Multi-Cloud Observability: Tools and Techniques for Monitoring and Troubleshooting Complex Hybrid Cloud Environments

Abstract

This article focuses on detection tools and methods for hybrid cloud that are used to deal with complexity levels within multi-cloud infrastructures. It breaks down some of the best open-source and commercial observability solutions, like Prometheus, Grafana, Jaeger, Datadog, New Relic, Dynatrace, and Splunk, describing the offered functions, their advantages, and disadvantages. Some of the problems highlighted in the research include multi-cloud visibility and data consistency, integration difficulties, and inherent scalability. The real-life examples of TD Bank and Blinkit show how organizations can use and realize the values of observability solutions for better service dependability, quick reaction to incidents, and customer satisfaction. The paper then analyses some of the new trends, like the use of artificial intelligence in monitoring and enabling automated repairs and improvements to the network while at the same time trying to improve operational efficiency and looking at operation costs. Core problem-solving approaches for multi-cloud cases are articulated, which include diagnostics of the root cause, proper handling of the incident handling process, and the use of intelligent automation for problem-solving. Thus, the results highlight the need to implement extensive observability strategies for the effective management of distributed cloud systems. Future advancements are expected with cloud technologies; hence, organizations need to keep abreast of the latest concerning observability tools and approaches to ensure their multi-cloud environments remain high on performance and reliability.