Similar trends in multiple industries are apparent.
- Telecommunications Provider e.g. AT&T
- Networking/Internet IP,MPLS Service Providers
- Cloud Native Iaas, PaaS, SaaS industry
Let’s see what the trend is that they have in common:
- Telecom – AT&T ONAP’s DCAE – Data Collection, Analytics and Events
- Networking/Internet Service Provider – Cisco/Juniper Telemetry
- Cloud Native – Kafka and streaming events data from Microservices architectures
What they have in common is events & data production and thereafter streaming of the data and thereafter analytics on these events/data resulting in near real time decision making.
The naming is different, the products are different and the industries are different but the production of data, its streaming and analytics is common.
Telecom industry is moving from PNF (Physical Network Functions) to VNF (Virtual Network Functions). Which is a move from tightly coupled hardware/software devices to a more software driven architecture
The ISP industry is still shifting around IP Packets but they are now looking for more streaming style analytics of their devices and the traffic flows which they are calling Telemetry.
The Cloud Native industry is in the pack with its Microservices based software centric application architectures.
They all have event generation in common and want to process the data and then use it in real time. Real Time Data Streaming and Processing.
Lets now see dig a little deeper and start correlating the terminologies. From the products category we will take Telecom’s ONAP, Networking’s Cisco DNA, Cloud Native’s Prometheus and Kafka and Information Security’s Splunk from the industries to analyse.
ONAPs VNF Event Stream or VES is the stream event producer. ONAPs logging section utilises the same ELK, Elastricsearch Logstash and Kibana dashboarding available in AWS cloud.
Juniper’s Telemetry streaming utilises Google’s Protocol Buffers (gpb) structured messages are relayed to a performance management application. Cisco’s Model Driven Telemetry utilises the same Google Protocol Buffers for streaming data from its devices.
Cloud Native applications are Microservices based which has Event Sourcing and CQRS and are requiring Rabbit MQ/Kafka style message brokers in addition to stream processors and analytics such as the same ELK stack mentioned earlier.
Large organisations such as Linkedin faced the problem of data deluge earlier than the rest of the world in terms of its handling, processing and analytics in real time. This has resulted in products such as Kafka.