Multi-cloud AI/ML and DevSecOps on Kubernetes
Learn more about AI/ML: https://ubuntu.com/kubeflow
Get Kubernetes on Ubuntu: https://ubuntu.com/kubernetes
In collaboration with: https://www.metrostarsystems.com/
The latest News and Information on DevOps, CI/CD, Automation and related technologies.
Learn more about AI/ML: https://ubuntu.com/kubeflow
Get Kubernetes on Ubuntu: https://ubuntu.com/kubernetes
In collaboration with: https://www.metrostarsystems.com/
Today’s generation of makers, artists and creatives have reinforced the idea that great things can happen when you roll up your sleeves and try to learn something new and exciting. Kubernetes was like this only a couple of years ago: the mere act of installing the thing was a rewarding challenge. Kelsey Hightower’s Kubernetes the Hard Way became the Maker’s handbook for this artisan craft.
Before we dive into the specifics of MetricFire vs. Datadog, let's address the most critical point: scaling. Datadog is great for users who need to do a little bit of everything, but Datadog's biggest weakness is scaling. Datadog can do logs, APM, time-series and more, but scaling time-series metrics, alerts, and servers will cause your monthly bill to escalate. The graph below shows what you pay at Datadog vs. MetricFire: Now, let's dive into MetricFire vs. Datadog, and their key comparisons.