Software development in the past decades has moved from being perceived as a form of alchemy to something that can be quantified and managed.
Alongside good project management practices, those working in the DevOps world rely on complex tools that enable a team to contribute code to a common objective.
These enable team members to leave or join without taking with them the knowledge that only that hold, and allows these projects to scale workforce as, and when necessary.
Here are some of the best tools for keeping software development under control, and developers happy.
The standard for DevOps tools
- Free and open source
- Massive community support
If you ask most software developers to name a tool for handling distributed version control, then they’re most likely to say ‘Git’.
What has helped made Git the major force in software development it has become is that it is both free and open source. But what keeps it relevant is ongoing development and an excellent feature set for code management.
What Git excels at is managing a software development scenario where the project might be required to branch in multiple directions, allowing for independent code that can be merged and deleted without impacting on the common code base.
The beauty of this solution is that you can branch code, develop new functionality and then realize that you need to adapt the inherited foundations, make those changes and merge those into the branch.
Once you’ve completed a feature on that branch, it can be merged with the common code, for use across the project. Or, it can be restricted until other related features are ready to share.
This approach encourages disposable code experimentation and allows changes to be made at all levels without, hopefully, upsetting others working on the project.
Wrapping up code to travel
- Not all applications benefit from containers
- Some app performance is lost in translation
Software tools often rely on a custom installation routine to be placed on to a computer that handles the placement of files and folders, and the wiring of the functionality into the operating system.
This approach is prone to problems, as operating systems change over time, and what any version might contain isn’t guaranteed.
Docker resolves the installation conundrum by packaging an application along with its code, runtime, system tools, system libraries, and settings. Docker images are executed by the open-source Docket Engine on the OS, and link to the computers OS system kernel.
This model allows the code inside to be fully isolated from other docker containers running on the same hardware, making them both secure and protected from malware attacks.
In many respects, Docker has similarities to the virtual installs offered by Hypervisors, but as all Docket containers can reuse the same OS, it is inherently more efficient.
The Docket technology works so well that containers are now supported on Linux, Windows and in the Cloud. And, Docker shared applications can be developed on Windows PC and the Apple Mac.
Overall, Docker has become one of the go-to technologies for those that need transportable applications.
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Time to cut the strings of compliance management
- Maximizes DevOps resources, man and machine
- Excellent community support
- Protects infrastructure knowledge from leaving
- Resource heavy
On one level Puppet is about server management. But that description demeans what is a very powerful tool to use in any DevOps controlled environment.
What Puppet can do is provide a global perspective on infrastructure, identifying what hardware is running what services and containers, and highlighting those that are potentially vulnerable.
But it is also compliance aware and can make sure that servers are protected in the ways they need to be and generating reports to confirm that patches have been applied and upgrades executed.
And, if the developers are familiar with YAML, Puppet provides a mechanism to deploy applications to multiple cloud-native targets from a source-controlled repository.
For the Enterprise, getting a proper vision of the state of computing infrastructure and mission-critical applications is important. The quality of that information will directly impact key business decisions while maintaining security or compliance initiatives.
Puppet sweeps away manual interventions and crisis management methods and replaces it with automated processes that enforce consistency and security.
Vaporises bugs and errata
- Cloud and local deployment
- Processes users and code interactions
- Supports Web-based, Windows, Mac, Linux, iOS and Android platforms
- Can be costly
Bug hunting is the bane of all software developers because mistakes get made and eventually, many will need fixing.
Raygun is a cloud-based tool designed to monitor networks and track bugs, and then deliver a workflow to resolve issues it identifies.
It’s best to think of it like those people that control the emergency services, that direct the crews to the location of a crash or fire and provide all the information needed by those attending.
But it also has the tools to monitor an application, those clients using it and analyze the interaction between them to provide insight into what triggers an error or failure.
Being able to access diagnostic information and workflow tools helps DevOps identify, reproduce and resolve problems smartly and efficiently.
These processes are especially relevant to software development teams that deploy major updates regularly and need to know that the new release is working properly for the point-of-sales staff or other mission-critical purposes.
Raygun pricing is based on the number of error events or user sessions processed and is available either on a monthly or yearly subscription basis. The Startup tier can handle 250k events a month, Small Business a million, where the top Business and Enterprise customers have unlimited events.
Enterprise customers can also install Raygun locally, rather than use the Cloud.
Better software faster
- Accelerates build process
- Supports Kotlin development
- Community plugins
- Build speeds can be an issue
The objectives of Gradle are ambitious; to help build any code quicker, automate delivery end-to-end, and deliver it faster to those that need it.
To achieve those lofty goals, Gradle provides a means to declare all the tasks needed for a complex build and then execute them.
Those who are only developing for a single platform on one project might not find Gradle helpful, but those working on multi-platform, multi-language, and multi-channel solutions will almost certainly will.
In a single click, code can be compiled, tested, packaged and then shipped without handcrafting scripts or entering command-line instructions.
The only drawbacks to having such a powerful build tool are that overheads can slow the building process and hold back ongoing development if they’re on the same workstation.
Performance can be enhanced if you run higher performance networks to the code repository and use a second machine for the build process if needed.
Amazingly, Gradle is free to developers. But, if you want to enhance performance and reliability, a paid Enterprise Gradle is available for a quoted cost.
As with many open-source projects, Gradle has great community support, and many community-created plugins are available to use with it.
Disclaimer- This article was originally published on www.techradar.com
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