CloudQuery

My main use case for CloudQuery is that it serves as an open-source, SQL-based cloud asset inventory and governance platform designed for cloud operations, platform engineers, security, and FinOps teams. Being a DevOps engineer, I appreciate that CloudQuery follows an ELT (Extract, Load, and Transformation) model. CloudQuery helps me by reducing manual investigation work. Daily benefits include finding untagged resources quickly, detecting configuration drift, identifying orphaned infrastructure, auditing IAM permissions, and tracking changes across environments.

I use CloudQuery as part of my regular workflows. In morning operational checks, it helps me find failed resources, detect policy violations, and review overnight changes. It also helps me in incident response by identifying recent configuration changes, determining affected resources, and investigating security incidents. CloudQuery aids me in infrastructure reviews by validating tagging compliance, checking resource ownership, and verifying backup configurations. Additionally, it helps me in CI/CD integration by running compliance checks during deployment environments and preventing misconfigured infrastructure from reaching production. It also assists me in reporting by generating monthly cost reports, building executive dashboards, and creating auditing evidence automatically.

CloudQuery has positively impacted my organization by saving costs as well as time. It improves cost efficiency in several ways, including identifying idle resources such as unattached EBS volumes, idle load balancers, stopped EC2 instances, and unused public IP addresses. Additionally, it helps detect resource sprawl by discovering duplicate environments, forgotten test resources, and shadow IT deployments, which saves significant costs. By correlating infrastructure and cost data, I can identify opportunities for reserved instances, saving plans, and right-sizing. It also reduces audit costs by automating reporting, which decreases manual effort during compliance audits and security reviews.

CloudQuery saves time for the organization by eliminating manual cloud console navigation, reducing time spent creating reports, automating compliance checks, simplifying incident investigations, centralizing cloud inventory, and reducing engineering requests from security and FinOps teams. Previously, we took around two to three days or even a week for audits, optimizing reserved capacity, and ensuring tagging compliance. In those scenarios, we typically took around one week or two to four days. However, after using CloudQuery, these tasks happen within a few hours. CloudQuery reduces costs by eliminating resources that have been unused for a considerable time and helps in checking for duplicate resources, thus assisting in cost savings.

CloudQuery has high accuracy because it provides the data that we need. Regarding its reliability, it is reliable. However, for some areas, we still need manual checking, particularly for real-time event monitoring capabilities since it does not have this feature. Additionally, we need manual effort for advanced visualization. There are some areas where it is reliable, but in some cases, we require manual intervention.

The best features that CloudQuery offers and helped me significantly include SQL-based querying because it uses standard SQL instead of requiring the learning of proprietary query languages. It helps me integrate with existing reporting and analytics tools and build custom dashboards easily. Another key feature is security and compliance monitoring, which continually detects misconfigurations, creates custom compliance checks, and monitors security baselines. Additionally, FinOps and cost optimization is another key feature as it correlates resource configuration with cost data, identifies unused resources, and improves tagging and cost allocation. Furthermore, it includes a history change tracking feature that allows me to track infrastructure changes over time, identify configuration drift, and simplify root cause analysis.

CloudQuery has an additional feature that is Policy-as-Code, which defines governance policy using SQL, automates compliance checks, and enforces organizational standards. Another feature is multi-cloud asset inventory, which provides a unified view across AWS, Azure, GCP, and Kubernetes. It also allows visibility into resources across multiple accounts and regions and has centralized infrastructure inventory.

Regarding CloudQuery's AI capabilities, I think its governance and security are very strong and secure.

The areas where CloudQuery needs improvement include real-time event monitoring, native remediation, remediation workflows, and log aggregation along with metrics collection. Therefore, for these, we still require tools such as Grafana, Prometheus, and DataDog. If these aspects are improved by CloudQuery, it will be very helpful.

I would find it very helpful if CloudQuery could create an out-of-the-box dashboard.

I have been using CloudQuery for the last three years.

CloudQuery is stable.

CloudQuery's scalability benefits from being an open-source platform, making it very scalable.

Our experience with customer support is that we have not interacted much, but they were great during the installation process when we required assistance, and they helped us significantly with our needs.

We previously used other solutions such as DataDog, but those tools were quite costly and did not meet our needs. That is why we evaluated other tools and found CloudQuery, which is helpful for us, and we decided to choose CloudQuery.

My experience with pricing, setup cost, and licensing is that it reduces costs significantly. While it incurs substantial installation costs, it is useful for us because it saves so much overall cost. Therefore, the investment in this cloud solution is valuable.

I do not have specific metrics, but I confirm that time and money are saved by using CloudQuery. Moreover, the number of employees we previously used for some operations has decreased thanks to CloudQuery. This platform has reduced our workforce requirements for certain operational tasks.

My experience with pricing, setup cost, and licensing is that it reduces costs significantly. While it incurs substantial installation costs, it is useful for us because it saves so much overall cost. Therefore, the investment in this cloud solution is valuable.

Before choosing CloudQuery, I evaluated other options. We considered other options such as Steampipe and Resoto for cloud inventory, but those were less useful for our needs. When we checked CloudQuery, it proved to be suitable for what we needed, leading us to choose CloudQuery.

My advice for others looking into using CloudQuery is that they should definitely choose CloudQuery because it is a very useful tool for data engineers and DevOps engineers. It significantly aids in daily work by helping with monitoring and security, so I recommend going for CloudQuery. I would rate my overall experience with CloudQuery an 8 out of 10.