By: Gregg Ostrowski, CTO Advisor, Cisco AppDynamics
Organizations across a wide range of industries will be looking to accelerate their Industry 4.0 transformation programs this year. From semiconductors and electronics, through pharmaceuticals, to automotive and aerospace, manufacturers recognize the need to innovate at even greater speeds to compete in the future economy.
The World Economic Forum describes Industry 4.0 as the fusion of technologies blurring lines between physical, digital and biological spheres, and that it will “herald the transformations of entire systems, production, management, and governance” for organizations across the world. The move to smart factories is expected to grow by 20.6% year on year over the next three years, reaching more than $165 billion by 2026.
Significantly, this exponential growth will be based on a seismic shift to cloud native technologies across all corners of the manufacturing industry. Businesses will rely on cloud native technologies to deliver the speed, agility and resilience required to increase release velocity and respond to rapidly changing business needs.
Therefore, it’s essential that business and IT leaders approach the transition to cloud native technologies in a strategic way, ensuring their technologists have the tools and insights they need to monitor and optimize availability and performance across these highly fragmented and dynamic cloud native environments at all times. Ultimately, the success of any Industry 4.0 program will hinge on the organization’s ability to deliver seamless digital experiences to customers, suppliers and staff, without disruption or downtime.
Industry 4.0 is built on a shift to cloud native technologies
The shift from partial to fully automated factories is incredibly complex and some manufacturers are still trying to work out exactly how this new concept can best be applied within their operations, while others are facing cultural resistance. As with all digital transformation programs, there are also difficulties in integrating information technologies (IT) and operational technologies (OT) alongside legacy equipment.
Another significant challenge is managing the shift to cloud computing, which is widely accepted as a critical foundational infrastructure component required to scale Industry 4.0 strategies. As manufacturers race to reap the benefits of Industry 4.0 and the Industrial Internet of Things (IIoT), we are seeing even greater volumes of applications being spread across multiple cloud environments. Modern application architectures, built on technologies such as microservices and Kubernetes, present huge benefits for organizations in terms of improved speed to innovation, greater flexibility and improved reliability.
Explosion of data in cloud native environments threatens Industry 4.0 programs
However, this shift to cloud native technologies is dramatically increasing the complexity of application topologies, with organizations deploying thousands of microservices and containers. Many IT teams currently don’t have full or unified visibility across the technology landscape supporting these cloud native applications, which makes it extremely challenging for them to manage performance and availability.
In order to understand how an application is performing in modern IT environments, technologists need visibility across the application level, into the supporting digital services (such as Kubernetes), and into the underlying infrastructure-as-code (IaC) services (such as compute, server, database, network) that they’re leveraging from their cloud providers.
The distributed and dynamic nature of cloud native applications makes it extremely difficult for technologists to pinpoint the root cause of issues, due to new application behaviors and fault modes and data volumes which far outweigh what humans can handle. Cloud native technologies such as microservices and Kubernetes rely on thousands of containers and spawn a massive volume of metrics, events, logs and traces (MELT) every second.
The upshot of this is that many IT teams find themselves being bombarded by massive volumes of performance data from every corner of their IT landscape, and without the tools to cut through the noise to make informed decisions and prioritize their actions. In our Agents of Transformation 2022 report, 65% of technologists admitted that they feel overwhelmed by the soaring volumes of data being caused by rapid innovation and spiraling complexity.
This is evidently a major threat to the success of Industry 4.0 programs, which rely so heavily on the use of data and insights to monitor and improve performance within the context of business goals and to power operational decision making. Business and IT leaders need to leverage smart data in order to understand and report on the impact of newly embedded technologies and to identify opportunities for further innovation and growth.
Visibility into cloud native environments is critical to deliver and measure Industry 4.0 success
To overcome this escalating problem, manufacturers should be looking to implement a modern, cloud native observability solution which allows their IT teams to manage complex and dynamic applications and technology stacks. And critically, they need a solution which enables them to monitor the health of key business transactions distributed across their entire technology landscape.
Organizations need to be able to monitor performance at both a technical and business level throughout a transformation program, with observability plugged into the CI/CD pipeline (Continuous Integration/Continuous Delivery) from the very start. This is crucial to avoid application or infrastructure silos further down the line, and to ensure people and processes are unified around a single, trusted set of data.
Cloud native observability provides technologists with meaningful insights when issues arise, enhancing application performance and providing an always-on snapshot of the end-to-end health across the entire technology estate; distributed applications, APIs, networks, public and private cloud infrastructure, IIoT and any other connection points. They’re able to quickly see where slowdowns and failures are occurring at any given time, as well as identify issues that may occur but haven’t yet.
Importantly, artificial intelligence (AI) and machine learning (ML) enables a more proactive approach to monitoring, helping to correlate issues with the potential severity of impact on business priorities across the full lifecycle of a technology ecosystem. Remediation can be executed quickly and in order of importance even if the issue lies outside the organization’s control because alerts sound off when third-party anomalies are discovered, which enables reporting to be expedited.
With real-time insights from the business transaction’s telemetry data, technologists can quickly identify the root cause of issues and expedite resolution, ensuring that their applications are delivering the level of digital experiences that customers, suppliers and employees now expect. Only with this level of visibility into cloud native environments, will manufacturers be able to fully reap the benefits of their Industry 4.0 initiatives.
