Graphql schema storage as dockerized on-premise service for federated graphql gateway server (based on apollo server) as alternative to Apollo studio and The Guild's Hive
- Stores versioned schema for graphql-federated services
- Serves supergraph schema for graphql gateway based on provided services & their versions
- Validates new schema to be compatible with other running services
- Provides UI for developers to see stored schema & its history diff
- Stores service urls emulating managed federation: you no longer need to hardcode the services in your gateway's constructor, or rely on an additonal service (etcd, consul) for service discovery
- Does async schema usage analysis to minimize breaking changes from reaching production
- Publishes schema registration events to minimize supergraph update time
- Stores & shows in UI automatic persisted queries (passed by the gateway) for better visibility
Oct-11-2022.02-28-28.mp4
With default settings, UI should be accessible at https://localhost:6001
git clone https://github.com/pipedrive/graphql-schema-registry.git && cd graphql-schema-registry
cp example.env .env && nano .env
npm install && npm run build
node app/schema-registry.js
We have docker image published for main node service.
It assumes you have mysql/redis running separately.
Use exact IP instead of localhost
.
Use exact docker image tag to avoid breaking changes.
docker pull pipedrive/graphql-schema-registry:5.0.0
docker run -e DB_HOST=localhost -e DB_USERNAME=root -e DB_PORT=6000 -p 6001:3000 pipedrive/graphql-schema-registry
git clone https://github.com/pipedrive/graphql-schema-registry.git && cd graphql-schema-registry
docker-compose -f docker-compose.base.yml -f docker-compose.prod.yml up
flowchart LR
GW[federated-gateway] == poll schema every 10 sec\n POST /schema/compose ==> SR["schema registry\n(gql-schema-registry)"] -- store schemas --> DB[("mysql 8\n(gql-schema-registry-db)")]
SR -- cache persisted queries\nstore & query last logs --> R[("redis 6\n(gql-schema-registry-redis)")]
SR -- publish schema change --> KF1("kafka\n(gql-schema-registry-kafka)\ngraphql-schema-updates topic") -- listen schema updates --> GW
GW -- publish queries --> KF2("kafka\n(gql-schema-registry-kafka)\ngraphql-queries topic")
KF2 --> QA["query analyzer\n(gql-schema-registry-worker)"]
QA --update schema hits --> DB
GW -- query A --> S1["service A"] -- register schema in runtime --> SR
GW -- query B --> S2["service B"] -- register schema in runtime --> SR
S2["service B"] -. validate schema \n on commit/cli/CI .-> SR
style KF1 fill:#0672e6,color:white
style KF2 fill:#0672e6,color:white
style DB fill:#0672e6,color:white
style R fill:#0672e6,color:white
style SR fill:#ffe43e
style QA fill:#ffe43e
style GW fill:#c5f7c9
style S1 fill:#c5f7c9
style S2 fill:#c5f7c9
Name | Role | Description |
---|---|---|
federated gateway | Required | Apollo server running in federated mode. You should have your own. Check examples folder how to configure it. Note however, that gateway is very simplified and does not have proper error handling, query cost limit checks or fail-safe mechanisms. |
schema registry | Required | Main service that we provide |
mysql | Required | Main data storage of schemas and other derivative data |
query analyzer | Optional | Processes queries in async mode, required for usage tracking. Main code in /src/worker folder |
kafka | Optional | Ties schema-registry and federated gateway with async messaging. Required for fast schema updates and for usage tracking |
redis | Optional | Caching layer for APQs. Not used much atm |
Frontend (/client folder) |
Backend (/src folder) |
---|---|
react | nodejs 16 |
apollo client | express, hapi/joi |
styled-components | apollo-server-express, dataloader |
redis 6 | |
knex | |
mysql 8 |
Migrations are done using knex
erDiagram
services {
id int PK
name varchar
is_active int
updated_time datetime
added_time datetime
url varchar
}
clients {
id int PK
name varchar
version varchar
calls bigint
updated_time datetime
added_time datetime
}
schema {
id int PK
service_id int FK
is_active tinyint
type_defs mediumtext
updated_time datetime
added_time datetime
}
container_schema{
id int PK
service_id int FK
schema_id int FK
version varchar
added_time datetime
}
persisted_queries{
key varchar PK
query text
is_active int
updated_time datetime
added_time datetime
}
clients_persisted_queris_rel{
version_id int
pq_key varchar
}
schema_hit{
client_id int
entity varchar
property varchar
day date
hits bigint
updated_time bigint
}
services ||--o{ schema : defines
schema ||--|{ container_schema : "is registered by"
clients_persisted_queris_rel ||--|{ persisted_queries : use
clients_persisted_queris_rel ||--|{ clients : have
clients ||--|{ schema_hit : "use schema properties"
schema ||..|{ schema_hit : "relates to"
We use environment variables for configuration. You can:
- pass them directly
- add .env file and dotenv will pick them up
- add them to
docker-compose.yml
orDockerfile
The following are the different environment variables that are looked up that allow configuring the schema registry in different ways.
Variable Name | Description | Default |
---|---|---|
DB_HOST | Host name of the MySQL server | gql-schema-registry-db |
DB_USERNAME | Username to connect to MySQL | root |
DB_SECRET | Password used to connect to MySQL | root |
DB_PORT | Port used when connecting to MySQL | 3306 |
DB_NAME | Name of the MySQL database to connect to | schema-registry |
DB_EXECUTE_MIGRATIONS | Controls whether DB migrations are executed upon registry startup or not | true |
REDIS_HOST | Host name of the Redis server | gql-schema-registry-redis |
REDIS_PORT | Port used when connecting to Redis | 6379 |
REDIS_SECRET | Password used to connect to Redis | Empty |
ASSETS_URL | Controls the url that web assets are served from | localhost:6001 |
NODE_ENV | Specifies the environment. Use production to load js/css from dist/assets |
Empty |
ASYNC_SCHEMA_UPDATES | Specifies if async achema updates is enabled | false |
KAFKA_BROKER_HOST | Host name of the Kafka broker, used if ASYNC_SCHEMA_UPDATES = true | gql-schema-registry-kafka |
KAFKA_BROKER_PORT | Port used when connecting to Kafka, used if ASYNC_SCHEMA_UPDATES = true | 9092 |
KAFKA_SCHEMA_TOPIC | Topic with new schema | graphql-schema-updates |
KAFKA_QUERIES_TOPIC | Topic with new schema | graphql-queries |
LOG_LEVEL | Minimum level of logs to output | info |
LOG_TYPE | Output log type, supports pretty or json. | pretty |
For development we rely on docker network and use hostnames from docker-compose.yml
.
Node service uses to connect to mysql & redis and change it if you install it with own setup.
For dynamic service discovery (if you need multiple hosts for scaling), override app/config.js
and diplomat.js
On service start-up (runtime), make POST to /schema/push to register schema (see API reference for details). Make sure to handle failure.
See example for nodejs/ESM.
Usually in production, POST /schema/push
requires unique version
that should be unique git or docker hash.
But, if you are developing a service and you run schema-registry locally, you can set version: "latest"
to skip this version check.
- if your gateway uses /schema/compose then no, schema is composed based on services you see as healthy
- if your gateway uses /schema/latest then yes, service has
is_active
flag in DB that you can manually toggle (no API yet)
On pre-commit / deploy make a POST /schema/validate to see if its compatible with current schema. If you have multiple regions or environments (test), makes sense to check all.
If service A contains schema that needs to be migrated to service B with close to 0 downtime, you will need to orchestrate schema & traffic change. Instead of juggling with schema status flags, we suggest the following scenario:
sequenceDiagram
participant service_A
participant service_B
participant schemaRegistry
loop Every 5 sec
service_B->>+schemaRegistry: register schema B + A1
schemaRegistry->>-service_B: validation error, A1 is registered to service A
end
service_A->>+schemaRegistry: remove schema A1
schemaRegistry->>-service_A: ok
service_B->>+schemaRegistry: register schema B + A1
schemaRegistry->>-service_B: ok, A1 is registered to service B, stop retries
nvm use
npm install
npm run build
docker-compose -f docker-compose.base.yml -f docker-compose.dev.yml up
To have fast iteration of working on UI changes, you can avoid running node service in docker, and run only mysql & redis
docker-compose -f docker-compose.base.yml up -d
npm run develop
npm run develop-worker
To create new DB migration, use:
npm run new-db-migration
If not using the default configuration of executing DB migrations on service startup, you can run the following npm
command prior to starting the registry:
npm run migrate-db
The command can be prefixed with any environment variable necessary to configure DB connection (in case you ALTER DB with another user), such as:
DB_HOST=my-db-host DB_PORT=6000 npm run migrate-db
use jest, coverage is quite low as most logic is in db or libraries.
npm run test
require docker, mostly blackbox type - real http requests are done against containers.
DB tables are truncated after every test from within test/functional/bootstrap.js
Jest runs in single worker mode to avoid tests from affecting each other due to same state.
#docker-compose -f docker-compose.light.yml up -d
#npm run develop
npm run test-functional
use k6 + dockerized setup similar to functional tests above + grafana and influxdb for reporting the load these tests are intended just to show/detect avg latencies of most important endpoints
docker-compose -f docker-compose.perf-tests.yml up
open https://localhost:8087/dashboard/import
// Add "2587" to ID, pick influxdb datasource, import dashboard and observe it when you run tests
docker-compose -f docker-compose.perf-tests.yml run --rm k6 run /scripts/schema-latest.test.js
If you change build process in Dockerfile or Dockerfile.CI, consider checking also testing it
# run db
docker-compose -f docker-compose.light.yml up
#build local image
docker build -t local/graphql-schema-registry .
# try to run it
docker run -e DB_HOST=$(ipconfig getifaddr en0) -e DB_USERNAME=root -e DB_PORT=6000 -p 6001:3000 local/graphql-schema-registry
- There is not strict process on finding or updating vulnerabilitites. The license also states there there is no Liability or Warranty, so be aware of that
- You can use Slack or Github discussions / issues as a communication channel to notify about vulnerabilities.
- We use snyk in PR checks. We try to look at
npm audit
reports manually on PR creation to minimize issues. - We intentionally use strict versioning of nodejs dependencies which prevents automatic dependabot PRs. Thus version upgrades are manual. Why? Because sometimes we saw external dependencies rolling out breaking changes in minor/patch versions which broke our master. Same thing with hacked libraries.
- Commit often (instead of making huge commits)
- Add verb at the beginning of commit message
- Add why you're doing something in commit message
- Reference issues
- When making a pull request, be sure to follow the format of what is the problem you're fixing, what was changed & how to test it. Screenshots/videos are a welcome
- Fill CHANGELOG
- To avoid vulnerabilities, please use fixed versions in package.json
Current maintainer - @tot-ra. Mention in PR, if it is stuck
Original internal mission that resulted in this project going live:
See main blog post
Simplified version of /schema/compose where latest versions from different services are composed. Some services prefer this to use this natural schema composition, as its natural and time-based.
Advanced version of schema composition, where you need to provide services & their versions. Used by graphql gateway to fetch schema based on currently running containers.
The advantage over time-based composition is that versioned composition allows to automatically update federated schema when you deploy older version of the pod in case of some incident. If you deploy older pods they can ofc try to register old schema again, but as it already exists in schema-registry, it will not be considered as "latest".
{
"services": [
{ "name": "service_a", "version": "ke9j34fuuei" },
{ "name": "service_b", "version": "e302fj38fj3" }
]
}
- β 400 "services[0].version" must be a string
- β 500 Internal error (DB is down)
- β 200
{
"success": true,
"data": [
{
"id": 2,
"service_id": 3,
"version": "ke9j34fuuei",
"name": "service_a",
"url": "https://localhost:6111",
"added_time": "2020-12-11T11:59:40.000Z",
"type_defs": "\n\ttype Query {\n\t\thello: String\n\t}\n",
"is_active": 1
},
{
"id": 3,
"service_id": 4,
"version": "v1",
"name": "service_b",
"url": "https://localhost:6112",
"added_time": "2020-12-14T18:51:04.000Z",
"type_defs": "type Query {\n world: String\n}\n",
"is_active": 1
}
]
}
- services{ name, version}
If services
is not passed, schema-registry tries to find most recent versions. Logic behind the scenes is that schema with highest added_time
OR updated_time
is picked as latest. If time is the same, schema.id
is used.
Validates and registers new schema for a service.
{
"name": "service_a",
"version": "ke9j34fuuei",
"type_defs": "\n\ttype Query {\n\t\thello: String\n\t}\n"
}
URL is optional if you use urls from schema-registry as service discovery
{
"name": "service_b",
"version": "jiaj51fu91k",
"type_defs": "\n\ttype Query {\n\t\tworld: String\n\t}\n",
"url": "https://service-b.develop.svc.cluster.local"
}
- β 400 "You should not register different type_defs with same version."
Validates schema, without adding to DB
- name
- version
- type_defs
Compares schemas and finds breaking or dangerous changes between provided and latest schemas.
- name
- version
- type_defs
Deletes specified schema
Property | Type | Comments |
---|---|---|
schemaId |
number | ID of sechema |
Deletes specified service including all schemas registered for that service
Property | Type | Comments |
---|---|---|
name |
string | name of service |
Looks up persisted query from DB & caches it in redis if its found
Property | Type | Comments |
---|---|---|
key |
string | hash of APQ (with apq: prefix) |