Published Release 4.3.0 (Quest) of Onesait Platform

Owned by Onesait Platform
Last updated: 16/01/23
13 min read

On Friday, January 13, 2013, Release 4.3.0 of Onesait Platform  (mnemonicQuest) was published, following our versioning policy: Version Policy Onesait Platform.

You can follow our Roadmap and find more information about the capabilities of the Platform in the new Developer Portal.

ENGINE

Optimize the development of business solutions independent of the technology layer with Lowcode strategy.

We apply agile and Lowcode strategies for the development and integration of business solutions, based on standards, independent of specific cloud vendors, and deployable on IaaS, SaaS or On Premise infrastructures:

  • Scalability and stability of any infrastructure

  • Data at the center

  • Integrated end-to-end security

More info on Engine Guides

Google Cloud Storage support in File Repository

The File Repository is a platform component that allows uploading and sharing files from the platform, both from the Control Panel and from a REST API.

Until now, this component was able to work with GridFS when we had MongoDB in the installation or with MinIO for installations in which we used this distributed file system.

In this version Google Cloud Storage has been supported as another repository on which to store the files managed by the File Repository, this scenario is very interesting for platform projects that are deployed in GCP and that can use these native services.

In addition, the management UIs have been unified, so that from the same section it will be possible to select the storage mechanism (typically each project will use only one):

More info at this post.

Queries Profiler UI: Dashboard for Query Profiling

In release 4.2 a metrics system for queries was created to have more information about the queries that are executed in the system (these metrics are stored in the QueryMetrics Entity).

In this version a new UI has been created (built as a dashboard) that allows a complete profiling of the queries that execute within the platform, including the slowest queries, those that give error,....

The UI is accessible in the Tools>Queries Profiler UI

 

 

 

 

 

 

 

 

 

 

 

 

 

More info at this post.

Config Manager

The first version of this Architecture accelerator has been generated, which includes:

  • The multi-language module to manage the languages and literals per language of each application.

  • The master data manager of an application

Using Java 17 (LTS) as the Platform's default JVM

Until now, the Platform images used Java 8 by default, although it was also certified for Java 12 and Java 15.

In this version, OpenJDK 17 has been adopted as the default JVM. This version has been used because it is the latest LTS version of Oracle Java SE and therefore guarantees support.

git editor for functions in Serverless Manager

A visual component has been created (on Vue) that allows editing files in git.

This component has been enabled in the serverless platform module to facilitate the creation of functions, thanks to this improvement, it will be possible to upload, edit and select the files necessary for the execution of a function during the creation or editing of the same.

You can see how to use this tools here.

Attribute encryption/decryption support on Hashicorp Vault

Vault de Hashicorp is a popular tool used to securely manage sensitive information. Hashicorp Vault comes with several plugeable components called secrets engines and authentication methods that allow it to integrate with external systems. The purpose of these components is to manage and protect your secrets in dynamic infrastructures (e.g. database credentials, passwords or API keys). 

In Platform there is a functionality that allows encrypting and decrypting attributes of an Entity automatically from a master key stored in Platform. With this integration the Vault manages this master key.

More information on integration at this post.

GIS Library

We have developed a GIS library focused on the representation of geospatial data. For its design, we have based our work on the compilation of the needs of the different products and projects where there are map viewers.

This first version uses OpenLayers in its version 6.14.1. The library is designed in such a way that it allows the update of OpenLayers versions, as well as to contemplate in the future the use of other different libraries (CesiumJS, Leaflet, etc.).

More info.

Architecture Framework Update

In this quarter the Architecture framework has been updated with information such as this:

GeoServer as GIS server

In addition to generating a GIS library for products and projects, in this version we have worked on the implementation of a GIS server, according to the Onesait framework for GIS, the chosen server has been GeoServer.

Specifically, we have installed GeoServer version 2.22.0 on a PostgreSQL version 13 and the PostGIS extension with version 3.1.

The server is running and serving layers in different OGC formats: WMS, TMS, WMS-C, WMTS, WFS, WCS and WPS.

More info here.

INTELLIGENCE

Maximize the value of your information with our methodology and algorithm.

We virtualize and simplify data access between organizations, departments and systems, achieving a 360º view of business entities and facilitating their exploitation through real-time rules, execution of complex algorithms or traditional analysis:

  • Single multi-repository data model

  • Collaborative environment for Data Scientist

  • Access, management and consumption of APIs

More information at Intelligence Guides

Presto integration as a multi-repository query engine

In Platform release 3.1.0 we integrated Presto+MinIO as DataLake storage support for migration scenarios from Hadoop.

In this release we have supported Presto as a multi-repository SQL query engine, which will allow us to make analytical queries on all Platform Entities/Ontologies regardless of the repository where they are stored (this for example will allow us to make JOINs between a Postgresql and a MongoDB, or between a MinIO and an Oracle).

For this we have created a new type of Entity: Presto Entity:

which allows users to connect to the different catalogs registered in Presto by the platform administrator creating PRESTO entities.

Once the PRESTO entities have been created, we can make JOINS between them transparently to the repository:

More information here.

DataClass Concept (Data Governance)

The DataClass functionality associated with Data Governance, allows to associate both Entities (at a general level) and attributes of these, these rules allow to define validation rules and data formatting, thus allowing to execute a preprocessing before inserting the data.

This preprocessing will allow the definition of error messages to be inserted in the user's audit entity, thus facilitating the display of failed data and load statistics on a dashboard. Rules can be created in Groovy and Javascript.

Rules may be associated with an attribute of an ontology, in which case they will be cast for that attribute:

Or at the Entity level, in which case all attributes of the Entity may be used in the rule.

More info here.

REST communication support in Dashboard Engine

The Dashboard Engine allows dashboards to be created from gadgets built on datasources, which are translated into queries on the platform Entities. At the execution level, the browser establishes a communication with the Dashboard Engine to pass parameters and retrieve information.

In previous versions the communication could be WebSockets or XHR in Fallback mode. For the type of application, WebSockets communication is ideal because it establishes a secure channel between the client and the server. However, in some scenarios this communication poses problems in the face of peripheral security elements such as WAFs.

For this reason, a new REST communication channel has been implemented in the Dashboard Engine.

Once this working mode of the Dashboard Engine is activated, the operation is transparent to the developer and end user of the dashboards.

Destination Component in DataFlow CRUD Platform

A new component has been developed for DataFlow that allows us to perform a CRUD on one or more target entities.

With this component, I can easily load data to the platform from other sources.

For more details there is a post dedicated to the component.

CENTER

Support tool for system modernization and migration to the Cloud.

Onesait Platform Center (Center) is a tool that provides support in these areas:

  • Guide the phases of a project (startup, development, operation, change management) through a LowCode (*) approach by providing high-level visual tools to all phases.

  • Support the process of application modernization and migration to the Cloud.

  • Standardize the creation of solutions including their architecture and deployment

  • Simplify system operation

More information on Center Guides

Support for Spring Boot applications and Onesait Architecture applications

In the new release of the Center, the Spring Boot category has been added to the Assessment. This allows this type of applications, which are more modern and in line with the trend of decomposing the application into microservices, to be added to a project from the initial inventory phase.

Existing applications can be added, in which case I will indicate some information and the path to the source code of the project in Git.

Or for a new application, in which case the Center will create the archetype of the new Spring Boot project as a Maven project ready for development. In this case to create the project archetype we can use the Onesait Architecture Initializer or Spring.io Initializr.

More information on the use of this capability is available at this post.

ODS CLI Support

Onesait Design System (ODS) offers developers a CLI (command line) tool for creating Front application archetypes based on this technology.

In this release, integration with this tool has been included in the Onesait Platform Center so that these Front application archetypes can be generated in the Asssessment phase and included in the cloud containerization and deployment cycle managed by the Onesait Platform Center.

Infrastructure Diagram

Through this new diagram, from the Center we can easily model the infrastructure of a solution, so that the Center is in charge of orchestrating calls to Terraform and Ansible to deploy the required infrastructure:

At this url you can find a vídeo with an example of a VM and network deployment over GCP.

Integrated Git File Editor

The Center projects have an associated Git repository where all the code related to the project is stored and versioned. To facilitate the editing of the project files, a Git editor has been integrated into the project itself, accessible from the project tabs:

Once we are in the section, we can select a branch of our repository:

And automatically loads the editor directory tree where we can choose any file to edit:

More info here.

THINGS

Ansible-based deployment

The deployment of services in the field is a main pillar in node management. Therefore, new remote orchestration systems have been included, improving and extending the capabilities of Onesait Edge. Until now, remote deployment was based on the use of docker-compose as orchestrator of Edge services, in this release Onesait Edge incorporates deployment methods by updating the IoT agent (iota), allowing installation using Ansible.

Red Hat Operating Systems Certification

Worked with the Red Hat team to certify the deployment of Onesait Edge on their operating systems, both Cloud and Edge.

Deployment on Openshift:

The deployment of Onesait Edge on Openshift has been validated, making some changes with the Helm used in Kubernetes, adapting them to the peculiarities of Openshift, some of the images used have been modified for the use of systems certified by Red Hat (OpenJDK, Node.js, etc).

RHEL for Edge Support

Red Hat has a lightweight operating system for remote field deployment.

Onesait Edge has carried out the complete integration and validation with Rhel for Edge: installation of base image with IoT agent (iota), orchestration through Podman, hardware and software validation (specific programs, modems from different manufacturers).

Field accelerators

 The ability to perform complex operations in the field and implement artificial intelligence is an essential requirement for Onesait Edge, which is why the system has been integrated with Nvidia Jetson accelerators. Each Nvidia Jetson is a complete system on module (SOM) that includes GPU, CPU, memory, power management, high-speed interfaces, sensors, etc.

These Jetson machines are compatible with the most popular AI frameworks on the market: TensorFlow, PyTorch, Caffe, Keras, MXNet and with SDKs for new developments. This integration with Jetson systems allows Onesait Edge not only to execute more complex AI in the field, but also to evolve it.

The equipment used was the Jetson Nano, whose main capabilities are:

  • NVIDIA CUDA® architecture: Maxwell™ GPU 128 cores

  • Quad-core ARM® Cortex® Cortex®-A57 MPCore CPU

  • AI: High performance AI computing with GPU processing

  • Ideal for smart city applications with perimeter AI

  • GbE 15W PoE support for cameras

EXPERIENCE

Conversion of ODS components to Web Components

The approach, design, adaptation and development of ODS components to Web Components has been carried out, including a storybook with the available Web Components and a migration policy for existing systems..

As the first project built on these Web Components, a Chatbot has been created:

Evolutionary and ODS maintenance

  • ODS XR, creation of a reusable onboarding scenario for virtual reality projects and adaptation of ODS and creation of interaction resources for VR projector.

  • Component evolution and support (Accessibility improvements, style evolution, component design corrections such as Steps, tabs, popover, dropdown, Action menu...)

  • Libraries and methodology, adaptation of libraries and documentation of new processes, covers and file organization in Figma.

  • Support and documentation, evolution of component documentation in more detail.

  • Approach design tokens for interactions and animations.

DEMOS

System ingest, correlation and actuation demonstrator

This demonstrator is responsible for the detection, notification and troubleshooting of multiple remote systems mounted in a topological network with the information provided by the raw logs of these systems.

For this purpose, modules such as DataFlow for log ingestion, Kafka are used,

the FlowEngine for launching correction processes on remote systems

Graph entities for modeling service topology:

and dashboards for information exploitation:

The full details of the demonstrator can be found here.

IBM Maximo Integration Demonstrator

This demonstrator allows for the exploitation of data stored in IBM Maximo from the Platform. In the demonstrator it was chosen to connect with the Maximo database, for that the DataFlow module was used to connect with the Maximo tables, extract the information and store it in the platform entities,

and then exploit it in dashboards.

You can find the complete scope of the demonstrator here.

Cloud Migration with the Center Demonstrator

In this demo we start from a legacy application deployed in a traditional way and move on to containerize it, deploying it in a Kubernetes cluster through Charts Helm.

and finally deploy it on OpenShift on Google Cloud Platform.

More information about the demonstrator here.

COMMUNITY

Community Releases

Community Channels

These are the ones we use to keep in touch with you. With each passing quarter we continue to grow in both content and followers (thank you all very much!). Throughout this last quarter of the year:

  • We reached the 1.250 user at CloudLab of Onesait Platform, our free and experimental environment.

  • We have 175 subscribers in our channel of YouTube,totaling +830 total viewing hours and exceeding 100,000 impressions.

  • Our Community version of the Platform in GitHub exceeds +1200 clones, and with a total of 258 developers currently following the project.

  • Our Blog totaled +320,000 reads of our articles, increasing this quarter by +65,000 reads.

  • We surpassed +340,000 total impressions on Twitter, with almost 170,000 visits to our profile, +900 retweets and almost +1400 likes from our peeps.

If you want to be kept up to date with our special events, be sure to sign up at our Meetup community, where there are already +700 subscribers.