Prometheus monitoring that is radically simple and fully compatible
Prometheus is transforming observability for cloud native applications and services. As an open source project, Prometheus offers a standard way to collect, store, and query metrics across containers, Kubernetes, services, and applications. Since Sysdig Monitor is fully compatible with Prometheus, customers can take advantage of enterprise features without sacrificing their investment in the Prometheus ecosystem.
Prometheus Monitoring Use Cases
Managed Prometheus Service
Sysdig Monitor provides a fully managed Prometheus service with enterprise features for Prometheus monitoring. You can use Prometheus Query Language queries for dashboards and alerts, or the Prometheus API for scripted queries, as part of a DevOps workflow. Users can take advantage of our built-in agent scraping, simplified querying, troubleshooting, correlation, and support that we provide as part of Sysdig Monitor for a complete Prometheus monitoring solution.
“We have built so much around Prometheus, and with Sysdig, we are able to really use those metrics. Sysdig’s support of Prometheus is unique, along with its support for PromQL.”BERND MALMQVIST
PRINCIPAL CONTAINER PLATFORM ENGINEER, WORLDPAY
Frequently Asked Questions
Q: What is Prometheus monitoring?
A: Prometheus monitoring is the practice of using Prometheus to collect and store information about Kubernetes, services, and applications. You can analyze this information to get details about the health and performance of your infrastructure and applications.
Q: Why is Prometheus monitoring essential?
A: Prometheus is an open standard. By collecting metrics using Prometheus organizations can avoid vendor lock-in while having more control about how they collect important data. Since Sysdig Monitor is fully compatible with Prometheus, customers can take advantage of enterprise features without sacrificing their investment in the Prometheus ecosystem.
Q: How does Prometheus monitoring work?
A: Prometheus collects and stores its metrics as time series data, i.e. metrics information is stored with the timestamp at which it was recorded, alongside optional key-value pairs called labels.
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