What are the biggest challenges and opportunities for application monitoring in the future?

1 Cloud-native applications

Cloud-native applications are designed to run on distributed, dynamic, and scalable environments, such as cloud platforms, containers, and microservices. This offers many benefits, such as faster development, deployment, and innovation, but also poses new challenges for application monitoring. For example, how do you monitor the health and performance of hundreds or thousands of ephemeral and interdependent components? How do you handle the variability and unpredictability of cloud resources and network conditions? How do you ensure security and compliance in a multi-cloud and hybrid scenario? To address these challenges, you need to adopt a cloud-native approach to application monitoring, which means using tools and methods that are compatible with the cloud-native principles, such as observability, automation, resilience, and DevOps.

2 AI and ML

Artificial intelligence (AI) and machine learning (ML) are transforming the way we monitor applications, by enabling more intelligent, proactive, and automated solutions. For example, AI and ML can help you analyze large and complex data sets, such as logs, metrics, traces, and user feedback, and extract meaningful insights and patterns. They can also help you detect and diagnose anomalies, predict and prevent issues, optimize performance and resource utilization, and recommend actions and solutions. However, AI and ML also bring new challenges and opportunities for application monitoring. For example, how do you ensure the quality and reliability of the AI and ML models and algorithms? How do you explain and validate the results and decisions of the AI and ML systems? How do you balance the human and machine roles and responsibilities in application monitoring?

3 User-centric monitoring

User-centric monitoring is a shift from focusing on the technical aspects of application monitoring, such as availability, uptime, and response time, to focusing on the user experience and satisfaction. This means measuring and optimizing the application performance and functionality from the user's perspective, such as usability, accessibility, engagement, and conversion. User-centric monitoring helps you align your application monitoring goals with your business outcomes, such as customer retention, loyalty, and revenue. It also helps you identify and prioritize the issues and improvements that matter most to your users. However, user-centric monitoring also requires new skills and tools for application monitoring. For example, how do you collect and analyze user feedback and behavior data, such as surveys, ratings, reviews, sessions, and journeys? How do you define and track user-centric metrics and indicators, such as user satisfaction score (USS), user error rate (UER), and user journey success rate (UJSR)? How do you communicate and collaborate with other stakeholders, such as developers, designers, and marketers, to deliver a better user experience?

5 Edge computing

Edge computing is a trend of moving some of the computation and data processing from the centralized cloud servers to the edge devices, such as smartphones, tablets, laptops, sensors, and IoT devices. This offers many advantages, such as lower latency, higher bandwidth, better privacy, and more resilience. However, edge computing also creates new challenges and opportunities for application monitoring. For example, how do you monitor the performance and availability of the edge devices and networks, which may vary widely in terms of capacity, connectivity, and security? How do you collect and aggregate the monitoring data from the edge devices, which may be distributed, disconnected, or offline? How do you synchronize and coordinate the monitoring policies and actions between the cloud and the edge?