Amazon CloudWatch vs. SonarQube

For out business we find that AWS Cloudwatch is good at providing real-time metrics for monitoring and analysing the performance and usage of our platform by customers. It is possible to create custom metrics from log events, such people adding items to a basket, checking out or abandoning their orders.

Incentivized

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.

Incentivized

• It provides lot many out of the box dashboard to observe the health and usage of your cloud deployments. Few examples are CPU usage, Disk read/write, Network in/out etc.
• It is possible to stream CloudWatch log data to Amazon Elasticsearch to process them almost real time.
• If you have setup your code pipeline and wants to see the status, CloudWatch really helps. It can trigger lambda function when certain cloudWatch event happens and lambda can store the data to S3 or Athena which Quicksight can represent.

Incentivized

• 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.

Incentivized

• Memory metrics on EC2 are not available on CloudWatch. Depending on workloads if we need visibility on memory metrics we use Solarwinds Orion with the agent installed. For scalable workloads, this involves customization of images being used.
• Visualization out of the box. But this can easily be addressed with other solutions such as Grafana.
• By design, this is only used for AWS workloads so depending on your environment cannot be used as an all in one solution for your monitoring.

Incentivized

• 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

Incentivized

It's excellent at collecting logs. It's easy to set up. The viewing & querying part could be much better, though. The query syntax takes some time to get used to, & the examples are not helpful. Also, while being great, Log Insights requires manual picking of log streams to query across every time.

Incentivized

It can improve in some user experience and usability parts, like the code view and the way we assign issues it's a bit hidden and not highlighted

Incentivized

Support is effective, and we were able to get any problems that we couldn't get solved through community discussion forums solved for us by the AWS support team. For example, we were assisted in one instance where we were not sure about the best metrics to use in order to optimize an auto-scaling group on EC2. The support team was able to look at our metrics and give a useful recommendation on which metrics to use.

Incentivized

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.

Incentivized

Grafana is definitely a lot better and flexible in comparison with Amazon CloudWatch for visualisation, as it offers much more options and is versatile. VictoriaMetrics and Prometheus are time-series databases which can do almost everything cloudwatch can do in a better and cheaper way. Integrating Grafana with them will make it more capable Elasticsearch for log retention and querying will surpass cloudwatch log monitoring in both performance and speed

Incentivized

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

Incentivized

• Positive for alarms and alert notifications once configured/customized.
• Has upfront learning curve, and cost can increase as does the alarm activity and monitoring details you may require.
• Cost-effective for any size organization keeping with AWS and utilizing its native tools is a savings in long-term ROI.

Incentivized

• 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)