The Internet of Things: Surviving the Connected Device Transition

How to handle the emergence of the IoT in the world of automation

Yann Guernion
Yann Guernion, October 20, 2017 2:30 pm
Blog > Workload Automation | AWA | IoT > The Internet of Things: Surviving the Connected Device Transition

The Internet of Things (IoT) continues to expand exponentially. According to prospective studies from analyst firms such as IDC and Forrester, or network vendors such as Cisco, the number of connected devices could reach between 25 and 50 billion by 2020.

For IT departments, this huge volume of connected devices will pose many challenges, including security, communication, processing, storage and complexity. As a result, Gartner estimates that in 2018 more than 75% of IoT-related projects will have lasted twice as long as expected.

In this context, automation is key to IoT projects succeeding. In particular, it addresses data-related issues: collecting information from heterogeneous sources, absorbing workload peaks, distributing data in various Big Data and BI environments, and leveraging expert knowledge into standardized processes. Traditional Data Warehouse processes and tools are no longer adapted to the speed and volume that will be imposed by the IoT.

Who is concerned? Potentially all businesses aiming at near real-time interactions with consumers. And this ranges across all sectors: insurance with accident sensors, health with biological or physiological sensors, manufacturing with maintenance sensors, marketing with location and environmental sensors, utilities with smart meters... The list goes on.

iDate’s research assumes more than 1.8 billion smart meters will be deployed in 2018 by water or energy suppliers. For example, a major US, west coast-based utility company was faced with the problem of processing nearly 90 million smart meter readings per day. Workload automation was introduced to fully automate data flows across the entire process; from acquisition to the delivery of information. As a result, processing time was reduced by 70%, errors were completely eliminated and the overall simplification allowed teams to concentrate on the development of new customers services.

CA Automic Workload Automation: Taking Data Flow Orchestration to a New Level

The Internet of Things requires you to efficiently capture and store data as it emerges in any volume, velocity, or variety. You also need to distribute it to hundreds of downstream applications—sometimes in real-time. Version 12.1 of CA Automic Workload Automation takes orchestration of these data flows to a new level of security and speed.

The CA Automic Automation Engine can now handle up to 500,000 agent connections per instance and fully supports hybrid networks, with a mix of IPV4 and IPV6 protocols. Version 12.1 also introduces an Event Engine that adds unprecedented reactivity to automation by correlating up to 25,000 external events per second. As a result, it dramatically reduces latency in workflows, guaranteeing information delivery and integrity in large-scale dynamic environments.

Today’s automation solutions are often too primitive for the IoT; they are unable to connect large numbers of heterogeneous devices and systems, handle different data formats or traverse various networks. As such, introducing a forward-facing solution, which supports massive environments and complex event-driven data management, such as CA AWA v12.1, will definitely set the new standard for automation in the digital age.

If you’re driving your digital transformation and building new innovative services, it’s time to consider CA Automic Workload Automation’s unique capabilities.

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Yann Guernion

Yann Guernion

Yann Guernion is Product Marketing Director at Automic Software. With over 25 years of experience in the world of IT, Yann has a wealth of expertize in managing the entire product line lifecycle.