Elevator Pitch
Data influences decision-making, and real-time data enables immediate decisions. Mere monitoring and reacting to failures are insufficient. Thus, having a robust full-stack observability strategy along with AIOPS becomes increasingly vital for preventing recurrent failures in the future.
Description
By embedding observability earlier in the software lifecycle, engineers can plan for and fix performance problems that they ordinarily wouldn’t recognise until code is running in production. In this talk, let us delve into harnessing AI/ML capabilities on AWS. AIOps empowers organizations to achieve an advanced, proactive full-stack observability model. This enables automated responses to emerging issues and harnesses data for improved resilience and optimization.
Notes
In this presentation, I will talk about the significance of full-stack observability in today’s enterprise landscape. I’ll explain how it plays a pivotal role in identifying and resolving issues, enhancing performance, and guaranteeing the overall reliability of applications. Drawing from my extensive experience with various clients, I’ll provide concrete examples of real-time use cases and scenarios that highlight the practical benefits of full stack observability.
Furthermore, I will explore the suite of AWS tools that can be leveraged to construct an effective observability solution. These tools are instrumental in collecting and analyzing crucial data for actionable insights.
Lastly, we’ll delve into the synergy between AI and observability, showcasing how artificial intelligence can bolster observability efforts and contribute to the development of highly resilient systems.