Generative AI (GenAI) engineering refers to the field of engineering that focuses on the development, implementation and optimization of generative AI models. Generative AI refers to technologies that can generate new derived versions of content, strategies, designs and methods by learning from large repositories of original source content. By developing GenAI models, engineers can create new and innovative ways to generate content. The vendors in this segment are made up by incumbent and startup vendors covering full-model life cycle management, specifically adjusted to and catering to development, refinement and deployment of generative models (e.g., LLMs) and other GenAI artifacts in production applications. Please note that this market is based on Beta research and is continuously evolving. We will be making changes as and when there are new updates.
Gartner defines observability platforms as products that ingest telemetry (operational data) from a variety of sources including, but not limited to, logs, metrics, events and traces. They are used to understand the health, performance and behavior of applications, services and infrastructure. Observability platforms enable an analysis of the telemetry, either via human operator or machine intelligence, to determine changes in system behavior that impact end-user experience such as outages or performance degradation. This allows for early, and even preemptive, problem remediation. Observability solutions are used by IT operations, site reliability engineers, cloud and platform teams, application developers, and product owners. Observability platforms are used by organizations to understand and improve the availability, performance and resilience of these critical applications and services. Investment in and successful deployment of observability platforms leads to revenue loss avoidance and enables faster product development cycles and improvements in brand perception.