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Plug and Play Telemetry with fledge.io Cloud

Modern applications produce and consume significant amounts of data. The data and state is shared in the form of messages, events and files. Distributed applications rely on data from different microservices to make key decisions in real-time. The data and state also become important for application portability. So a robust and secure data infrastructure is critical for distributed applications.

We have now added key data infrastructure enhancements to fledge.io Cloud. These enhancements are intended to help with the following

  1. Enable geo-distributed applications to easily and securely share the data among microservices
  2. Offer tools visualize the data for analysis purposes
  3. Enable stateful migration of microservices across locations and providers

This is the first feature enhancement announcement in the context of data infrastructure.

Plug and Play Telemetry

fledge.io has supported telemetry based data collection and streaming from the beginning. So what is new here?

fledge.io has had a rich, application specific data collection capabilities based on eBPF along with data streaming capabilities that is built-in. Now, this capability has been expanded to enable applications to collect, stream and share telemetry data (health, performance, sensor etc.) across cloud and edge environments.

What are the challenges with telemetry?

The challenges associated with telemetry are the following

  • Most telemetry implementations often include defining specific data formats that need to be shared between producer and consumer, which means adding and integrating with a bunch of plugins
  • If there are different microservices that are written in different languages, one needs different language bindings for polyglot support
  • To stream, store and visualize this data in real-time, one needs to understand and integrate more tools and technologies
  • If you add security to the mix with authentication, key management etc. for secure data exchange, the complexity increases further

You get the idea !

All this works well in a one-off deployment. But if one needs to do this on a repeatable and scalable basis and that too being agnostic of cloud provider / vendor, this becomes a big project in itself for DevOps teams.

What does plug and play telemetry mean here?

fledge.io has developed a simple telemetry implementation. Collect any type of data in a simple JSON format and just push it out by calling a REST API. That’s it !

Collect and stream any data

What are the advantages?

  • No need to define special data formats. Just use a simple JSON and push any data to an API in real time from your code
  • No plugins to integrate with. So, no installation of new packages or new tools to learn
  • No language specific bindings are needed. It works for all programming languages as all you need to do is call a REST API
  • All the data that is streamed is encrypted and transmitted over fledge.io App SDWAN (service mesh across clouds, datacenters, edges) that is also encrypted i.e. double encryption on the wire
  • Visualize your data with auto generated dashboards with time series views – the dashboards are specific to your application deployment and automatically show up on your fledge.io application dashboard
  • It is highly scalable as there is no polling, scraping service needed to be installed on each node, which often tends to be cpu intensive

This works just the same on any cloud, datacenter or edge environments

Same api interface on any cloud, datacenter or edge node

How does this help Developers?

As a developer, you do not need to worry about multiple tools or integrate with various plugins. Just collect any data (application health, performance, sensor…) you want in form of a simple JSON and push it out to a REST endpoint. That’s it.

It works the same no matter what programming language your microservices are written in.

How does it help DevOps?

Anyone who has configured different data collectors and visualization tools will understand the number of touch points you have to visualize the data. They will also be able to appreciate the complexity w.r.t identifying and mapping the data streams for visualization, especially if there are multiple streams of data coming in.

Imagine if you don’t have to worry about any of those and the dashboards are instantly, automatically generated for you when you deploy the application with a click of a button ?

This is exactly what fledge.io telemetry does for you.

Customers can focus on actual policies and decisions to make from the data instead of spending significant time to get visibility to it.

Did you say – too good to be true? Well, the proof is in the pudding.

Reach out to us at info@fledge.io to see a demo.

Stay tuned for next set of announcements around data infrastructure.

Pramodh Mallipatna
Founder and CEO
fledge.io

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