How does Liftr Insights gather data about public clouds?
We implement DevOps—a combination of development and operations. We write and maintain cloud-based apps to gather cloud data via each CSP’s application programming interface (API) and other methods of software automated data collection. If you are into software development, we’re an agile software development shop.
Does Liftr Insights field surveys to gather data?
No. We’re not against surveys—they’re very useful for finding information that is not publicly available. But we collect publicly-available data, so surveys are unnecessary. Because our public data collection is based on DevOps, we automatically collect data on everything we’re interested in. It’s fast, it’s comprehensive, there is no sample bias and it is much less expensive to implement than surveys.
How does Liftr Insights analyze the data it gathers?
We have data scientists on staff. They do data sciencey things like ensure we’re gathering the right data, normalize data so we can compare cloud service provider offerings and perform data analytics to compare the cloud service providers.
Does Liftr Insights use machine learning?
Yes, we occasionally use machine learning. We spend a lot of time on making sure we gather the right data and that the data we gather is clean (data scientists call it “data hygiene”). Then, through our Liftr Cloud Distiller database and other internal systems of record, we normalize the data we gather from each cloud service provider so that we can make fair comparisons between the providers. Machine learning is part of our analysis mix. We also use a lot of other analytic techniques.
Any data through API?
Yes, as part of the automated data pipeline, we harvest the bulk of our data through API. Having programmatic access to data ensures that our analysis is less prone to errors and always up-to-date.
How do I know your data is unbiased?
We reduce bias by not fielding surveys and not sampling. We reduce bias by not cherry-picking the best data or cutting corners to collect the convenient data. We count everything.