This GraphQL server is built to expose information from Mina's Archive Node.
The server aims to expose zkApp related information to be used by developers and o1js. Users can query for events and actions related to their zkApp. In addition, users can filter for specific events and actions by public key, tokenId, to/from block ranges, and chain status.
An example query for events and actions looks like this:
query getEvents {
events(input: { address: "B62..." }) {
blockInfo {
stateHash
timestamp
ledgerHash
height
parentHash
chainStatus
distanceFromMaxBlockHeight
globalSlotSinceGenesis
}
eventData {
data
}
transactionInfo {
status
hash
memo
}
}
}
query getActions {
actions(input: { address: "B62..." }) {
blockInfo {
stateHash
timestamp
ledgerHash
height
parentHash
chainStatus
distanceFromMaxBlockHeight
globalSlotSinceGenesis
}
actionState {
actionStateOne
actionStateTwo
actionStateThree
actionStateFour
actionStateFive
}
actionData {
data
transactionInfo {
status
hash
memo
}
}
}
}
To see the data exposed, see the GraphQL schema.
The server lets operators connect to an existing Archive Node Postgres database and provides application monitoring with Jaeger.
Finally, the server provides a set of environment variables to configure runtime options such as database connections, CORS origin, logging behaviour, etc.
The server will use the PG_CONN
environment variable to establish a connection to a running Archive Node. Note that PG_CONN
is a connection string, so the expected format looks like 'postgres://postgres:password@localhost:5432/archive'
The server additionally supports multi-host connections for high availability if you are running multiple Archive Nodes. For example, numerous connection strings can be passed to PG_CONN
as 'postgres://localhost:5432,localhost:5433'
. This works the same as the native psql
command. Read more at multiple host URIs.
Connections will be attempted in order of the specified hosts/ports. On a successful connection, all retries will be reset. This ensures that hosts can come up and down seamlessly.
To run an instance of Jaeger locally, see the init_jaeger script. By running the script, a local instance of Jaeger will be instantiated with Docker with default environment variables. If you run it as is, you can access the Jaeger dashboard by visiting http://localhost:16686
.
To enable logging to Jaeger, set the following environment variables:
ENABLE_JAEGER="true"
JAEGER_SERVICE_NAME="archive-api"
JAEGER_ENDPOINT='http://localhost:14268/api/traces'
ENABLE_JAEGER
: Tells the server to allow Jaeger logging. If Jaeger logging is not enabled, all logs will be printed to stdout.
JAEGER_ENDPOINT
: The specified URL for the running Jaeger service.
JAEGER_SERVICE_NAME
: Specifies the service name to be used by Jaeger. The service name will be what identifies the service in the Jaeger logs.
Also, note that Jaeger supports distributed logging. This means that if you're running multiple instances of this server, you can specify the same Jaeger endpoint. All your logs will be consolidated in one place for simplified logging across all your server instances.
This section aims to describe all the environment variables exposed to configure runtime behaviour:
-
APP_COMMAND
: The command to run the server. A sensible default isnpm run start
. -
PG_CONN
: The connection string used to connect to either a single or multiple Archive Nodes. -
ENABLE_INTROSPECTION
: Enable or disable GraphQL introspection. GraphQL introspection is a feature of GraphQL that allows clients to inspect the capabilities of a GraphQL server. It enables clients to discover the types, fields, and other metadata available on the server and query it using this information. -
ENABLE_GRAPHIQL
: GraphiQL is an in-browser tool for working with GraphQL APIs. It provides a user-friendly interface for constructing and executing GraphQL queries, making it easier for developers to test and debug their GraphQL applications. GraphiQL is an excellent tool for development and testing, but it should be considered disabled in a production environment for security-related reasons. -
ENABLE_LOGGING
: Enables logging to either Jaeger or to stdout. IfENABLE_JAEGER
is not defined, butENABLE_LOGGING
is, all logs will be directed to stdout. IfENABLE_JAEGER
is specified, all logs will be directed to the Jaeger server. Logging is done using OpenTelemetry -
ENABLE_JAEGER
: Enable or disable logging to a Jaeger server. If not enabled, all logging is done through stdout. -
JAEGER_ENDPOINT
: A URL that specifies a running Jaeger instance to send logs to. If the./scripts/init_jaeger.sh
was run to instantiate a local instance of Jaeger, the endpoint will behttp://localhost:14268/api/traces
. -
JAEGER_SERVICE_NAME
: The name used to specify your service within Jaeger. This name will be used to identify your specific running server. -
PORT
: The port to be used when running the server. By default, it will use port8080
. -
LOG_LEVEL
: Specifies the level of logs to emit from GraphQL Yoga. See documentation here for more details. -
CORS_ORIGIN
: Specify the CORS origin if you wish to run this server behind a proxy. By default, the server will returnAccess-Control-Allow-Origin: *
.
To see an example of sensible defaults, see the env.example configuration file.
To start the server, run
npm run build
npm run start
or in development mode, run
npm run dev
This will start the server and allow you to interact with the GraphQL API specified with the port defined in your .env
file or port 8080
by deafult. e.g. http://localhost:3000
.
In production, we recommend running this with a process control system pm2 or Supervisor. In addition to using these tools, you could utilize the provided Dockerfile to build and run a container.
To run the tests, you will need a running instance of Lightnet. Lightnet will start a running Postgres instance with a local Mina network and will populate the database with zkApp related data. To run the tests, you will have to run a zkApp script to emit events and actions to the database. To do this, ensure you have Lightnet running on your local machine and then run the following commands:
node --loader ts-node/esm benchmark/setup.ts
This will run a script that will deploy a zkApp and emit events and actions to the database. Once the script is finished, you can run the tests with the following command:
npm run test
To run a benchmark on the Typescript GraphQL server, you will need to have a running Lightnet instance to connect to. See the Running tests section if you still need to run the setup.
You will also need to run the server to run the benchmarks. For example, to run the server in development mode, run the following command:
npm run dev
Once the server is up and running, you can run the benchmarking script by using the following command:
npm run benchmark
This script will run the config defined in benchmarking/graphql.yaml
and output a report in the benchmarking folder. The report will contain summarized metrics of the performance testing run against the server.
It is important to note that the benchmarking script requires the server to run to collect performance metrics. The report generated will provide valuable insights into the server's performance and help identify any potential bottlenecks or areas for improvement. Please note that running the benchmark may consume significant resources and should be done cautiously. Ensure that the server runs in a stable environment before running the benchmarking script.
Running the Archive Node API requires a hardware configuration that can handle the load placed on the server by user requests, with the primary load being on the database. This API is written to be resource efficient; the main bottleneck is expected to be on the database performance, not the Archive Node API process.
To mitigate the load on the database, it is recommended to use the multi-host connection to utilize multiple Archive Node databases. By supplying additional read-only databases for the API to connect to, queries will be spread evenly across all databases, which will help with response time. Additionally, the use of more powerful hardware on existing Archive Node databases should be considered.
To get a real sense of what hardware requirements are needed, you can utilize the benchmarking suite to see how many requests can be handled.
For example, a benchmark report is shown below and was run with an Archive Node API and Postgres database container running on the same machine with a 12-core processor & 32GB of RAM.
--------------------------------------
Metrics for period to: 19:05:30(-0800) (width: 9.999s)
--------------------------------------
http.codes.200: ................................................................ 7908
http.request_rate: ............................................................. 794/sec
http.requests: ................................................................. 7915
http.response_time:
min: ......................................................................... 1
max: ......................................................................... 54
median: ...................................................................... 15
p95: ......................................................................... 30.9
p99: ......................................................................... 39.3
http.responses: ................................................................ 7908
vusers.completed: .............................................................. 7907
vusers.created: ................................................................ 7916
vusers.created_by_name.Get Actions: ............................................ 3885
vusers.created_by_name.Get Events: ............................................. 4031
vusers.failed: ................................................................. 0
vusers.session_length:
min: ......................................................................... 2.4
max: ......................................................................... 55.5
median: ...................................................................... 16
p95: ......................................................................... 32.1
p99: ......................................................................... 40
To set up a local development environment, you can use the zkApp-CLI Lightnet. This tool allows you to run a local Mina network with zkApps enabled. The zkApp-CLI Lightnet will also start a running Postgres instance with a local Mina network and will populate the database with zkApp related data. Once you have the zkApp-CLI Lightnet running, you can run the server and interact with the GraphQL API.
To see how to set up the zkApp-CLI Lightnet, see the zkApp-CLI Lightnet documentation.
If you wish to populate the database with zkApp related data, you can run the following commands:
node --loader ts-node/esm benchmark/setup.ts
This will run a script that will deploy a zkApp and emit events and actions to the database. Once the script is finished, you can run the server with the following command:
npm run dev
To ensure you have the correct environment variables set up, you can see a copy of the .env.example.lightnet
file.
Generally, it is recommended that you use Lightnet as your local development environment, as it will provide you with a running Mina network and a Postgres instance with zkApp related data.
The provided docker-compose.yml
file simplifies the process of setting up a local development environment. This file orchestrates the creation of a Docker network comprising of Mina daemon, Archive Node, GraphQL server, and Jaeger. Follow the steps below to get everything up and running:
Step 1: Libp2p Keypair Generation
You will need a libp2p keypair for the setup. If you don't already have one, you can easily generate a keypair specifically for local development (note: this should not be used in production). Use the script provided in the repository:
./scripts/generate_libp2p.sh
Step 2: Update Environment Variables
Once you have generated the keypair, make sure to update your .env
file with the passwords that were used during the keypair generation process.
Step 3: Launch the Docker Network
With the prerequisites in place, start the Docker network by running the following command in your terminal:
docker compose up
This command pulls the necessary Docker images and launches them, setting up a local environment ideal for server development. This setup offers a way to connec to a live running Mina network, specified by it's seed peers and Mina daemon build. Use this setup to test the server's functionality and performance against a live running network.