From 0558910e6af93955def31b113b760bb4f8623b87 Mon Sep 17 00:00:00 2001 From: Puru Gupta Date: Tue, 23 May 2023 18:21:45 +0530 Subject: [PATCH] docs: add cache metrics docs PR-URL: https://github.com/hasura/graphql-engine-mono/pull/9219 Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com> GitOrigin-RevId: d2aa98ecd330ecf08df8db0b0310d1f1853f73be --- docs/docs/caching/caching-metrics.mdx | 70 ++++++++++++++++++ docs/docs/enterprise/metrics.mdx | 4 +- .../img/metrics/cache-metrics-grafana.png | Bin 0 -> 118561 bytes 3 files changed, 72 insertions(+), 2 deletions(-) create mode 100644 docs/docs/caching/caching-metrics.mdx create mode 100644 docs/static/img/metrics/cache-metrics-grafana.png diff --git a/docs/docs/caching/caching-metrics.mdx b/docs/docs/caching/caching-metrics.mdx new file mode 100644 index 00000000000..c281b3ecfc4 --- /dev/null +++ b/docs/docs/caching/caching-metrics.mdx @@ -0,0 +1,70 @@ +--- +title: Caching Metrics +keywords: + - docs + - caching + - metrics + - prometheus + - grafana +sidebar_position: 3 +--- + +import Thumbnail from '@site/src/components/Thumbnail'; +import ProductBadge from '@site/src/components/ProductBadge'; + +# Caching Metrics + + + +## Introduction + +Hasura Enterprise Edition exports Prometheus metrics related to caching which +can provide valuable insights into the efficiency and performance of the caching system. +This can help towards monitoring and further optimization of the cache utilization. + +## Exposed metrics + +The graphql engine exposes the `hasura_cache_request_count` Prometheus metric. +It represents a `counter` and is incremented every time a request with `@cached` directive is served. + + +It has one label `status`, which can have values of either `hit` or `miss`. + +| status | description | +|-----------|-------------------| +| `hit` | request served from the cache | +| `miss` | request served from the source (not found in cache) | + + +## Get insights from metrics + +The `hasura_cache_request_count` metric can be used to get insights into the cache utilization by calculating the hit-miss ratio. +The hit-miss ratio is the ratio of the number of requests served from the cache to the total number of requests. + +``` +hit-miss ratio = hit count / (hit count + miss count) +``` + +What does the hit-miss ratio tells us? + +- **Cache Efficiency**: The hit-miss ratio reflects how well the caching system can serve requests from its cache. A higher hit ratio indicates more efficient cache usage, as more requests are being served from the cache rather than requiring fetching data from the upstream data source. + +- **Cache Performance**: The hit-miss ratio is a measure of cache performance. A higher hit ratio generally indicates better cache performance as it reduces latency and improves overall system performance. + +## Visualize metrics + +The metrics can be visualized using a tool like Grafana. + + + +:::tip Sample PromQL Queries + +- Total requests per minute with `@cached` directive: `sum(increase(hasura_cache_request_count[1m]))` +- `hit` requests per minute: `increase(hasura_cache_request_count{status="hit"}[1m])` +- `miss` requests per minute: `increase(hasura_cache_request_count{status="miss"}[1m])` +- Hit-Miss ratio over lifetime: `sum(hasura_cache_request_count{status="hit"})/sum(hasura_cache_request_count)` + +::: \ No newline at end of file diff --git a/docs/docs/enterprise/metrics.mdx b/docs/docs/enterprise/metrics.mdx index f4a0b6663e5..9f256f851c7 100644 --- a/docs/docs/enterprise/metrics.mdx +++ b/docs/docs/enterprise/metrics.mdx @@ -95,9 +95,9 @@ runtime errors. | Type | Gauge | | Labels | `subscription_kind`: streaming \| live-query | -### Hasura Cache requests count +### Hasura cache request count -Tracks cache hit and miss requests, which helps in monitoring and optimizing cache utilization. +Tracks cache hit and miss requests, which helps in monitoring and optimizing cache utilization. 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