From 78c36392eb2cc592789109cbf29f90ba18e6e277 Mon Sep 17 00:00:00 2001 From: hasura-bot Date: Mon, 7 Nov 2022 22:57:10 +0530 Subject: [PATCH] docs: add guide on performance tuning (fix #4805) GITHUB_PR_NUMBER: 9052 GITHUB_PR_URL: https://github.com/hasura/graphql-engine/pull/9052 PR-URL: https://github.com/hasura/graphql-engine-mono/pull/6163 Co-authored-by: Aniketh Varma <55805574+aniketh-varma@users.noreply.github.com> Co-authored-by: Rob Dominguez <24390149+robertjdominguez@users.noreply.github.com> Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com> GitOrigin-RevId: 0e9fac8795211e211aa9909d4f18dcfdc261f1b9 --- docs/docs/deployment/performance-tuning.mdx | 208 ++++++++++++++++++ .../deployment/hasura-connection-poller.png | Bin 0 -> 23656 bytes .../img/deployment/hasura-load-balancer.png | Bin 0 -> 36753 bytes .../img/deployment/hasura-microservices.png | Bin 0 -> 36946 bytes docs/static/img/deployment/hasura-usage.png | Bin 0 -> 63732 bytes 5 files changed, 208 insertions(+) create mode 100644 docs/docs/deployment/performance-tuning.mdx create mode 100644 docs/static/img/deployment/hasura-connection-poller.png create mode 100644 docs/static/img/deployment/hasura-load-balancer.png create mode 100644 docs/static/img/deployment/hasura-microservices.png create mode 100644 docs/static/img/deployment/hasura-usage.png diff --git a/docs/docs/deployment/performance-tuning.mdx b/docs/docs/deployment/performance-tuning.mdx new file mode 100644 index 00000000000..2864c05e957 --- /dev/null +++ b/docs/docs/deployment/performance-tuning.mdx @@ -0,0 +1,208 @@ +--- +description: Tune performance of the Hasura GraphQL Engine +keywords: + - hasura + - docs + - deployment + - performance + - tuning +sidebar_position: 120 +sidebar_label: Performance tuning +--- + +# Tune Hasura Performance + +This page serves as a reference for suggestions on fine tuning the performance of your Hasura GraphQL Engine instance. +We cover database configurations, scaling, observability, and software architecture to help you get the most out of your +set up. + +## Configuration and deployment + +### Postgres configuration + +PostgreSQL's basic configuration is tuned for wide compatibility rather than performance. The default parameters are +very undersized for your system. You can read more details about the configuration settings at the +[PostgreSQL Wiki](https://wiki.postgresql.org/wiki/Main_Page). There are also config generator tools that can help us: + +- [Tuning Your PostgreSQL Server](https://wiki.postgresql.org/wiki/Tuning_Your_PostgreSQL_Server) +- [Config generator](https://pgtune.leopard.in.ua) + +### Hasura configuration + +With respect to Hasura, several environment variables can be configured to tune performance. + +#### `HASURA_GRAPHQL_PG_CONNECTIONS` + +- Minimum **2** connections +- Default value: **50** +- Max connections: = Max connections of Postgres - 5 (keep free connections for another services, e.g PGAdmin, metrics + tools) + +However, how many connections is the best setting? Of course, it depends on the Postgres server's hardware +specifications. Moreover, too many connections doesn't mean query performance will be the highest. There are many great +articles that analyze this deeper: + +- [https://brandur.org/postgres-connections](https://brandur.org/postgres-connections) +- [https://github.com/brettwooldridge/HikariCP/wiki/About-Pool-Sizing](https://github.com/brettwooldridge/HikariCP/wiki/About-Pool-Sizing) + +There isn't a silver bullet for all server specs. Your developer has to test and benchmark carefully for the final +result. However, as a starting point, you can estimate with this formula, and then test around this value: + +``` +connections = ((core_count * 2) + effective_spindle_count) +``` + +For example, if your server has a 4 Core i7 CPU and 1 hard disk, it should have a connection pool of: + +9 = ((4 \* 2) +1). + +:::tip Tip + +Call it 10, as a nice round number. + +::: + +For high-transaction applications, a horizontal scale with multiple GraphQL Engine clusters is the recommended best +practice. However, you should be aware of the total connections of all nodes. The number must be lower than the maximum +connections of the Postgres instance. + +#### `HASURA_GRAPHQL_CONNECTIONS_PER_READ_REPLICA` + +With Read replicas, Hasura can load balance multiple databases. However, you will need to balance connections between +database nodes too: + +- Master connections (`HASURA_GRAPHQL_PG_CONNECTIONS`) are now used for writing only. You can decrease max connections + lower if Hasura doesn't write much, or share connections with other Hasura nodes. +- Currently, read-replica connections use one setting for all databases. It can't flexibly configure specific values for + each node. Therefore, you need to be aware of the total number of connections when scaling Hasura to multiple nodes. + +#### `HASURA_GRAPHQL_LIVE_QUERIES_MULTIPLEXED_REFETCH_INTERVAL` + +Default: **1000** (ms) + +In brief, live query subscribers are grouped with the same query and variables. The GraphQL Engine needs to execute one +query and return the same results to clients once every refetch interval. + +The smaller the interval is, the faster the update clients receive. However, everything has a cost. Small intervals with +a large number of subscriptions need larger CPU and memory resources. If you don't need such high frequency, the +interval can be set a bit longer. In contrast, with a small to medium number of subscriptions, the default value will +suffice. + +#### `HASURA_GRAPHQL_LIVE_QUERIES_MULTIPLEXED_BATCH_SIZE` + +Default: **100** + +Imagine there are 1,000,000 subscribers to the same query. Emitting to millions of websockets in sequence can cause +delays and eat more memory in a long queue. However, a small batch size can increase the number of SQL transactions. +This value needs to be kept in balance. If you don't have an idea to determine what value to use, use the default. + +### Scalability + +The Hasura GraphQL Engine binary is containerized by default, so it is easy to scale horizontally. You need to estimate +concurrent requests/second, benchmark how many requests one Hasura node can load, then scale multiple nodes with a +simple calculation: + +``` +total_nodes = required_ccu / requests_per_node + backup_node +``` + +:::info Note + +`backup_node` is `0` or `1`, depending on your plan. + +::: + +However, you need to be aware of the total Postgres connections, too. The default `HASURA_GRAPHQL_PG_CONNECTIONS` value +is `50`, meanwhile the default Postgres `max_connections` configuration is `100`. The Postgres server will easily be out +of connections with `3` Hasura nodes, or `2` nodes with events/action services that connect directly to the database. + +``` +pg_max_connections >= hasura_nodes * hasura_pg_connections + event_nodes * event_pg_connections +``` + +### Observability + +Observability tools help us track issues, alert us to errors, and allow us to monitor performance and hardware usage. It +is critical in production. There are many open-source and commercial services. However, you may have to combine many +tools because of the architectural complexity. For more information, check out our +[observability section](/observability/index.mdx) and our +[observability best practices](/guides/best-practices-for-production/observability.mdx). + +## Software architecture and best practices + +### Hasura as a data service + +#### Connection Pooler + +Database connection management isn't an easy task, especially when scaling to multiple application nodes. There are +common issues such as connection leaking, and maximum connections exceeded. If you use serverless applications for +Actions/event triggers that connect directly to a database, connection leaking is unavoidable because every invocation +may result in a new connection to the database. This is especially true when the number of services has grown into the +hundreds. + +You can use many solutions such as [PgBouncer](https://www.pgbouncer.org/), vertical scaling, and increasing +`max_connections` on Postgres configurations. However, increasing too many connections can have unintended consequences +for your server and degrade performance. + +Therefore, you can reduce connection usage by querying data from the GraphQL Engine instead. Connection pooling will be +centralized in Hasura nodes. + +![hasura connection pooling](/img/deployment/hasura-connection-poller.png) + +You can read more in the +[Hasura Blog](https://hasura.io/blog/level-up-your-serverless-game-with-a-graphql-data-as-a-service-layer/). + +### Understand your data + +Hasura's query performance relies on database performance. When there is any performance issue, you need profiling to +identify the bottleneck point and optimize your database queries. Utilizing the power of Postgres can help boost +application speed. + +Fundamental knowledge you should know and practice: + +- Index your table. +- Optimize queries with view, materialized view, and functions. +- Use trigger to update data instead of using 2 or more request calls. +- Normalize data structure. +- [EXPLAIN, ANALYZE](https://www.postgresql.org/docs/current/sql-explain.html). + +### Query tips + +- Avoid too many `_or` conditions. This doesn't utilize the table index. +- `like`, `ilike` is expensive, especially on long text. Use + [Full-text search](https://hasura.io/blog/full-text-search-with-hasura-graphql-api-postgres/) instead. +- Pagination is necessary. +- Fetching batched multiple queries in one request is useful. However, you shouldn't overuse it. One common case is + using aggregate count with data in the same pagination query. It is okay for small-to-medium tables. However, when the + table size is large, the query will be slow because of the scanning the entire table. +- Avoid joining too many tables. + +### Microservices + +Hardware has its limits. It's expensive to scale servers as well as optimize data. Moreover, Postgres doesn't support +master-master replica, so it will be a bottleneck if you store all the data in one database. Therefore, you can divide +your business logic into multiple smaller services, or microservices. + +Hasura encourages microservices with [Remote Schemas](/remote-schemas/index.mdx). This can act as an API Gateway that +routes to multiple, smaller GraphQL servers. + +![hasura load-balancer](/img/deployment/hasura-microservices.png) + +For example, in an e-commerce application, you can design three Hasura services: + +- User + Authentication +- Product management +- Order + Transactions + +Depending on a project's scope, the design philosophy is flexible. On a small project, one database will suffice. + +### Postgres ecosystem + +Thanks to the open-source community, Postgres has many extensions for various types of applications: + +- Time-series data, metrics, IoT: [TimescaleDB](https://www.timescale.com/), [CitusDB](https://www.citusdata.com/). +- Spatial and geographic objects: [PostGIS](https://postgis.net/). +- Image processing: [PostPic](https://github.com/drotiro/postpic). + +With Remote Schemas, you can use Hasura with multiple databases for various use cases. 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