“OpenObserve helped us migrate from Datadog in under an hour... reducing observability costs by 4x.”
4x
Lower observability cost
< 1 hour
Migrated off Datadog
Flat pricing
No month-end surprises
SLOs and Error Budgets. Alert on Burn Rate, Not Noise.
Count and time-slice SLIs. Rolling 7, 30, or 90 days.
Define what working means for your services, measure it continuously, and alert on how fast you are burning error budget - on the same engine that already holds your logs, metrics, and traces.
Measure what you promised
Define good as a query, pick a target, get an error budget for the difference.
Alert on speed, not noise
Burn-rate alerts fire on sustained damage and ignore the two minute spike.
One engine, not three tools
SLOs run on the same backend already holding your logs, metrics, and traces.
Reliability & Error Budgets
Alert on What Your Users Actually Feel
Define What Good Means
Good Is a Query, Not a Checkbox
A scope filter sets the denominator, a good-when predicate picks the numerator, a live preview splits good from bad as you type.
A Real Number on Day One
Count SLIs cover request success rates, time slice SLIs cover latency and freshness. Windows are rolling 7, 30, or 90 days.
Alert on Burn Rate
Burn Rate Puts Failures in Proportion
At 1 you finish the window having used exactly your allowance, at 14.4 a 30-day budget is gone in about two days.
Two Windows, So Alerts Resolve When Incidents Do
The long window establishes the problem is real and sustained, the short window confirms it is still happening.
Group by Dimension
One Series per Group
Group by region, endpoint, or tenant and each one gets its own SLI, budget, and burn rate.
The Overall Number Is Measured, Not Summed
The headline SLI is computed on its own, so it never silently becomes the sum of whichever groups fit.
One Measurement, Many Alerts
Measurement and Paging Stay Apart
An SLO only measures, alerting on one is an ordinary alert with the same destinations and severity as everything else.
Three Urgencies, One Objective
Fast burn pages you, mid burn notifies a channel, slow burn files a ticket.
Benchmarks
Measured against industry leaders
Same telemetry, same workloads, one platform. Every number is OpenObserve against a named vendor - not an industry average.
vs. Datadog
8×
more cost-effective
8x cost reduction means you can unify your observability into a single platform.
Read case studyvs. Elastic
140×
storage efficiency
140x storage means longer retention doesn't necessarily mean expensive bills.
Read case studyvs. Grafana stack
5–15×
faster performance
5x to 15x faster queries mean dashboards load in milliseconds, not minutes.
Read case study
See how much you would save switching today.
Testimonials
Teams trust OpenObserve to hold them to their objectives
Correlate between the environments and signals across various sources with OpenObserve built-in correlation engine.
SLO FAQs
Resources
Explore guides, videos, and articles
to help you get the most out of SLOs.
