Sandbox Quick Start¶
The TRAC sandbox is a self-contained distribution of TRAC D.A.P. that can run on a single machine. It includes all the functionality of the platform in one ready-to-use bundle. Of course, it doesn’t have the power and scalability available with a cloud deployment or physical cluster. Technology controls are not enforced, so developers with access to the server can delete or modify data, or change the deployment entirely.
The sandbox is useful for development, testing, PoCs and small-scale demo scenarios. It can be used to develop and test end-to-end processes, including models, model chains, data preparation, applications / UIs and control / sign-off workflows. All these items should work without modification when deployed to a real production instance of TRAC (subject to capacity constraints and assuming models are coded in line with TRAC conventions).
The TRAC platform sandbox is available to download on the GitHub release page:
You want the tracdap-sandbox zip file, the package will work on Linux, macOS and Windows. Unless you have a good reason, always use the latest stable release.
Deploying the sandbox¶
TRAC requires Java version 11 or higher, using LTS 11 or LTS 17 is recommended. Suitable JDKs are available from Azul (Zulu) and Adoptium (Eclipse Temurin). If your company restricts software deployment, it is fine to use the Java package they provide so long as it is version 11 or higher.
TRAC requires Python 3.7 or higher, which can be downloaded and installed from python.org. If your company restricts software deployment, it is fine to use the Python package they provide so long as it is version 3.7 or higher.
Start by creating a directory for your TRAC installation and unzipping the sandbox distribution.
mkdir /opt/trac cd /opt/trac unzip path/to/downloads/tracdap-sandbox-<version> # Having a "current" link makes it easy to upgrade and switch versions later ln -s tracdap-sandbox-<version> current
Create a directory C:\trac then unzip the TRAC sandbox zip in this folder.
You’ll also need to create directories for storing both data and metadata. These should be outside of the versioned deployment folder, because you want to keep them when you install newer versions of the platform.
mkdir /opt/trac/data mkdir /opt/trac/metadata
mkdir C:\trac\data mkdir C:\trac\metadata
The metadata service requires a JDBC database driver, which must be copied as a JAR file into the plugins folder of the TRAC installation. To use the H2 embedded database, you can download the H2 JDBC JAR from Maven Central:
If you are behind a corporate firewall, you may need to use a web proxy and/or point at a Nexus server hosted inside your network.
VENV for model execution
You will need to set up a Python VENV with the TRAC runtime library installed, which will be used for executing models. If you have multiple versions of Python installed, make sure to use the right one to create your venv.
cd /opt/trac/trac-platform-<version> python -m venv ./venv . venv/bin/activate pip install "tracdap-runtime == <version>"
cd C:\trac\trac-platform-<version> python -m venv .\venv venv\Scripts\activate pip install "tracdap-runtime == <version>"
The pip install command will download the TRAC runtime package for Python from PyPi. If you are behind a corporate firewall, you may need to use a web proxy and/or point at a Nexus server hosted inside your network.
The sandbox deployment comes with some example configuration to use as a starting point. Below is a quick walk through of the major sections and what they all do, for a standalone sandbox most of these settings can be left as they are, with just the locations of key resources to be filled in. Before editing these configuration files, it is recommended to take a copy as a backup, in case you need to refer to it later.
The config section refers to other configuration files or sources. The example config includes a logging config file and a local secret store using the PKCS12 format. We’ll set up the secret store later using the TRAC setup tools.
config: logging: trac-logging.xml secret.type: PKCS12 secret.url: secrets.p12
Relative file names or URLs in the config section will be taken relative to the main config file.
The platformInfo section allows you to specify some information about the TRAC environment. This is made available to clients and can be shown in UIs and client apps, so users know which environment they are connected to.
platformInfo: environment: SANDBOX production: false
The authentication section controls the platform’s internal authentication mechanism, which uses JWT. This is to allow the platform to validate user tokens and to let different platform services talk to each other.
The task of actually logging users in and obtaining their details is handled by the gateway component, so the configuration for this is in the gateway config file. The JWT details supplied here need to match what is in the gateway config file.
authentication: jwtIssuer: trac_platform jwtExpiry: 3600 jwtLimit: 57600
The metadata section describes how and where the TRAC metadata will be stored. The current implementation uses SQL to store metadata and several common SQL dialects are supported. The default sandbox config uses the H2 embedded database for the simplest possible setup, you just need to add the path for the metadata folder created above. For examples of how to configure other SQL dialects, see the deployment docs for the metadata store.
metadata: format: PROTO database: protocol: JDBC properties: dialect: H2 # Set the path to your H2 metadata file here jdbcUrl: /path/to/metadata/trac.meta h2.user: trac h2.pass: trac h2.schema: public pool.size: 10 pool.overflow: 5
H2 is mostly used in development scenarios where the password is not sensitive. If you want to use a secret for the H2 password, see Using Secrets.
The storage section allows you to configure one or more storage buckets to hold primary data. In TRAC, a “bucket” is any storage location that can hold files, which could be a cloud storage bucket on a cloud platform but can also be a local folder. Other protocols such as network storage or HDFS can also be supported with the appropriate storage plugins.
The defaultBucket and defaultFormat settings tell TRAC where to store new data by default. These defaults can be changed later, data that is already written will be picked up using the correct location and format.
The sample configuration contains one storage bucket, you just need to specify a path.
storage: defaultBucket: STORAGE1 defaultFormat: ARROW_FILE buckets: STORAGE1: protocol: LOCAL properties: # Set the path to your local storage location here rootPath: /path/to/data/storage1
Pay particular attention to the bucket key, which is STORAGE1 in this example. The bucket key is a unique identifier for a storage location, you may want to give it a meaningful name, for example relating to your project or business division.
The repositories section let’s you configure model repositories, that TRAC will access to load models into the platform. The sample config includes the TRAC repository as an example, you should replace this with your own model repository and choose a meaningful repository key. You can add multiple repositories if required, so long as each one has a unique key.
repositories: # Add your own repositories in here to load models into TRAC trac_repo: protocol: git properties: repoUrl: https://github.com/finos/tracdap
The last thing you need to add in the platform config is an executor. The example config is already set up with a local executor, so you just need to add the path for the VENV you built in the deployment step.
executor: protocol: LOCAL properties: # Set this to the venv of your local TRAC execution environment venvPath: /path/to/venv
There are two more sections in the platform config, services and instances. The services section sets up the service properties for each service, most importantly the ports they should run on. The instances section lists the instances of each service. For a sandbox setup there is no need to alter these sections.
The gateway example config will work without alteration to serve the API endpoints for the TRAC services. However, the gateway can also be used to route requests for client applications; this is particularly useful for web applications in a dev / test scenario, because it provides a direct route to access the TRAC API and avoids CORS issues. If you want to use this capability, look in the gateway config and you will find an example of setting up an additional HTTP route. You can add as many HTTP routes as you need.
The example configuration uses guest authentication, which logs all users in as “guest” without requiring a password. To set up real user logins, see the deployment docs for authentication.
Logging is provided using log4j, the example configuration writes to the local log/ directory by default.
Environment variables can be specified in the shell before launching the TRAC services. Alternatively, an environment file is available for both Linux / macOS (env.sh) and Windows (env.bat). These can be useful for specifying system settings, such as JAVA_HOME to select a particular installation of Java, or JAVA_OPTS to control the JVM memory parameters. You can also control some of the TRAC options here, e.g. setting CONFIG_FILE will tell trac to load a different root config file.
For sandbox setups, the main variable to set in this file is TRAC_SECRET_KEY. This is the master key for the TRAC secret store, that unlocks all the other secrets in the configuration. In production setups this key should not be stored in a file, but passed in through the environment using a scheduling tool, or as part of a containerized job setup.
TRAC D.A.P. comes with a few tools to simplify the deployment. There are two we need to use for a sandbox setup, secret-tool and deploy-metadb.
The secret-tool utility is used to manage secrets, certificates and other sensitive configuration. It can also be used to manage users if you are using a local user database. The tool will write secrets to the secret store configured in the platform configuration. If this is a local keystore file and it does not exist then it will be created. Make sure you have set the TRAC_SECRET_KEY environment variable before using secret-tool.
For the sandbox setup we need a minimum of one secret, the root authentication key. This key is used by TRAC to sign and verify its internal JWT tokens. The available key types for the root authentication key are elliptic curve (EC) or RSA. Elliptic curve keys are considered to give better security with better performance at lower key sizes, so for this reason we recommended EC 256 keys.
cd /opt/trac/current bin/secret-tool run --task init_secrets bin/secret-tool run --task create_root_auth_key EC 256
cd /d C:\trac\tracdap-sandbox-<version> bin\secret-tool.bat run --task init_secrets bin\secret-tool.bat run --task create_root_auth_key EC 256
Running the create_root_auth_key command a second time will replace the root authentication key, which will invalidate any existing JWT tokens.
TRAC D.A.P. comes with a tool to help deploy the metadata database. It runs off the same configuration as the platform services, so make sure to finish updating your configuration before running the tool.
We need to perform two tasks to prepare the database: deploy the schema and create a tenant. Choose a tenant code and description that is meaningful for your project or business division. The description can be altered later but the tenant code cannot.
cd /opt/trac/current bin/deploy-metadb run --task deploy_schema bin/deploy-metadb run --task add_tenant ACME_CORP "ACME Supplies Inc." bin/deploy-metadb run --task alter_tenant ACME_CORP "ACME Mega Supplies Inc."
cd /d C:\trac\tracdap-sandbox-<version> bin\deploy-metadb.bat run --task deploy_schema bin\deploy-metadb.bat run --task add_tenant ACME_CORP "ACME Supplies Inc." bin\deploy-metadb.bat run --task alter_tenant ACME_CORP "ACME Mega Supplies Inc."
Start the services¶
Once the configuration is done and the setup tools have be run, all that remains is to start the services:
cd /opt/trac/current bin/tracdap-svc-meta start bin/tracdap-svc-data start bin/tracdap-svc-orch start bin/tracdap-gateway start
cd /d C:\trac\tracdap-sandbox-<version> bin\tracdap-svc-meta.bat start bin\tracdap-svc-data.bat start bin\tracdap-svc-orch.bat start bin\tracdap-gateway.bat start
By default, the gateway will be listening on port 8080 and logs will be written to the log/ directory in the installation folder.
To test that the services are running, you can use Postman to send REST requests to the TRAC APIs. There are some example REST requests available in the TRAC GitHub repo.
The service control scripts provide several commands which may be helpful:
start - Start the service
stop - Stop the service
restart - Stop then immediately start the service
status - Indicate whether a service is up or down
kill - Kill the service immediately (Send SIGKILL, do not process a clean shutdown)
kill_all - Find and kill all running instances of the service
run - Run the service in the foreground
The run option requires a separate console for each service and will terminate the service on Ctrl-C. For this configuration, it is recommended to enable logging to stdout in trac-logging.xml.