Published Release 3.1.0 (KickOff) of Onesait Platform

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Last updated: 18/10/21
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Info general

On July 30, 2021, Release 3.1.0 of the Onesait Platform (KickOff mnemonic) was released, following our release policy: Version Policy onesait Cloud Platform.

You can follow our roadmapen Roadmap Onesait Platform

Below you can see the main features of this release.

Engine

This platform distribution supports the development of microservices and all types of applications. To assist in this type of development, the platform allows visual development with a LowCode approach incorporating a centralized web console that supports administration, configuration, development and deployment.

In this version we have incorporated important features:

  • Renaming of the Ontology concept to Entity: in Platform we used the name Ontology to refer to the Entities managed by Platform, the name came from the origins of the Platform in the European R&D area. As you have told us on several occasions, the term was sometimes confusing, we have listened to you and from this version in the Control Panel you will see that we refer to the Platform Entities:

 

  • New Control Panel Home UI: this functionality gives administrator users information about the overall status of the platform. Using the metrics provided by Prometheus, the new UI allows the user to have a unified view of the status and performance of each of the components that are deployed in their installation. More info

  • Web Project Creation Until this version, the creation of web projects in controlpanel only allowed uploading a file where the user attached all the files needed for the operation of his web project. With this improvement, the user can decide if he wants to use the Web Template provided by the platform as the basis of his web project. (Onesait Platform Web Template) which gives us integrated and configurable via JSON login, security, menus, header,...

 

  • Entities without ContextData A new configuration has been added when creating an Ontology that allows to enable/disable the option of adding the ContextData object to the information inserted in the Platform. More info.

Intelligence

This distribution of the platform supports the development of systems that use the capabilities of Platform Intelligence, either with its AI capabilities, ingest from different sources, analytics, visualization,....

And in this quarter we have worked on this:

  • Big Data Storage on Presto+MinIO:  Presto is an open-source distributed SQL query engine that allows you to launch interactive analytical queries against a large number of data sources, and MinIO is a distributed storage that implements the AWS S3 API. These two technologies together allow us to replace Hadoop (HDFS) and Datawarehouse (HIVE) storage services.. El uso de estas 2 tecnologías nos permite tener una solución más elástica, dinámica y fácilmente gestionable que con Hadoop (leer más). La guía de uso indica cómo usar esta nueva característica: MinIO+Presto as Historical Database for Entities

 

  • Models Manager with MLFlow: In order to offer new tools to data scientists that make their work more productive, we have integrated MLFlow to help with ML models development.

    The user with Rol Analytics will be able to access this new tool from the new My ML Lifecycle management option:

MLflow is an open-source platform for managing the Machine Learning development lifecycle including tracking of experiments to record and compare parameters and results.(MLflow Tracking), packaged the ML code in a reusable and reproducible form for sharing with other data scientists and deploying it in production (MLflow Projects), model management and deployment (MLflow Models) and central model repository to collaboratively manage the entire lifecycle of an MLflow model, including model versioning, stage transitions, and annotations (MLflow Model Registry).

We can use MLFlow both from Notebooks that have already established a Platform as a Tracking Server.

as well as from our own code in different languages by simply setting the URL of our Tracking Server as a variable:

More information in this new section: https://onesaitplatform.atlassian.net/wiki/pages/createpage.action?spaceKey=DOCT&title=Models%20Manager%20Guides

  • TimescaleDB support as a TimeSeries DB on Entities: TimescaleDB is an open-source database for Time Series storage and analysis with the power and advantages of using SQL, TimescaleDB is built on top of PostgreSQL which has the advantage of being able to use the tools of the Postgresql ecosystem. TimescaleDB includes specific data management capabilities, such as data retention, downsamplings, native compression, data lifecycle management, aggregation policies as well as Time Series analytics oriented functions, such as window creation, gap filling, LOCF queries,... And being built on PostgreSQL it can store your business data in the same database allowing you to perform JOINS.

    When creating the TimeSeries Entity type you can select TimescaleDB

And from there configure the way Timescale is used, from the Chunk time interval that defines the time window that is taken into account to create the chunks.

Window frequency indicating whether we want the timeseries to have discrete intervals when storing measurements or not:

Aggregation functions: In the case of selecting a frequency, it will be possible to select between different aggregation functions (LAST, SUM) to know how to aggregate the data of each signal if more than one record is received for a set of TAGs and a particular frequency/timestap.

Things

This platform distribution supports the development of IoT systems, both in the Cloud and Edge environments.

In this quarter we have made progress in:

  • Landscape active monitoring and telemetry: the ability to report through the Control Channel (Device2Cloud Flow), information regarding the use of resources (RAM, CPU and disk) of the corresponding Edge Device by each of the loads deployed on the device, has been added to the IoT/Edge Agent. This telemetry is configurable via CLI in the Edge Device itself and the 'iotagent' command.

 

  • IoT/Edge HUB native Kafka Connector: Within the connectors section, the creation and deployment of a bi-directional (Producer and Consumer), multi-topical Kafka<->MQTT connector is now available, allowing to easily connect the Business Channel of all types of devices included in the Lanscape. A properties management system allows dynamic configuration of all the usual Kafka parameters for its version >=2.7.  (https://kafka.apache.org/27/documentation.html ).

 

  • Edge Agent (based on Go 1.15.8) in Edge Device Orchestration with advanced interface to Podman: IoT/Edge Agent has been updated to be able to interact with Podman deployments >=3.0 on RHEL 8 or related distributions. Isolated execution of containers or using docker-compose emulation available in Podman is possible.

  • IoT/Edge HUB deployment on VM/Baremetal using microk8s: IoT/Edge HUB deployment on microk8s using VMs or Baremetal has been certified and released. The Helm deployment parameterized for a deployment using microk8s Helm v.3 Addon is now available.

  • IoT/Edge HUB deployment for VM/Baremetal using Rancher 2.5: IoT/Edge HUB deployment on Rancher 2.5 using VMs or Baremetal has been certified and released. Parameterized Helm deployment is now available for two different ingress Traefik (default in Rancher) and Apache Kong.

  • Edge Agent (based on Go 1.15.8) in Edge Cluster Orchestration with interfaces for microk8s: It is now possible to orchestrate workloads on microk8s in remote clusters with the deployment of the new version of IoT/Edge Agent. Design your deployments with Helm v.3, include them in the IoT/Edge HUB deployment structure and the agent will take care of distributing and lifting the load securely, giving kubectl access to the remote cluster.

DevOps

Within this line of work we include all the tools, utilities and platform capabilities that help in the Development and Operation.

  • Helm Charts to deploy Platform resources in high availability: in this version Helm Charts have been created to deploy different Platform components in high availability, both in Kubernetes and Openshift. We can highlight the Chart to deploy a MongoDB Replica-Set in Kubernetes.

More info here: DevOps - High Availability Platform Resource Deployment Charts

 

Onesait Platform Community

This line of work includes the tasks we carry out in relation to the Platform Community, of which the Open Source version of Onesait Platform forms part, as well as the Platform's different communication channels.

Throughout this first quarter of 2021, we have worked on:

Sf you want to keep up to date with our webcasts, be sure to sign up to our Meetup community, where there are already +700 subscribers.

  • Community Channels: these are the channels we use to keep in touch with you, and we continue to grow in both content and followers (thank you all very much!). Throughout this second quarter of the year, we have:

    • Reached 1,073 users in Onesait Platform CloudLab, our free and experimental environment.

    • Grew by +16 new subscribers in our channel on YouTube, surpassing 145 total subscribers, totaling +70 hours of viewing and achieving +8,000 impressions during this quarter.

    • Surpassed 80 clones on GitHub of our Community version of the Platform, gaining +4 new developers, reaching a total of 248 developers following the project.

    • We continue to prepare content for DZone, and so far our articles have a total of +50,000 reads.

    • We have published a total of 24 entries in our Blog, reaching +30,000 quarterly readings.

    • Reached 287 followers in Twitter, exceeding 30,000 impressions.