What is Apache Maven and what are its top alternatives?
Apache Maven is a build automation tool primarily used for Java projects. It provides a way to standardize project structure, manage dependencies, and automate the build process. Key features include declarative build scripts, dependency management, plugin architecture, and integration with continuous integration tools like Jenkins. However, Maven can be complex to configure, especially for beginners, and it relies heavily on XML for configuration, which some developers find cumbersome.
- Gradle: Gradle is a build automation tool that offers a more flexible and efficient build system compared to Maven. It uses Groovy or Kotlin DSL for build scripts, provides excellent dependency management, and supports incremental builds. Pros include faster build times and better performance, but it may have a steeper learning curve compared to Maven.
- Ant: Apache Ant is a Java-based build tool that focuses on flexibility and customizability. It uses XML for build scripts and is known for its simplicity. Pros include fine-grained control over the build process, but it lacks many features found in Maven, such as dependency management.
- Bazel: Bazel is a build tool from Google that emphasizes performance and reproducibility. It uses a language-agnostic syntax for build files and supports large-scale builds. Pros include fast and reliable builds, built-in support for multiple languages, and caching for incremental builds.
- Buildr: Apache Buildr is a build automation tool that simplifies building, testing, and packaging Java applications. It uses Ruby DSL for build scripts and provides a higher level of abstraction compared to Maven. Pros include ease of use and integration with popular IDEs, but it may not have as extensive plugin support as Maven.
- Pants: Pants is a build system designed for scaling and performance, particularly in large codebases. It supports various languages, including Java, Python, and Scala, and provides features like incremental compilation and distributed caching. Pros include fast builds, support for monorepos, and fine-grained dependency management.
- SCons: SCons is a software construction tool written in Python that focuses on extensibility and automation. It uses Python scripts for build files and offers a high level of customization. Pros include ease of use for Python developers, but it may lack some features found in more specialized build tools like Maven.
- CMake: CMake is a cross-platform build system that generates native build files for different platforms and IDEs. It uses a simple scripting language and supports C, C++, and Fortran projects. Pros include platform independence, integrated testing support, and compatibility with various tools, but it may not offer as much built-in functionality for Java projects compared to Maven.
- Buck: Buck is a build system developed by Facebook that focuses on speed and incremental builds. It uses a domain-specific language for build files and supports multiple languages, including Java and Android. Pros include fast builds, fine-grained dependency management, and integration with popular IDEs, but it may require more manual configuration compared to Maven.
- SBuild: SBuild is a Scala-based build tool that offers a concise and expressive syntax for defining build configurations. It is designed to be flexible, modular, and extensible, with built-in support for dependency management and parallel builds. Pros include simplicity, Scala integration, and plugin ecosystem, but it may have a smaller community compared to Maven.
- Make: Make is a classic build tool for automating the build process of software projects. It uses makefiles to specify dependency relationships and build targets. Pros include simplicity and widespread adoption, but it may lack the features and extensibility of more modern build tools like Maven.
Top Alternatives to Apache Maven
- Jira
Jira's secret sauce is the way it simplifies the complexities of software development into manageable units of work. Jira comes out-of-the-box with everything agile teams need to ship value to customers faster. ...
- Jenkins
In a nutshell Jenkins CI is the leading open-source continuous integration server. Built with Java, it provides over 300 plugins to support building and testing virtually any project. ...
- Gradle
Gradle is a build tool with a focus on build automation and support for multi-language development. If you are building, testing, publishing, and deploying software on any platform, Gradle offers a flexible model that can support the entire development lifecycle from compiling and packaging code to publishing web sites. ...
- Apache Ant
Ant is a Java-based build tool. In theory, it is kind of like Make, without Make's wrinkles and with the full portability of pure Java code. ...
- Apache Tomcat
Apache Tomcat powers numerous large-scale, mission-critical web applications across a diverse range of industries and organizations. ...
- Eclipse
Standard Eclipse package suited for Java and plug-in development plus adding new plugins; already includes Git, Marketplace Client, source code and developer documentation. Click here to file a bug against Eclipse Platform. ...
- 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. ...
- 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. ...
Apache Maven alternatives & related posts
Jira
- Powerful310
- Flexible254
- Easy separation of projects149
- Run in the cloud113
- Code integration105
- Easy to use58
- Run on your own53
- Great customization39
- Easy Workflow Configuration39
- REST API27
- Great Agile Management tool12
- Integrates with virtually everything7
- Confluence6
- Complicated6
- Sentry Issues Integration3
- It's awesome2
- Rather expensive8
- Large memory requirement5
- Slow2
- Cloud or Datacenter only1
related Jira posts
So I am a huge fan of JIRA like #massive I used it for many many years, and really loved it, used it personally and at work. I would suggest every new workplace that I worked at to switch to JIRA instead of what I was using.
When I started at #StackShare we were using a Trello #Kanban board and I was so shocked at how easy the workflow was to follow, create new tasks and get tasks QA'd and deployed. What was so great about this was it didn't come with all the complexity of JIRA. Like setting up a project, user rules etc. You are able to hit the ground running with Trello and get tasks started right away without being overwhelmed with the complexity of options in JIRA
With a few TrelloPowerUps we were easily able to add GitHub integration and storyPoints to our cards and thats all we needed to get a really nice agile workflow going.
I'm not saying that JIRA is not useful, I can see larger companies being able to use the JIRA features and have the time to go through all the complex setup to get a really good workflow going. But for smaller #Startups that want to hit the ground running Trello for me is the way to go.
In saying that what I would love Trello to implement is to allow me to create custom fields. Right now we just have a Description
field. So I am adding User Stories
& How To Test
in the Markdown of the Description
if I could have these as custom fields then my #Agile workflow would be complete.
#StackDecisionsLaunch
Last time we shared there information about our decision about using YouTrack over Jira actually we found much better solution that our team have loved. Linear is a minimalistic issue tracker that integrates well with Sentry, GitHub, Slack and Figma which are our basic tools. I would like to recommend checking out Linear as a potential alternative to "heavy" issue trackers, maybe at enterprises that may not work but when we're a startup that works awesome!
- Hosted internally523
- Free open source469
- Great to build, deploy or launch anything async318
- Tons of integrations243
- Rich set of plugins with good documentation211
- Has support for build pipelines111
- Easy setup68
- It is open-source66
- Workflow plugin53
- Configuration as code13
- Very powerful tool12
- Many Plugins11
- Continuous Integration10
- Great flexibility10
- Git and Maven integration is better9
- 100% free and open source8
- Github integration7
- Slack Integration (plugin)7
- Easy customisation6
- Self-hosted GitLab Integration (plugin)6
- Docker support5
- Pipeline API5
- Fast builds4
- Platform idnependency4
- Hosted Externally4
- Excellent docker integration4
- It`w worked3
- Customizable3
- Can be run as a Docker container3
- It's Everywhere3
- JOBDSL3
- AWS Integration3
- Easily extendable with seamless integration2
- PHP Support2
- Build PR Branch Only2
- NodeJS Support2
- Ruby/Rails Support2
- Universal controller2
- Loose Coupling2
- Workarounds needed for basic requirements13
- Groovy with cumbersome syntax10
- Plugins compatibility issues8
- Lack of support7
- Limited abilities with declarative pipelines7
- No YAML syntax5
- Too tied to plugins versions4
related Jenkins posts
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.
Releasing new versions of our services is done by Travis CI. Travis first runs our test suite. Once it passes, it publishes a new release binary to GitHub.
Common tasks such as installing dependencies for the Go project, or building a binary are automated using plain old Makefiles. (We know, crazy old school, right?) Our binaries are compressed using UPX.
Travis has come a long way over the past years. I used to prefer Jenkins in some cases since it was easier to debug broken builds. With the addition of the aptly named “debug build” button, Travis is now the clear winner. It’s easy to use and free for open source, with no need to maintain anything.
#ContinuousIntegration #CodeCollaborationVersionControl
- Flexibility110
- Easy to use51
- Groovy dsl47
- Slow build time22
- Crazy memory leaks10
- Fast incremental builds8
- Kotlin DSL5
- Windows Support1
- Inactionnable documentation8
- It is just the mess of Ant++6
- Hard to decide: ten or more ways to achieve one goal4
- Bad Eclipse tooling2
- Dependency on groovy2
related Gradle posts
We use Apache Maven because it is a standard. Gradle is very good alternative, but Gradle doesn't provide any advantage for our project. Gradle is slower (without running daemon), need more resources and a learning curve is quite big. Our project can not use a great flexibility of Gradle. On the other hand, Maven is well-know tool integrated in many IDEs, Dockers and so on.
Hi, I'm working on dockerizing a heavy Java EE application where the process of installation requires a complex process maintained by a Gradle project we've developed to install, configure and customize specific jar files to generate a runnable server application at the end for the user. I'm new to Docker. As I said, the problem is that we have got a long process to install the app. The first alternative pop into my head is to put the installer Gradle project in the docker image and manage stateful data using the writable layer (in this case, I need to add Gradle too and the writable layer will be too heavy). Any advice! Thank you
- Flexible4
- Simple1
- Easy to learn1
- Easy to write own java-build-hooks1
- Slow1
- Old and not widely used anymore1
related Apache Ant posts
All Java-Projects are compiled using Apache Maven. We prefer it over Apache Ant and Gradle as it combines lightweightness with feature-richness and offers basically all we can imagine from a software project-management tool and more. We're open however to re-evaluate this decision in favor of Gradle or Bazel in the future if we feel like we're missing out on anything.
Apache Tomcat
- Easy79
- Java72
- Popular49
- Spring web1
- Blocking - each http request block a thread3
- Easy to set up2
related Apache Tomcat posts
I need some advice to choose an engine for generation web pages from the Spring Boot app. Which technology is the best solution today? 1) JSP + JSTL 2) Apache FreeMarker 3) Thymeleaf Or you can suggest even other perspective tools. I am using Spring Boot, Spring Web, Spring Data, Spring Security, PostgreSQL, Apache Tomcat in my project. I have already tried to generate pages using jsp, jstl, and it went well. However, I had huge problems via carrying already created static pages, to jsp format, because of syntax. Thanks.
- Does it all131
- Integrates with most of tools76
- Easy to use64
- Java IDE63
- Best Java IDE32
- Open source9
- Hard for newbews3
- Great gdb integration2
- Professional2
- Good Git client allowing direct stage area edit2
- True open source with huge contribution2
- Great code suggestions2
- Extensible2
- Lightweight2
- Works with php0
- 2000 Design14
- Bad performance9
- Hard to use4
related Eclipse posts
UPDATE: Thanks for the great response. I am going to start with VSCode based on the open source and free version that will allow me to grow into other languages, but not cost me a license ..yet.
I have been working with software development for 12 years, but I am just beginning my journey to learn to code. I am starting with Python following the suggestion of some of my coworkers. They are split between Eclipse and IntelliJ IDEA for IDEs that they use and PyCharm is new to me. Which IDE would you suggest for a beginner that will allow expansion to Java, JavaScript, and eventually AngularJS and possibly mobile applications?
Have been a Visual Studio Code user since just after launch to the general public, having used the likes of Eclipse and Atom previously. Was amazed how mature it seemed off the bat and was super intrigued by the bootstrapped nature of it having been written/based on Electron/TypeScript, and of course being an open-source app from Microsoft. The features, plugin ecosystem and release frequency are very impressive. I do dev work on both Mac and Windows and don't use anything else now as far as IDEs go.
- 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 made8
- Awful merge handling5
- Unexistent preventive security flows3
- Rebase hell3
- Ironically even die-hard supporters screw up badly2
- When --force is disabled, cannot rebase2
- 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.
GitHub
- Open source friendly1.8K
- Easy source control1.5K
- Nice UI1.3K
- Great for team collaboration1.1K
- Easy setup867
- Issue tracker504
- Great community487
- Remote team collaboration483
- Great way to share449
- Pull request and features planning442
- Just works147
- Integrated in many tools132
- Free Public Repos122
- Github Gists116
- Github pages113
- Easy to find repos83
- Open source62
- Easy to find projects60
- It's free60
- 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
- Fast8
- Beautiful user experience8
- It integrates directly with Hipchat8
- Easy to discover new code libraries7
- Smooth integration6
- Integrations6
- Graphs6
- Nice API6
- It's awesome6
- Cloud SCM6
- Quick Onboarding5
- Remarkable uptime5
- CI Integration5
- Reliable5
- Hands down best online Git service available5
- Version Control4
- Unlimited Public Repos at no cost4
- Simple but powerful4
- Loved by developers4
- Free HTML hosting4
- Uses GIT4
- Security options4
- Easy to use and collaborate with others4
- Easy deployment via SSH3
- Ci3
- IAM3
- Nice to use3
- Easy and efficient maintainance of the projects2
- Beautiful2
- Self Hosted2
- Issues tracker2
- Easy source control and everything is backed up2
- Never dethroned2
- All in one development service2
- Good tools support2
- Free HTML hostings2
- IAM integration2
- Very Easy to Use2
- Easy to use2
- Leads the copycats2
- Free private repos2
- Profound1
- Dasf1
- Owned by micrcosoft55
- Expensive for lone developers that want private repos38
- Relatively slow product/feature release cadence15
- API scoping could be better10
- Only 3 collaborators for private repos9
- Limited featureset for issue management4
- Does not have a graph for showing history like git lens3
- GitHub Packages does not support SNAPSHOT versions2
- 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.
Context: I wanted to create an end to end IoT data pipeline simulation in Google Cloud IoT Core and other GCP services. I never touched Terraform meaningfully until working on this project, and it's one of the best explorations in my development career. The documentation and syntax is incredibly human-readable and friendly. I'm used to building infrastructure through the google apis via Python , but I'm so glad past Sung did not make that decision. I was tempted to use Google Cloud Deployment Manager, but the templates were a bit convoluted by first impression. I'm glad past Sung did not make this decision either.
Solution: Leveraging Google Cloud Build Google Cloud Run Google Cloud Bigtable Google BigQuery Google Cloud Storage Google Compute Engine along with some other fun tools, I can deploy over 40 GCP resources using Terraform!
Check Out My Architecture: CLICK ME
Check out the GitHub repo attached