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-rw-r--r--docs/tutorials/longer-metrics-storage.md10
1 files changed, 5 insertions, 5 deletions
diff --git a/docs/tutorials/longer-metrics-storage.md b/docs/tutorials/longer-metrics-storage.md
index 1e34f67a6b..80cc08ea44 100644
--- a/docs/tutorials/longer-metrics-storage.md
+++ b/docs/tutorials/longer-metrics-storage.md
@@ -12,8 +12,8 @@ long term?
Many people think Netdata can only store about an hour's worth of real-time metrics, but that's simply not true any
more. With the right settings, Netdata is quite capable of efficiently storing hours or days worth of historical,
-per-second metrics without having to rely on a [backend](../../backends/) or [exporting
-connector](../../exporting/README.md).
+per-second metrics without having to rely on a [backend](/backends/README.md) or [exporting
+connector](/exporting/README.md).
This tutorial gives two options for configuring Netdata to store more metrics. **We recommend the default [database
engine](#using-the-database-engine)**, but you can stick with or switch to the round-robin database if you prefer.
@@ -65,7 +65,7 @@ Based on our testing, these default settings will retain about a day's worth of
more historical metrics.
But before you change these options too dramatically, read up on the [database engine's memory
-footprint](../../database/engine/README.md#memory-requirements).
+footprint](/database/engine/README.md#memory-requirements).
With the database engine active, you can back up your `/var/cache/netdata/dbengine/` folder to another location for
redundancy.
@@ -158,9 +158,9 @@ Now that you have either configured database engine or round-robin database engi
probably want to see it in action!
For more information about how to pan charts to view historical metrics, see our documentation on [using
-charts](../../web/README.md#using-charts).
+charts](/web/README.md#using-charts).
-And if you'd now like to reduce Netdata's resource usage, view our [performance guide](../../docs/Performance.md) for
+And if you'd now like to reduce Netdata's resource usage, view our [performance guide](/docs/Performance.md) for
our best practices on optimization.
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