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zebedee's Introduction

Zebedee

NOTE: We are currently in the process of deprecating this service due to:

  • Performance limitations
  • Maintainability issues
  • Inability to scale effectively
  • Limitations of the underlying HTTP framework

Zebedee is the CMS used by the ONS website and the internal website publishing system. It is a JSON API and does not have a user interface. It comes in 2 flavours:

zebedee-reader

Zebedee-reader is read-only. It's used by Babbage (the public facing web frontend of the ONS website) it returns the published site content as JSON.

zebedee-cms

Zebedee-cms is an extension of zebedee-reader. It's used by Florence and provides API endpoints for managing content, users, teams and publishing collecions. Zebedee-CMS is not public facing and requires authentication for the majority functionality. Pre-release content is encrypted and requries the appropriate permissions to be able to access it.

Prerequisites

  • git
  • Java 8
  • Maven
  • Docker

As mentioned Zebedee is a JSON API, and does not have a user interface. The quickest and easiest way to use it is to set up a local copy of the "publishing" stack. Clone and set up the following projects following the README instructions in each repo:

Getting started


If you encounter any issues or notice anything missing from this guide please update/add any missing/helpful information and open a PR.

Much appreciated. The Dev team


NOTE: The following set guide will set up Zebedee in "CMS" mode as this is typically how the devlopers will run the stack locally.

Getting the code:

git clone [email protected]:ONSdigital/zebedee.git

Database...

Zebedee isn't backed by a database instead it uses a file system to store json files on disk ***. As a result it requires a specific directory structure in order to function correctly.


*** We know this is a terrible idea - but in our defence this is a legacy hangover and we are actively working towards deprecating it.


To save yourself some pain you can use the dp-zebedee-content tool to create the required directory structure and populate the CMS with some "default content" - follow the steps in the README before going any further.

Once the script has run successfully copy the generated script from dp-zebedee-utils/content/generated/run-cms.sh into the root dir of your Zebedee project. This bash script compiles and runs Zebedee setting typical dev default configuration and uses the content / directory structure generated by dp-zebedee-utils.

You may be required to make the bash script an executable before you can run it. If so run:

sudo chmod +x run-cms.sh
<Enter your password when prompted>

Running the publishing stack

In order to use Zebedee you will need to have the following other project running:

  • Florence
  • Babbage
  • Sixteens
  • dp-compose
  • dp-identity-api

Follow the steps in the README of each project.

Zebedee content

Zebedee needs contents before it can be run. Basic demo content and file structures can be generated via the dp-zebedee-content by following the instructions in the dp-zebedee-content readme

Running zebedee

./run-cms.sh

Assuming Zebedee has started without error head to Florence login and login with the default account:

email: [email protected]
password: Doug4l
  • If it's the first time logging in you will be prompted to change the password for that user.
  • On the home screen create a new collection.
  • Click Create/edit on the Collection Details screen.

If everything is working correctly you should now see the the ONS website displayed in the right hand pane. Congratulations ๐ŸŽ‰! Advanced to GO collect ยฃ200 ๐Ÿ’ต

Otherwise ๐ŸŽป kindly ask someone from the dev team to help troubleshoot.

Optional configuration options

Environment variable Default Description
DEFAULT_WEBSITE_URL "http://localhost:8080" Service URL
DEFAULT_SLACK_WARNING_CHANNEL "slack-client-test" Slack channel
DEFAULT_SLACK_ALARM_CHANNEL "slack-client-test" Slack alarm channel
DEFAULT_SLACK_USERNAME "Zebedee" Slack user
DEFAULT_PUBLIC_WEBSITE_URL "http://localhost:8080" Service public URL
DEFAULT_FLORENCE_URL "http://localhost:8081" Florence URL
DEFAULT_BRIAN_URL "http://localhost:8083" Brian URL
DEFAULT_TRAIN_URL "http://localhost:8084" Train URL
DEFAULT_DYLAN_URL "http://localhost:8085" Dylan URL
CONTENT_DIRECTORY "content" Content directory
KAFKA_SEC_PROTO unset if set to "TLS", kafka connections will use TLS
KAFKA_SEC_CLIENT_CERT unset PEM for the client certificate 1
KAFKA_SEC_CLIENT_KEY unset PEM for the client key 1
MATHJAX_SERVICE_URL "http://localhost:8888" Mathjax service URL
DATASET_API_URL "http://localhost:22000" Dataset API URL
IMAGE_API_URL "http://localhost:24700" Image API URL
ENABLE_KAFKA false Feature flag to send kafka messages when a collection is published
KAFKA_ADDR "localhost:9092" Comma seperated list of kafka brokers
KAFKA_CONTENT_UPDATED_TOPIC content-updated Kafka topic to send content updated event to
DATASET_API_AUTH_TOKEN "FD0108EA-825D-411C-9B1D-41EF7727F465" Dataset API authentication token
SERVICE_AUTH_TOKEN "15C0E4EE-777F-4C61-8CDB-2898CEB34657" Service API authentication token
SESSIONS_API_URL "http://localhost:24400" Session API URL
KEYRING_SECRET_KEY "KEYRING_SECRET_KEY"; Keyring encryption key
KEYRING_INIT_VECTOR "KEYRING_INIT_VECTOR" Keyring init vector
VERIFY_RETRY_DELAY 5000; //milliseconds Retry delay duration
VERIFY_RETRY_COUNT 10 Retry count for how long, in seconds, to wait for retry
DEFAULT_PREPROCESS_SECONDS_BEFORE_PUBLISH 30 how many seconds before the actual publish time should we run the preprocess
DEFAULT_SECONDS_TO_CACHE_AFTER_SCHEDULED_PUBLISH 30 how many additional seconds after the publi
IDENTITY_API_URL "http://localhost:25600" Identity API URL

New Central Keyring configuration

The new central keyring feature is currently behind a feature flag:

export ENABLE_CENTRALISED_KEYRING=true/false
  • If enabled Zebedee will attempt to read/write from the new central keyring and default to the legacy keyring if unsuccessful.
  • If disabled Zebedee will add/remove keys from both legacy and central keyring implementations but will only read from the legacy keyring.

The central keyring requires encryption config to be provided in app configutation. These secrets can be generated using the collection-keyring-secrets-generator.


๐Ÿ•ท๏ธ ๐Ÿ•ท๏ธ ๐Ÿ•ท๏ธ ๐Ÿ•ท๏ธ

Legacy dataset versions defect

There is currently an intermittant defect where the previous versions of a dataset are not being correctly added to the reviewed directory of the collection. This causes complications if it goes unnoticed and the collection is published. Work is ongoing to identify the cause.

To combat this an additonal check has been added to the /approve endpoint. If the collection contains dataset pages that are missing any of the expected versions the approval will be rejected.

Bypassing the check

This check (if enabled) can be manually bypassed by a publisher user using an overrideKey on the approval request.

This should only be used as a last resort. Publising a collection in this state will require a manual datafix on the live environment and should only be done with service manager approval.

To bypass this check:

  • Login into Florence and use the Chrome developer tools to get the collection ID and auth token for your user (remember you must be a publisher user).
  • Use the dp-cli tool to access to publishing / publishing_mount
  • Run sudo docker ps -a to get the IPand port for the publishing Zebedee instance
  • Generate an override key - The number of minutes remaining until midnight (UTC). You can use the dp tool to calculate this for you - dp override-key
  • From the publishing box run the following curl command:
curl -H "X-Florence-Token: <ZEBEDEE_SESSION_TOKEN>" -XPOST "http://<DOMAIN>/approve/<COLLECTION_ID>?overrideKey
=<OVERRIDE_KEY>" | jq .
  • ZEBEDEE_SESSION_TOKEN - A valid Zebedee session token for your user.
  • <DOMAIN> - the address of the Zebedee publishing instance.
  • <COLLECTION_ID> - the ID of the collection to be approved.
  • <OVERRIDE_KEY> - the secret key required to override the check.

If successful you should get something similar too:

  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current
                                 Dload  Upload   Total   Spent    Left  Speed
100     4  100     4    0     0    285      0 --:--:-- --:--:-- --:--:--   285
true

If this is fails try again after regenerating an override key as it may have expired before your request was sent.


Service authentication with Zebedee

  1. Login to florence using: curl -X POST -d '{"email":"[email protected]","password":"<your password>"}' http://localhost:8082/login
  2. Make a note of the access_token that gets returned in the headers
  3. Create an admin service key: curl -X POST http://localhost:8082/service -H "X-Florence-Token: <access_token>" -d '{"id":"admin"}'
  4. Make a note of the service token that gets returned in the response body
  5. Set the environment variable: export SERVICE_AUTH_TOKEN=<YOUR_SERVICE_TOKEN> replacing the token with that one you got in step 4
  6. Restart zebedee and authenticating services

SERVICE_AUTH_TOKEN creation for Sandbox/Prod

Please see document in dp-operations:

dp-operations/guide Generate Service Auth Token

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