Time series database built to manage scale

Outgrowing Prometheus with Levitate

High Cardinality

High cardinality labels are impossible to analyze, constantly crashing Prometheus. This limits the insights that can be gathered to successfully triage & resolve an incident.

Solves High Cardinality

Levitate is built to handle massive scales of data, and can handle queries at any cardinality. Above all, it gives you real-time insights into what metrics are unused

Metric storage costs

The explosion of services & infrastructure leads to the immense growth of metrics stored for monitoring. The cost of storage, amortisation, and data transfers, quickly spiral out of control.

This also results in accumulating unwanted data - nearly 60% of metrics data is unused, and most cases, useless

Pay for what you use, reduce costs

Levitate reduces storage costs by up to 50% compared to similar tsdbs. This is over and above the engineering time, & overheads spent maintaining internal infrastructure.

With Levitate data retention policies & tiered storage, you pay for metrics you use. Scale without having to tune configuration, & having to run a whole setup for data scaling.

Operational Toil

Operating Prometheus (and other time-series databases) at scale takes full-time engineering teams to manage machines, multiple instances, data retention, backup & recovery. This toil is an unimaginable hassle.

Engineering bandwidth should focus on product, and building features, not setting up Prometheus instances.

Increase engineering productivity

Levitate is fully managed. No need to worry about adding more machines, managing replication, or multiple Prometheus instances. Just change the remote-write endpoint of your one, or many tsdbs. A simple UI manages it all.

With Levitate, you can resolve incidents faster with decreased querying times, and allow engineering to focus on building product.