Replace all post_url with Hugo ref blocks
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@ -13,8 +13,8 @@ is convenient, but these companies are sometimes taking away my autonomy and exe
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for me it's time to take back a little bit of responsibility for my online social presence, away from centrally hosted services and to
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privately operated ones.
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In my [[first post]({% post_url 2022-11-20-mastodon-1 %})], I shared some thoughts on how I installed a Mastodon instance for myself. In a
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[[followup post]({% post_url 2022-11-24-mastodon-2 %})] I talked about its overall architecture and how one might use Prometheus to monitor
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In my [[first post]({{< ref "2022-11-20-mastodon-1" >}})], I shared some thoughts on how I installed a Mastodon instance for myself. In a
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[[followup post]({{< ref "2022-11-24-mastodon-2" >}})] I talked about its overall architecture and how one might use Prometheus to monitor
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vital backends like Redis, Postgres and Elastic. But Mastodon _itself_ is also an application which can provide a wealth of telemetry using
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a protocol called [[StatsD](https://github.com/statsd/statsd)].
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@ -84,8 +84,7 @@ minutes, I think I can see lots of nifty data in here.
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## Prometheus
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At IPng Networks, we use Prometheus as a monitoring observability tool. It's worth pointing out that **statsd** has a few options itself to
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visualise data, but considering I already have lots of telemetry in Prometheus and Grafana (see my [[previous post]({% post_url
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2022-11-24-mastodon-2 %})]), I'm going to take a bit of a detour, and convert these metrics into the Prometheus _exposition format_, so that
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visualise data, but considering I already have lots of telemetry in Prometheus and Grafana (see my [[previous post]({{< ref "2022-11-24-mastodon-2" >}})]), I'm going to take a bit of a detour, and convert these metrics into the Prometheus _exposition format_, so that
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they can be scraped on a `/metrics` endpoint just like the others. This way, I have all monitoring in one place and using one tool.
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Monitoring is hard enough as it is, and having to learn multiple tools is _no bueno_ :)
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