How we chose Thingsboard.io for AirLink Server

Decision Context

PAYG devices fall under the IoT 'edge device' umbrella. A small set of SaaS companies are currently offering integrated loan management and device management services to PAYG-IoT distributors, primarily focused on token-based GSM home-system devices with some extensions for data feedback. Companies like Angaza have proprietary hardware+software IoT stacks that offer API-integration at some levels while companies like Solaris offer more open source codebases for device firmware and token software. Neither offer an open-source provisioning or analytics platform, although both have SaaS offerings for analytics and PAYG control, integrated with their custom loan platform. Both have a per-end-user-per-month revenue model which is consistent with contemporary SaaS - their revenues scale directly with their customer's customer bases.

Simusolar would like to build or buy a PAYG + IoT Data system that has API integration, configurable analytics, cost-effective implementation, ability to serve partners as well as ability to aggregate data over BLE / GSM / Keypad / Wired systems. EnAccess has provided a $50,000 grant to Simusolar to build an open-source multi-medium IoT communication protocol and data format to support these goals in 2021, with a focus on a deliverable that can enable upstart companies in this area to easily overcome the PAYG-IoT technology barrier. Simusolar currently has pumps and fishing lights that will be modified to meet this standard.

We need to decide on the best alternative approach to building this IoT database and related tools. Simusolar has recently adopted several managed and no-code tools to enable speed of secure and scalable business process automation with low overhead costs. We believe this approach has long term value and hence we give priority to options which have managed or no-code cores. We consider two high-level options a. custom database with open source dashboarding tools (no-code device/partner management can follow alternate no-code/code analysis) b. open source IoT platforms

a. Custom db + Dashboard Options

(IaaS, e.g. managed Redis on DigitalOcean + custom droplet with code)

Pros of a custom db+dashboard approach

Freedom to adopt managed or self-managed databases without lock-in

Completely custom server code i.e. process triggers and PAYG responses

The communication layer ends at the database, cleanly separating the application layer which can be full-custom

A central database managed by one entity e.g. EnAccess would only require to handle communication layer while application layer would be handed off, making the central db more easily viable compared to a solution with an application layer

Cons of a custom db+dashboard approach

Requires coding competence to pre-process incoming IoT data stream

Requires domain-expert skill for building of device provisioning and basic analytics flows

Requires a full-time administrator to manage IoT connection to rest of business apps platform

New workflow features require coding and hence take weeks to develop

Initial adoption by business takes longer due to coding requirements

b. IoT Platform Options

(PaaS if managed or IaaS+PaaS in case of self-managed, includes closed-source options for reference)

Guide to IOT Dashboards and Platforms
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ThingsBoard - Open-source IoT Platform
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OpenRemote | The 100% Open Source IoT Platform
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Google Cloud IoT - Fully Managed IoT Services
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dweet™ - Bug Labs Enteprise IoT Platform
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Pros of an open-source IoT Platform approach

Leverages a pre-built best-practices approach to managing incoming IoT data-stream

Leverages a device provisioning and basic analytics platform that is ready to go, reducing the startup-building burden

New workflows can be built quickly as many of these platforms offer drag and drop UIs for process triggers based on incoming IoT connections

Companies can choose a managed or SaaS model for the same service if their business model supports that choice better than a self-managed PaaS

Cons of an open-source IoT Platform approach

Adopters would be initially oblivious to implementation details before they can study the large amount of platform source code in the specific programming language

The Application layer comes with presumptions about IoT management that may not apply across all businesses

Any central entity such as EnAccess who manages a common db might need to provide application-level client-management/API as well as database management and communication layer level API

Perspectives on Approach

Simusolar has experienced the often hidden time-cost and domain-knowledge complexity of building device-provisioning/onboarding flows for IoT systems, and considers provisioning an important complement to the IoT data/PAYG flow when considering approaches facilitating new ventures in this field. Standardizing this while considering privacy best-practices could reduce a big barrier, further abstracting away the technical details for integrating PAYG IoT with other business applications.

Data Retention management and Analytics is another natural feature desired of GSM IoT collections. We conjecture that most IoT analysis usually pivots on a single plotted variable for a particular device class e.g. power used by time of day for energy products, along with some standard status variables e.g. location, error state. PAYG control also has common requirements e.g. on/off control or use-metered control.

Hence there are opportunities to design a platform that has pre-built, privacy-enabled standard features for device provisioning, single-variable control and single-variable graphing with map and status indicators and a built in retention policy. Such a platform could enable adopters of the project to incorporate standard IoT outcomes easily into their business operations.

Lock-in risks as well as the central role of EnAccess in enabling upstarts points to the importance of open source, modular approaches that allow the scaling of individual components as managed or self-managed entities, such as front end databases and servers that run data processing code.

Culling the options

AWS/Azure/IBM IoT offerings were not considered the right cost-value tradeoff due to the complexity of adoption and the fact that the dataset of most adopters of this project will be limited in size and will manage with smaller IT teams i.e. not tens of millions of devices/interactions per day managed by a specialist IT team, but hundreds of thousands at most managed by a multi-tasking IT team. The caveat is potentially losing out on AI integration which could be useful for predictive tasks. In the PAYG-IoT business case, learning and prediction requirements are as yet not well defined as business differentiators and hence AI was not considered a prime factor.

The alternatives list was further limited by the following parameter choices: Open source, Free/freemium versions and no per-device fees. Per-devices services are roughly $2/month/device (in addition to any network/SIM card fees), which adds up quickly when selling a large number of smart devices and can be margin-limiting in low-cost markets. This consideration discounted dweetpro.io, thingstream.io, particle.io and thingspeak.com

Baseline: SaaS + PaaS + IaaS + Support-vendor costs for Simusolar are $86,658/yr projected to reduce to $52,100/yr by December 2021 by using no-code platforms and internal support

Last Round Alternatives

Featurecustom developmentThingsBoard.io ✓Kaaproject.orgOpenRemote.io ❌Crate.io ❌
Total Cost of Ownership for paid premium option - 1 year, 10,000 devices$120/yr code server, $180/yr Redis managed, $180/yr postgresql managed = $480/yr$3600/yr for Docker+managed db or $6,000/yr for SaaS cloud, provides flexibility$3600/yr for self-managed or $24,000/yr for managed on-premise $3600/yr for self-managed, no cloud offeringdb-only $2616/month ❌
ModelIaaS: DigitalOcean droplet with custom stream-processing code, managed Redis db buffer for incoming data providing high-rel front end, then managed PostGreSQL db for IoT metrics. Custom device/partner management workflows on another platform e.g. Airtable-like no-code platformOpen Source or Managed PaaS: Monolithic/microservice interchangeable, IoT stream processing, device/partner management and and IoT Analytics platform in Docker on a DigitalOcean droplet with Aiven-Cassandra + PostGreSQL managed dbs on DigitalOcean. One downloadable package architecture, can be clustered Open Source or Managed PaaS: microservices type IoT stream processing, device/partner management and and IoT Analytics platform in Docker connecting to a Redis + PostGreSQL. No monolithic download so steeper initial learning curveAssissted deployment only, no managed cloud optionsOpen Source or Managed PaaS: CrateDB is a distributed SQL database built on top of a NoSQL foundation. Customers often use CrateDB to store and query machine data. This is because CrateDB makes it easy and economical to handle the velocity, volume, and diversity of machine and log data.
Open source —Yes, updated in 2021Yes, updated in 2021Yes, updated in 2021Yes, updated in 2021
Performance / scaleFull-customSingle-container / managed cluster / cloud SaaS optionalityKubernetes bakedHighly scalable
Lock-in riskNilCompany could decide to fork free/paid codebases. Timestream data could be migrated but tenant management structure would probably need to fork codebaseTimestream data could be migrated but tenant management structure would probably need to fork codebaseTimestream data could be migrated but tenant management structure would probably need to fork codebaseDeveloping for specific db type could lead to harder migration options
Basic Data External forwarding and Workflow triggers —Yes, Kafka stream and Rulechain configured from drag and drop UIYes Redis based queue'Rule-chain' for PAYG response seems very basic without custom scripts, only math/text functions ❌Needs external SQL queries but performance is fast enough to support datastream analysis
Vendor info / any risk to businessSLA is fully dependent on internal developersthingsboard pro used by Engie, no SLA for community edition, dependent on internal developersFDA and HIPAA as customersGermany focus with some cities adopting it also Schipol security—
Feature dev speed~1wk-1mo~1day-1wk (most common features are UI based)~1day-1wk (most common features are UI based)~1day-1wk (most common features are UI based)~1wk-1mo
Feature costInternal Development @$1000/monthInternal Development @$1000/monthInternal Development @$1000/monthInternal Development @$1000/monthInternal Development @$1000/month
IoT Comms CustomizablePOST/MQTT/CoAP upload, GET request or Gateway subscribing via MQTTPOST/MQTT/CoAP upload, GET request or Gateway subscribing via MQTT—
APIWill need to be builtREST with JWT auth per device/entityREST API—
Analytics for metricsNoYesYesNot inbuilt ❌
Device managementWill need to be builtYes with profiles and gateway MQTT-only devicesYes with profiles, versions and gateway MQTT-only devicesNo ❌
Data management possiblityManaged Redis + Managed PostgreSQLPart of docker image as starting point, Managed Cassandra (Aiven on DigitalOcean) + PostgreSQL (native DigitalOcean) databaseManaged Redis + Managed PostgreSQL
Customer managementWill need to be builtYes with groups and embeddable client dashboardsYes with groupsNo ❌
Customer supportInternalOnly for cloud otherwise internalOnly for cloud otherwise internal
Interoperable format compatibilityYesJSON key-value pairs, additional Customizable 'connectors' for custom binaryJSON
Chart optionsWill need external service e.g. No code big-data serviceMoving line/bar/speed-gauge/mapMoving line/bar/speed-gauge/mapNo ❌
Filters on displayed charts—Only time filters?Only time filters?No ❌
Dashboard UX—Basic, sufficientBasic, sufficient—
Login based filteringCustom developmentYesYes
SSO types for users/customersCustom developmentOauth2Oauth2
Programming languagePHPJavaGoGoJava
Device/Sandbox codebase—not seen anyArduino samples, web sandbox, etcPython client example
Git / source Link—https://thingsboard.io/docs/user-guide/install/digital-ocean/ also https://github.com/thingsboard/thingsboardhttps://github.com/kaaproject/kaahttps://github.com/openremotehttps://github.com/crate

Proposed Solution: thingsboard.io docker monolithic

Scale Architecture

Deployment proposal: Lock-in mitigation is by using a managed database for Cassandra/PostgreSQL

Multi-vendor management from a single central db

Private devices and dashboards via tenancy

PAYG control


Plotting the primary variable by device type

Feasible Implementation Plan

Stakeholder validation (R.A.C.I.)

Were the responsible (implementers) persons consulted for feasibility?

Are the accountable (project manager) persons committed to the outcome?

Have the consulted (change recipients) people indicated their support?

Will the Informed (all other impacted) people receive the information in time?

Final Choice:


Decider (Proof):