CircleCI vs. Datadog

CircleCI is perfect for a CI/CD pipeline for an app using a standard build process. It'll take more work for a complex build process, but should still be up to the task unless you need a lot of integrations with other tools. If you have a big team and can spare someone to focus full time on just the CI/CD tools, maybe something like Jenkins is better, but if you're just looking to get your app built, tested, and delivered without a huge amount of effort, CircleCI is probably your preferred tool.

Incentivized

Datadog works really well with complex microservices architecture like any E-commerce platform which will be having multiple services but they all are interdependent to others so in this scenario Datadog will be best to monitor these as it will show the transactions also between those microservices. If you are using multiple services in your architecture whether it will be cloud services or on prem services Datadog will be the best choice to monitor all those service with in Datadog so that you can see everything in a single place. But if you are having small architecture and few services in that then in that scenario you can use Datadog but it will be little costly as compared to other but obviously the features are very well.

Incentivized

• GitHub integration is seamless. Never had a problem with it missing commits.
• Robust test environment. I used Travis in the past but tests would sporadically time out for no clear reason, haven't had that happen with CircleCI
• Poweful YAML-based configuration in the GitHub repo itself. I don't like CI tools like Semaphore that push you into managing your CI/CD through a web UI, I prefer managing a config file and never having to log in to the CI tool.

Incentivized

• Create Dashboards as per application, environments, and Custom metrics in one panel.
• Log aggregation, one-stop Application monitoring tools for the whole infrastructure.
• Playbooks, SLA definition, success and error quotas, request visualizations.
• DB monitoring, Serverless stack monitoring.
• Alerting of Production incidents so we can quickly resolve the issues on time.

Incentivized

• It would be nice if you could configure everything via the YML file. Some things are only available via YML, and some things are actually only available in the UI, and many other things have full overlap between the two. I'm sure there are good reasons for this, but this is a pretty confusing situation. For example, certain PHP versions are only available on certain Ubuntu releases. Configuring the PHP version is done via the .yml file, but configuring the Ubuntu release being used for the build has to be done in the UI. This can easily lead to things not building properly.

Incentivized

• Alert windows cause lag in notifications (e.g. if the alert window is X errors in 1 hour, we won't get alerted until the end of the 1 hour range)
• I would appreciate more supportive examples for how to filter and view metrics in the explorer
• I would like a more clear interface for metrics that are missing in a time frame, rather than only showing tags/etc. for metrics that were collected within the currently viewed time frame

Incentivized

Definitely will not revisit after our issues and, in my opinion, poor support.

Incentivized

The reliability & speed, it just works. The ability to spin up macOS runners and Docker containers on demand without managing hardware is a huge win. The Orbs system makes integrating with AWS and Slack incredibly easy, saving us weeks of custom scripting and providing real-time updates in our Slack channel. This makes it easy for us to track and ensures that everyone involved knows the status. Of course, it has drawbacks related to configuration complexity and, in some cases, cost transparency, but overall, it is an industry-standard, robust tool that solves our core infrastructure problems well.

Incentivized

There is some room for improvement, but the Datadog team sends out updates frequently, and the UI is user-friendly for engineers, with no significant loading issues or region-specific problems. That was one of the key reasons we preferred Datadog; our company has employees worldwide, and it wasn't difficult to transition to the tool.

Incentivized

It's pretty snappy, even with using workflows with multiple steps and different docker images. I've seen builds take a long time if it's really involved, but from what I can tell, it's still at least on par if not faster than other build tools.

Incentivized

Unless you have a reasonably large account, you're going to be mainly stuck reading their documentation. Which has improved somewhat over the years but is still extremely limited compared to a platform like Digital Ocean who invested in the documentation and a community to ensure it's kept up to date. If you can't find your answer there, you can be stuck.

Incentivized

The support team usually gets it right. We did have a rather complicate issue setting up monitoring on a domain controller. However, they are usually responsive and helpful over chat. The downside would be I don’t think they have any phone support. If that is important to you this might not be a good fit.

Incentivized

Documentation was difficult to work through, rollout was catastrophic (completely outage)

Incentivized

CircleCI shines with its specialized infrastructure. Its dedicated macOS runners ensure blazing-fast iOS builds, while intelligent Docker layer caching significantly reduces backend build times and costs. The ability to SSH directly into failed builds dramatically accelerates debugging. Furthermore, its certified Orbs provide standardized, secure integrations with AWS and Slack, reducing the stability and security risks often associated with unverified community plugins on competing platforms such as GitHub Actions.

Incentivized

Datadog is a more complex but complete solution than any of the other Log Aggregation, monitoring, or general observabilty tools that we have trialed. I found it easier to setup following useful and up-to-date documentation provided directly by Datadog instead of scattered around many blogs or articles. I would love to have my own Grafana + Prometheus expert to setup all the peices we need but you're paying for expertise there instead of an experience with Datadog.

Incentivized

• Continuous Integration saves time for developers to manually handle deploying code.
• Ability to build complex workflows with test suites catches bugs before they get to production - saving a lot of headache.
• The integrations with Slack and DataDog keep the entire company informed of builds and deploys, increasing our awareness and efficiency.

Incentivized

• Saved us (time & money) from developing our own monitoring utilities that would pale in comparison
• Alerts allow us to remedy issues before our customers even know about them
• Tracking resource usage over time allows us to better plan for future needs, before it becomes a pain-point.

Incentivized