Docker Enterprise was sold to Mirantis in 2019; that product is now sold as Mirantis Kubernetes Engine. But Docker now offers a 2-product suite that includes Docker Desktop, which they present as a fast way to containerize applications on a desktop; and, Docker Hub, a service for finding and sharing container images with a team and the Docker community, a repository of container images with an array of…
$5
per month
SonarQube
Score 8.2 out of 10
N/A
SonarQube is an automated code review solution, serving as the verification layer for code quality and SDLC security. SonarQube is used to ensure that code is secure, reliable, and maintainable. It is available through SaaS or self-managed deployment.
You are going to be able to find the most resources and examples using Docker whenever you are working with a container orchestration software like Kubernetes. There will always some entropy when you run in a container, a containerized application will never be as purely performant as an app running directly on the OS. However, in most scenarios this loss will be negligible to the time saved in deployment, monitoring, etc.
SonarQube is excellent if you start using it at the beginning when developing a new system, in this situation you will be able to fix things before they become spread and expensive to correct. It’s a bit less suitable to use on existing code with bad design as it’s usually too expensive to fix everything and only allows you to ensure the situation doesn’t get worse.
Detecting bugs and vulnerabilities: SonarQube can identify a wide range of bugs and vulnerabilities in code, such as null pointer exceptions, SQL injection, and cross-site scripting (XSS) attacks. It uses static analysis to analyze the code and identify potential issues, and it can also integrate with dynamic analysis tools to provide even more detailed analysis.
Measuring code quality: SonarQube can measure a wide range of code quality metrics, such as cyclomatic complexity, duplicated code, and code coverage. This can help teams understand the quality of their code and identify areas that need improvement.
Providing actionable insights: SonarQube provides detailed information about issues in the code, including the file and line number where the issue occurs and the severity of the issue. This makes it easy for developers to understand and address issues in the code.
Integrating with other tools: SonarQube can be integrated with a wide range of development tools and programming languages, such as Git, Maven, and Java. This allows teams to use SonarQube in their existing development workflow and take advantage of its powerful code analysis capabilities.
Managing technical debt: SonarQube provides metrics and insights on the technical debt on the codebase, enabling teams to better prioritize issues to improve the quality of the code.
Compliance with coding standards: SonarQube can check the code against industry standards like OWASP, CWE and more, making sure the code is compliant with security and coding standards.
Importing a new custom quality profile on SonarQube is a bit tricky, it can be made easier
Every second time when we want to rerun the server, we have to restart the whole system, otherwise, the server stops and closes automatically
When we generate a new report a second time and try to access the report, it shows details of the old report only and takes a lot of time to get updated with the details of the new and fresh report generated
I have been using Docker for more than 3 years and it really simplifies the modern application development and deployment. I like the ability of Docker to improve efficiency, portability and scalability for developers and operations teams. Another reason for giving this rating is because Docker integrates CI/CD pipelines very well
We we easily able to integrate the SonarQube steps into our TFS process via the Microsoft Marektplace, we didn't have the need to call SonarQube support. We've used their online documentation and community forum if we ran into any issues.
The reason why we are still using Docker right now is due to that is the best among its peers and suits our needs the best. However, the trend we foresee for the future might indicate Amazon lambda could potentially fit our needs to code enviornmentless in the near future.
SonarQube is an open-source. It's a scalable product. The costs for this application, for the kind of job it does, are pretty descent. Pipeline scan is more secured in SonarQube. Its a very good tool and its support multiple languages. Its main core competency is of static code analysis and that is why SonarQube exists and it does it exceedingly well. The quality of scan on code convention, best practices, coding standards, unit test coverage etc makes them one of the best competent tool in the market
It is the only tool in our toolset that has not [had] any issues so far. That is really a mark of reliability, and it's a testimony to how well the product is made, and a tool that does its job well is a tool well worth having. It is the base tool that I would say any organisation must have if they do scalable deployment.
Positive ROI from the standpoint of flagging several issues that would have otherwise likely been unaddressed and caused more time to be spent closer to launch
Slightly positive ROI from time-saving perspective (it's an automated check which is nice, but depending on the issues it finds, can take developers time to investigate and resolve)
