rebase2
- Ironically even die-hard supporters screw up badly2
- Doesn't scale for big data1
related Git posts
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.
Often enough I have to explain my way of going about setting up a CI/CD pipeline with multiple deployment platforms. Since I am a bit tired of yapping the same every single time, I've decided to write it up and share with the world this way, and send people to read it instead ;). I will explain it on "live-example" of how the Rome got built, basing that current methodology exists only of readme.md and wishes of good luck (as it usually is ;)).
It always starts with an app, whatever it may be and reading the readmes available while Vagrant and VirtualBox is installing and updating. Following that is the first hurdle to go over - convert all the instruction/scripts into Ansible playbook(s), and only stopping when doing a clear vagrant up
or vagrant reload
we will have a fully working environment. As our Vagrant environment is now functional, it's time to break it! This is the moment to look for how things can be done better (too rigid/too lose versioning? Sloppy environment setup?) and replace them with the right way to do stuff, one that won't bite us in the backside. This is the point, and the best opportunity, to upcycle the existing way of doing dev environment to produce a proper, production-grade product.
I should probably digress here for a moment and explain why. I firmly believe that the way you deploy production is the same way you should deploy develop, shy of few debugging-friendly setting. This way you avoid the discrepancy between how production work vs how development works, which almost always causes major pains in the back of the neck, and with use of proper tools should mean no more work for the developers. That's why we start with Vagrant as developer boxes should be as easy as vagrant up
, but the meat of our product lies in Ansible which will do meat of the work and can be applied to almost anything: AWS, bare metal, docker, LXC, in open net, behind vpn - you name it.
We must also give proper consideration to monitoring and logging hoovering at this point. My generic answer here is to grab Elasticsearch, Kibana, and Logstash. While for different use cases there may be better solutions, this one is well battle-tested, performs reasonably and is very easy to scale both vertically (within some limits) and horizontally. Logstash rules are easy to write and are well supported in maintenance through Ansible, which as I've mentioned earlier, are at the very core of things, and creating triggers/reports and alerts based on Elastic and Kibana is generally a breeze, including some quite complex aggregations.
If we are happy with the state of the Ansible it's time to move on and put all those roles and playbooks to work. Namely, we need something to manage our CI/CD pipelines. For me, the choice is obvious: TeamCity. It's modern, robust and unlike most of the light-weight alternatives, it's transparent. What I mean by that is that it doesn't tell you how to do things, doesn't limit your ways to deploy, or test, or package for that matter. Instead, it provides a developer-friendly and rich playground for your pipelines. You can do most the same with Jenkins, but it has a quite dated look and feel to it, while also missing some key functionality that must be brought in via plugins (like quality REST API which comes built-in with TeamCity). It also comes with all the common-handy plugins like Slack or Apache Maven integration.
The exact flow between CI and CD varies too greatly from one application to another to describe, so I will outline a few rules that guide me in it: 1. Make build steps as small as possible. This way when something breaks, we know exactly where, without needing to dig and root around. 2. All security credentials besides development environment must be sources from individual Vault instances. Keys to those containers should exist only on the CI/CD box and accessible by a few people (the less the better). This is pretty self-explanatory, as anything besides dev may contain sensitive data and, at times, be public-facing. Because of that appropriate security must be present. TeamCity shines in this department with excellent secrets-management. 3. Every part of the build chain shall consume and produce artifacts. If it creates nothing, it likely shouldn't be its own build. This way if any issue shows up with any environment or version, all developer has to do it is grab appropriate artifacts to reproduce the issue locally. 4. Deployment builds should be directly tied to specific Git branches/tags. This enables much easier tracking of what caused an issue, including automated identifying and tagging the author (nothing like automated regression testing!).
Speaking of deployments, I generally try to keep it simple but also with a close eye on the wallet. Because of that, I am more than happy with AWS or another cloud provider, but also constantly peeking at the loads and do we get the value of what we are paying for. Often enough the pattern of use is not constantly erratic, but rather has a firm baseline which could be migrated away from the cloud and into bare metal boxes. That is another part where this approach strongly triumphs over the common Docker and CircleCI setup, where you are very much tied in to use cloud providers and getting out is expensive. Here to embrace bare-metal hosting all you need is a help of some container-based self-hosting software, my personal preference is with Proxmox and LXC. Following that all you must write are ansible scripts to manage hardware of Proxmox, similar way as you do for Amazon EC2 (ansible supports both greatly) and you are good to go. One does not exclude another, quite the opposite, as they can live in great synergy and cut your costs dramatically (the heavier your base load, the bigger the savings) while providing production-grade resiliency.
Python
- Great libraries1.2K
- Readable code961
- Beautiful code846
- Rapid development787
- Large community689
- Open source435
- Elegant393
- Great community282
- Object oriented272
- Dynamic typing220
- Great standard library77
- Very fast59
- Functional programming55
- Easy to learn49
- Scientific computing45
- Great documentation35
- Productivity29
- Easy to read28
- Matlab alternative28
- Simple is better than complex23
- It's the way I think20
- Imperative19
- Free18
- Very programmer and non-programmer friendly18
- Powerfull language17
- Machine learning support17
- Fast and simple16
- Scripting14
- Explicit is better than implicit12
- Ease of development11
- Clear and easy and powerfull10
- Unlimited power9
- It's lean and fun to code8
- Import antigravity8
- Print "life is short, use python"7
- Python has great libraries for data processing7
- Although practicality beats purity6
- Flat is better than nested6
- Great for tooling6
- Rapid Prototyping6
- Readability counts6
- High Documented language6
- I love snakes6
- Fast coding and good for competitions6
- There should be one-- and preferably only one --obvious6
- Now is better than never6
- Great for analytics5
- Lists, tuples, dictionaries5
- Easy to learn and use4
- Simple and easy to learn4
- Easy to setup and run smooth4
- Web scraping4
- CG industry needs4
- Socially engaged community4
- Complex is better than complicated4
- Multiple Inheritence4
- Beautiful is better than ugly4
- Plotting4
- If the implementation is hard to explain, it's a bad id3
- Special cases aren't special enough to break the rules3
- Pip install everything3
- List comprehensions3
- No cruft3
- Generators3
- Import this3
- It is Very easy , simple and will you be love programmi3
- Many types of collections3
- If the implementation is easy to explain, it may be a g3
- Batteries included2
- Should START with this but not STICK with This2
- Powerful language for AI2
- Can understand easily who are new to programming2
- Flexible and easy2
- Good for hacking2
- A-to-Z2
- Because of Netflix2
- Only one way to do it2
- Better outcome2
- Sexy af1
- Slow1
- Securit1
- Ni0
- Powerful0
- Still divided between python 2 and python 353
- Performance impact28
- Poor syntax for anonymous functions26
- GIL22
- Package management is a mess19
- Too imperative-oriented14
- Hard to understand12
- Dynamic typing12
- Very slow12
- Indentations matter a lot8
- Not everything is expression8
- Incredibly slow7
- Explicit self parameter in methods7
- Requires C functions for dynamic modules6
- Poor DSL capabilities6
- No anonymous functions6
- Fake object-oriented programming5
- Threading5
- The "lisp style" whitespaces5
- Official documentation is unclear.5
- Hard to obfuscate5
- Circular import5
- Lack of Syntax Sugar leads to "the pyramid of doom"4
- The benevolent-dictator-for-life quit4
- Not suitable for autocomplete4
- Meta classes2
- Training wheels (forced indentation)1
related Python posts
How Uber developed the open source, end-to-end distributed tracing Jaeger , now a CNCF project:
Distributed tracing is quickly becoming a must-have component in the tools that organizations use to monitor their complex, microservice-based architectures. At Uber, our open source distributed tracing system Jaeger saw large-scale internal adoption throughout 2016, integrated into hundreds of microservices and now recording thousands of traces every second.
Here is the story of how we got here, from investigating off-the-shelf solutions like Zipkin, to why we switched from pull to push architecture, and how distributed tracing will continue to evolve:
https://eng.uber.com/distributed-tracing/
(GitHub Pages : https://www.jaegertracing.io/, GitHub: https://github.com/jaegertracing/jaeger)
Bindings/Operator: Python Java Node.js Go C++ Kubernetes JavaScript OpenShift C# Apache Spark
Winds 2.0 is an open source Podcast/RSS reader developed by Stream with a core goal to enable a wide range of developers to contribute.
We chose JavaScript because nearly every developer knows or can, at the very least, read JavaScript. With ES6 and Node.js v10.x.x, it’s become a very capable language. Async/Await is powerful and easy to use (Async/Await vs Promises). Babel allows us to experiment with next-generation JavaScript (features that are not in the official JavaScript spec yet). Yarn allows us to consistently install packages quickly (and is filled with tons of new tricks)
We’re using JavaScript for everything – both front and backend. Most of our team is experienced with Go and Python, so Node was not an obvious choice for this app.
Sure... there will be haters who refuse to acknowledge that there is anything remotely positive about JavaScript (there are even rants on Hacker News about Node.js); however, without writing completely in JavaScript, we would not have seen the results we did.
#FrameworksFullStack #Languages