Loading...
Loading...
Loading...
Loading...
Loading...
Loading...
Loading...
Loading...
Loading...
Loading...
iFix Dashboard
Post infra setup (Kubernetes Cluster), We start with deploying the Jenkins and kaniko-cache-warmer.
Sub Domain to expose CI/CD URL
GitHub Oauth App
Docker hub account details (username and password)
SSL Certificate for the sub-domain
Prepare an <ci.yaml> master config file and <ci-secrets.yaml>, you can name this file as you wish which will have the following configurations.
credentials, secrets (You need to encrypt using sops and create a ci-secret.yaml separately)
Check and Update ci-secrets.yaml details (like github Oauth app clientId and clientSecret, GitHub user details gitReadSshPrivateKey and gitReadAccessToken etc..)
To create Jenkins namespace mark this flag true
Add your env's kubconfigs under kubConfigs like https://github.com/misdwss/iFix-DevOps/blob/mgramseva/deploy-as-code/helm/environments/ci-secrets.yaml#L19
KubeConfig env's name and deploymentJobs name from ci.yaml should be the same
Update the CIOps and DIGIT-DevOps repo name with your forked repo name and provide read-only access to github user to those repo's.
SSL Certificate for the sub-domain
You have launched the Jenkins. You can access the same through your sub-domain which you configured in ci.yaml.
The Jenkins CI pipeline is configured and managed 'as code'.
Example URL - https://<Jenkins_domain>
Since there are many services and the development code is part of various git repos, you need to understand the concept of cicd-as-service which is open-sourced. This page also guides you through the process of creating a CI/CD pipeline.
As a developer - To integrate any new service/app to the CI/CD below is the starting point:
Once the desired service is ready for the integration: decide the service name, type of service, whether DB migration is required or not. While you commit the source code of the service to the git repository, the following file should be added with the relevant details which are mentioned below:
Build-config.yml –It is present under the build directory in each repository
This file contains the below details which are used for creating the automated Jenkins pipeline job for your newly created service.
While integrating a new service/app, the above content needs to be added in the build-config.yml file of that app repository. For example: If we are onboarding a new service called egov-test, then the build-config.yml should be added as mentioned below.
If a job requires multiple images to be created (DB Migration) then it should be added as below,
Note - If a new repository is created then the build-config.yml should be created under the build folder and then the config values are added to it.
The git repository URL is then added to the Job Builder parameters
When the Jenkins Job => job builder is executed the CI Pipeline gets created automatically based on the above details in build-config.yml. Eg: egov-test job will be created under the core-services folder in Jenkins because the “build-config was edited under core-services” And it should be the “master” branch only. Once the pipeline job is created, it can be executed for any feature branch with build parameters (Specifying which branch to be built – master or any feature branch).
As a result of the pipeline execution, the respective app/service docker image will be built and pushed to the Docker repository.
Job Builder – Job Builder is a Generic Jenkins job that creates the Jenkins pipeline automatically which are then used to build the application, create the docker image of it and push the image to the docker repository. The Job Builder job requires the git repository URL as a parameter. It clones the respective git repository and reads the build/build-config.yml file for each git repository and uses it to create the service build job.
Check git repository URL is available in ci.yaml
If git repository URL is available build the Job-Builder Job
If the git repository URL is not available ask the Devops team to add it.
The services deployed and managed on a Kubernetes cluster in cloud platforms like AWS, Azure, GCP, OpenStack, etc. Here, we use helm charts to manage and generate the Kubernetes manifest files and use them for further deployment to the respective Kubernetes cluster. Each service is created as charts which will have the below-mentioned files in them.
To deploy a new service, we need to create the helm chart for it. The chart should be created under the charts/helm directory in iFix-DevOps repository.
We have an automatic helm chart generator utility that needs to be installed on the local machine, the utility prompts for user inputs about the newly developed service (app specifications) for creating the helm chart. The requested chart with the configuration values (created based on the inputs provided) will be created for the user.
Name of the service? test-service Application Type? NA Kubernetes health checks to be enabled? Yes Flyway DB migration container necessary? No, Expose service to the internet? Yes, Route through API gateway [zuul] No Context path? hello
The generated chart will have the following files.
This chart can also be modified further based on user requirements.
The Deployment of manifests to the Kubernetes cluster is made very simple and easy. We have Jenkins Jobs for each state and are environment-specific. We need to provide the image name or the service name in the respective Jenkins deployment job.
Enter a caption for this image (optional)
Enter a caption for this image (optional)
The deployment Jenkins job internally performs the following operations,
Reads the image name or the service name given and finds the chart that is specific to it.
Generates the Kubernetes manifests files from the chart using the helm template engine.
Execute the deployment manifest with the specified docker image(s) to the Kubernetes cluster.
Fiscal Event Aggregator is a java standalone application, which runs as Cron Job to aggregate the fiscal event data from the Druid data store to Postgres DB.
Current Version : 2.0.0
Before you proceed with the configuration, make sure the following pre-requisites are met
Java 8
Druid DB & Postgres DB should be up and running
Fiscal-Event-Aggregator computes the aggregate of data over a selected time period. Aggregator will apply the time range filter according to the following approach :
Fiscal periods will be picked up as per the current system time. The current year will be the current fiscal period starting from 1st of April of the current year to 31st March of (current year+1). And it will also aggregate the data of one previous fiscal year starting from 1st of April of (current year -1) to 31st March of the current year.
Follow the steps below to aggregate the final fiscal event data as per the fiscal time periods.
Group the sum of the amount based on department entity ancestry[6] id (attributes.departmentEntity.ancestry[6].id
) that is GP (Gram Panchayat), COA (chart of account) id, and event type.
Difference of the sum of amount of "DEMAND" and "RECEIPT" event type with respect to distinct department entity ancestry[6] id (attributes.departmentEntity.ancestry[6].id
) that is GP (Gram Panchayat).
Difference of the sum of amount of "BILL" and "PAYMENT" event type with respect to distinct department entity ancestry[6] id (attributes.departmentEntity.ancestry[6].id
) that is GP(Gram Panchayat).
Upsert the final aggregated fiscal event data into the Postgres DB.
Note: Below environment variables need to be configured with respect to the environment
Update the configurations in the dev.yaml, qa.yml, prod.yaml file.
Date/Time Filter
The date & time filter on the dashboard defaults to the current financial year since most of the calculations and visualizations makes sense when viewed from a fiscal year perspective rather than an individual week/month view. However, users can change to respective dates and most charts will be filtered to the selected time range.
Department Hierarchy Filter
Currently, there are 6 levels of hierarchy as per administration set up by the Department of Water supply and Sanitation Punjab. These are State, Zone, Circle, Division, Sub Division, Section, Gram Panchayat.
All these filters are independent and work on the dashboard irrespective of whether other filters in the hierarchy are selected or not.
Surplus/Deficit
This number shows whether the selected Administrative entity is financially surplus or not. It also compares with the previous year using the “trend” visualization in Metabase.
Pending Collections
For selected Administrative boundary what is the pending collections through water charges is represented in this card. If the pending amount is null. Then this card should display zero.
Outstanding Electricity Bills
Since electricity bills create a major component of the expenditure for all projects, it is important to show how much electricity bills are pending at each administrative entity. The total amount of pending bills filtered by electricity under COA gives us pending electricity bills
GPWSCs at Risk
Risky GPWSCs are divided into 3 types
High Risk: Demand is less than Bill. Medium Risk: Demand is more than bill but pending collections is less than pending bills.
Low Risk: Demand is more than bill and also pending collections is more than pending bills.
It is important to identify the risky GPWSCs and keep the officials of DWSS informed, for them to take the right actions before it’s too late.
Collections & Expenditure Time Series Graphs
These charts represent the Demand, Net Collections, Bills and Net Payments across time(month-on-month) so that officials get a fair idea of how the amount that is getting collected is being spent.
Any abnormalities in the graphs (Low collections or excessive spending) is something that needs to be paid attention to.
Expenditure by Chart of Accounts
Expenditure is currently divided into 4 broad categories - Electricity Bills, Salaries, Operations and Maintenance and Miscellaneous. How these 4 categories accumulate to total expenditure for the selected entity over time is presented on the chart. Usually, 75% of the expenditure should be of type electricity
Department Hierarchy Table
Here, we represent Total Demand, Receipt, Bills and Payments by all levels of the hierarchy so that officials at any point, instead of just viewing the charts, trends from the visualizations can also see the tables and compare best performing entities.
iFix Dashboard
Essentially, there are 2 stages that should allow you to use the full potential of DeploymentConfig and pipeline-as-code.
Stage 1: Clone the DevOps repo, choose your iFix product branch as iFix-adapter.
Prepare an <env.yaml> master config file, you can name this file as you wish which will have the following configurations, this env file need to be in line with your cluster name.
each service global, local env variables
credentials, secrets (You need to encrypt using sops and create a <env>-secret.yaml separately)
Number of replicas/scale of individual services (Depending on whether dev or prod)
mdms, config repos (Master Data, ULB, Tenant details, Users, etc)
sms g/w, email g/w, payment g/w
GMap key (In case you are using Google Map services in your PGR, PT, TL, etc)
S3 Bucket for Filestore
URL/DNS on which the DIGIT will be exposed
SSL Certificate for the above URL
End-points configs (Internal/external)
Stage 2: Run the iFix_Dashboard_setup deployment script and simply answer the questions that it asks.
iFIX Dashboard is built on Metabase and can be easily configured to develop various dashboards.
The below dashboard provides information about the fiscal position of various projects. The dashboard can be filtered for various date ranges and departmental hierarchies.
All content on this page by eGov Foundation is licensed under a Creative Commons Attribution 4.0 International License.
Tools used to create the OLAP system for the iFix
iFix dashboard is developed using the opensource tools that included the complete OLAP system that streams the data from various sources, transform and process data and visualize the data using dashboards
All content on this page by eGov Foundation is licensed under a Creative Commons Attribution 4.0 International License.
Fiscal Event services flatten each fiscal event line item and post them into Druid via the Kafka Druid connector. The raw events are stored in the fiscal-events dataset in Druid. Metabase is used for visualisations.
The flattened fiscal event consists of the following attributes
Reference Dashboard
This section contains details and information about the iFIX Reference Dashboard. Click on the links below to learn more.
All content on this page by eGov Foundation is licensed under a Creative Commons Attribution 4.0 International License.
Post infra setup (Kubernetes Cluster), the deployment has got 2 stages and 2 modes. We can see the stages first and then the modes.
Essentially, iFix dashboard deployment means that we need to generate Kubernetes manifests for each individual service of the required OLAP components like a druid, metabase. We use the tool called helm, which is an easy, effective and customizable packaging and deployment solution. So depending on where and which env you initiate the deployment there are 2 modes that you can deploy.
From Local machine - whatever we are trying in this sample exercise so far.
Advanced: Setup CI/CD System like Jenkins - Depending on how you want to set up your CI/CD and the expertise the steps will vary, however here you can find how we eGov has set up an exemplar CI/CD on Jenkins and the pipelines are created automatically without any manual intervention.
You can choose the infra type and the env to either single fat server or distributed setup on Docker compose or Kubernetes.
All content on this page by eGov Foundation is licensed under a Creative Commons Attribution 4.0 International License.
All content on this page by eGov Foundation is licensed under a Creative Commons Attribution 4.0 International License.
All content on this page by eGov Foundation is licensed under a Creative Commons Attribution 4.0 International License.
All content on this page by eGov Foundation is licensed under a Creative Commons Attribution 4.0 International License.
All content on this page by eGov Foundation is licensed under a Creative Commons Attribution 4.0 International License.
All content on this page by eGov Foundation is licensed under a Creative Commons Attribution 4.0 International License.
Attribute
Description
version
string example: 1.0.0
Version of the Data Model Definition
id
string example: 51c9c03c-1607-4dd5-9e0e-93bbf860f6f7
System generated UUID of Line Item
eventId
string example: fecbbf1d-d6e3-4f24-9935-02c33b9248e0
Fiscal Event Reference Id
tenantId
string nullable: false example: pb
Tenant Id
government.id
string example: pb
government.name
string example: Punjab
department.id
string example: 5d664a9f-9367-458a-aa5f-07fb18b90adc
Unique system generated UUID
department.code
string example: DWSS
Unique department code
department.name
string example: Department of Water Supply & Sanitation
Name of the department
expenditure.id
string example: d334d99a-b5c1-426c-942b-f11b5b5454fe
Unique system generated UUID
expenditure.code
string example: JJM
Unique Expenditure code
expenditure.name
string example: Jal Jeevan Mission
Name of the Expenditure
expenditure.type
string
Type of the Expenditure Enum: Array [ 2 ]
project.id
string example: 6ab1b1d2-e224-46fa-b53b-ac83b3c7ce95
Unique system generated UUID
project.code
string example: PWT
Unique Project code
project.name
string example: Peepli Water Tank
Name of the Project
eventType
string nullable: false example: Appropriation
Captures the event type e.g Demand, Receipt, Bill, Payment
eventTime
integer($int64) example: 1628177497000
when the event occurred at source system level
referenceId
string example: 013e9c56-8207-4dac-9f4d-f1e20bd824e7
reference unique id(transaction id) of the caller system
parentEventId
string nullable: true example: 7d476bb0-bc9f-48e2-8ad4-5a4a36220779
If this is a follow up event then it will refer to the parent event using this reference id.
parentReferenceId
string nullable: true example: 77f23efe-879d-407b-8f23-7b8dd5b2ecb1
If this is a follow up event then it will refer to the parent event in source system using this reference id.
amount
number example: 10234.5
Transaction Amount
coa.id
string example: e9f940d4-69aa-4bbb-aa82-111b8948a6b6
Unique system generated UUID
coa.coaCode
string example: 1234-123-123-12-12-12
Chart of account concatenated string
coa.majorHead
string example: 1234
Major head code
coa.majorHeadName
string
Major head name
coa.majorHeadType
string example: Revenue
Major head code type
coa.subMajorHead
string example: 123
Sub-Major head code
coa.subMajorHeadName
string
Sub-Major head name
coa.minorHead
string example: 123
Minor head code
coa.minorHeadName
string
Minor head name
coa.subHead
string example: 12
Sub-Head code
coa.subHeadName
string
Sub-Head name
coa.groupHead
string example: 12
Group head code
coa.groupHeadName
string
Group head name
coa.objectHead
string example: 12
Object head code
coa.objectHeadName
string
Object head name
fromBillingPeriod
integer($int64) example: 1622907239000
Start date of the billing period for which transaction is applicable
toBillingPeriod
integer($int64) example: 1628177643000
Start date of the billing period for which transaction is applicable
Key
Value
Description
DRUID_CONNECT_PROTOCOL
HTTP
This is a hardcoded value And won’t change w.r.t environment. And It depends upon the druid broker’s protocol that is getting used to connect.
DRUID_CONNECT_PORT
8082
This is a hardcoded value And won’t change w.r.t environment. It depends upon the druid broker protocol that we are using and the corresponding port of that druid broker.
DRUID_HOST
druid-broker.olap
this is kept under configmaps
.
FISCAL_EVENT_DATASOURCE
fiscal-event
This is the data Source present in Druid DB. It is the same as defined in Druid DB.
Platform Tools
Latest Version
Used Version
Description
License Type
v0.40.4
v0.40.2
Metabase is an open-source business intelligence tool. It lets you ask questions about your data, and displays answers in formats that make sense, whether that's a bar graph or a detailed table.
0.21.1
0.21.1
Apache Druid is a real-time analytics database designed for fast slice-and-dice analytics ("OLAP" queries) on large data sets. Druid is most often used as a database for powering use cases where real-time ingest, fast query performance, and high uptime is important. As such, Druid is commonly used for powering GUIs of analytical applications, or as a backend for highly concurrent APIs that need fast aggregations. Druid works best with event-oriented data.
6.2.0
5.4.1
Apache Kafka is an open-sourced and community distributed event streaming platform capable of handling trillions of events a day.
13.4
9.6 and 10.6
PostgreSQL is a powerful, open-source object-relational database system with over 30 years of active development that has earned it a strong reputation for reliability, feature robustness, and performance