System Patch Manager is one of the applications for console.redhat.com. This application allows users to display and manage available patches for their registered systems. This code repo stores sources for the backend part of the application which provides the REST API to the frontend.
- Architecture
- Database
- Development environment
- Control by private API
- VMaaS
- Monitoring
- [Profiling] (#profiling)
Uses podman-compose
to deploy the individual project components and supporting containers, which simulate the CMSfR platform and database:
podman-compose up --build # Build images if needed and start containers
podman-compose down # Stop and remove containers
When podman compose is running, you can test the app using dev shell scripts:
cd dev/scripts
./systems_list.sh # show systems
./advisories_list.sh # show advisories
./platform_sync.sh # trigger vmaas_sync to sync (using vmaas mock)
./platform_upload.sh # simulate archive upload to trigger listener and evaluator_upload
Run single component in host OS, rest in podman-compose:
podman-compose stop evaluator_upload # stop single component running using podman-compose
export $(xargs < conf/local.env)
./scripts/entrypoint.sh evaluator # (or listener, or manager) run component in host OS
We cover a large part of the application functionality with tests; this requires also running a test database and mocked services. This is all encapsulated into the configuration runable using podman-compose command. It also includes static code analysis, database migration tests and dockerfiles checking. It's also used when checking pull requests for the repo.
podman-compose -f docker-compose.test.yml up --build --abort-on-container-exit
After running all test suit, testing platform components are still running (kafka, platform, db). This is especially useful when fixing some test or adding a new one. You need to have golang installed.
podman-compose -f docker-compose.test.yml up --build --no-start # build images
podman-compose -f docker-compose.test.yml start db platform zookeeper kafka # start containers
. scripts/export_local_env.sh # setup needed env variables for tests
go test -count=1 -v ./evaluator -run TestEvaluate # run "TestEvaluate" test from "evaluator" component
Prerequisite is to have Go Extension installed.
To set it up copy the example settings from .vscode/settings.example.json
:
cp .vscode/settings.example.json .vscode/settings.json
When a podman compose (either dev or test one) is running, then the database can be access directly by executing
podman exec -it db psql -d patchman -U admin
or locally using psql
with:
export $(cat conf/local.env conf/database_admin.env | xargs ) 2>/dev/null; ./dev/scripts/psql.sh
Our REST API is documented using OpenAPI v3. On a local instance it can be accessed on http://localhost:8080/openapi/index.html.
To update/regenerate OpenAPI sources run:
go get -u github.com/swaggo/swag/cmd/swag # download binary to generate, do it first time only
./scripts/generate_docs.sh
There is a private API accessible only from inside of vmaas_sync
container. It allows running component routines manually. In local environment it can be tested like this:
podman exec -it patchman-engine_vmaas_sync_1 ./sync.sh # trigger advisories syncing event.
podman exec -it patchman-engine_vmaas_sync_1 ./re-calc.sh # trigger systems recalculation event.
podman exec -it patchman-engine_vmaas_sync_1 ./caches-check.sh # trigger account caches checking.
This project uses VMaaS for retrieving information about advisories, and resolving which advisories can be applied to which systems. For local development this repo contains VMaaS service mock as a part of platform mock allowing independent running of the service using podman-compose.
Each application component (except for the database) exposes metrics for Prometheus
on /metrics
endpoint (see docker-compose.yml for ports). Runtime logs can be sent to Amazon
CloudWatch if configuration environment variables are set (see awscloudwatch.go).
Your can control and inspect def Kafka instance using:
docker-compose exec kafka bash # enter kafka component and run inside:
/usr/bin/kafka-topics --list --bootstrap-server=kafka:9092 # show created topics
# list all messages send to a topic
/usr/bin/kafka-console-consumer --bootstrap-server=kafka:9092 --topic platform.inventory.events --from-beginning
# send debugging message to a topic
echo '{"id":"00000000-0000-0000-0000-000000000002"}' | /usr/bin/kafka-console-producer --broker-list kafka:9092 --topic patchman.evaluator.upload
export SONAR_HOST_URL=https://sonar-server
export SONAR_LOGIN=paste-your-generated-token
export SONAR_CERT_URL=https://secret-url-to/ca.crt # optional
podman-compose -f dev/sonar/docker-compose.yml up --build
Copy Grafana board json config to the temporary file, e.g. grafana.json
and run:
./scripts/grafana-json-to-yaml.sh grafana.json > ./dashboards/grafana-dashboard-insights-patchman-engine-general.configmap.yaml
App can be profiled using /net/http/pprof. Profiler is exposed on app's private port.
- set
ENABLE_PROFILE=true
in thecont/common.env
docker-compose up --build
go tool pprof http://localhost:{port}/debug/pprof/{heap|profile|block|mutex}
available ports:- 9000 - manager
- 9002 - listener
- 9003 - evaluator-upload
- 9004 - evaluator-recalc
- set
ENABLE_PROFILE_{container_name}=true
in the ClowdApp - download the profile file using internal api
/api/patch/admin/pprof/{manager|listener|evaluator_upload|evaluator_recalc}/{heap|profile|block|mutex|trace}
go tool pprof <saved.file>