Today’s enterprise applications are increasingly deployed in various public clouds. Even if your organization is traditionally based on on-premises infrastructure, chances are that you will have to consider migrating to a public or hybrid cloud model. With this transition to public cloud, there is often a lack of clarity about a key question related to security: who is responsible for your application’s security and compliance with established standards. In the case of public clouds, the answer is that security is a shared responsibility between the public cloud provider as well as your organization that deploys in the public cloud. Let’s double click on that shared responsibility to identify some aspects of security that can become blind spots and cause vulnerabilities.

Observability is a critical component of any enterprise software-as-a-service (SaaS) application. These applications are deployed in public or private clouds. These deployments either rely on a cloud provider’s native observability solution or choose one of the third-party monitoring products. Either one of these two types of solutions typically work well for an early stage startup company.

In today's fast-paced world of software development and operations, observability plays a crucial role in ensuring the performance, reliability, and security of applications and infrastructure. Traditionally, monitoring has been a reactive process, with DevOps teams relying on notifications and log analytics after an incident has occurred. However, with the advent of Artificial Intelligence (AI) in observability, we are witnessing a transformation that empowers DevOps to close the loop by collecting real-time data and proactively addressing issues. In this blog post, we explore how AI-driven observability is reshaping incident response, improving SRE efficiency, and revolutionizing the way we handle production issues.

The rise of AI, exemplified by the groundbreaking ChatGPT, has sparked intense curiosity across the computing industry. As businesses explore the implications of AI in their respective domains, observability emerges as a critical focus. In this blog post, we delve into the fascinating world of AI and observability, unraveling its impact on various observability sub-functions, and how observability contributes to the success of AI systems.