As enterprises race to operationalize generative AI throughout software development lifecycles, major cloud vendors are rapidly modernizing their solutions to better cater to these new demands. In March 2025, Amazon Web Services (AWS) added a new layer of functionality to OpenSearch—a distributed search and analytics engine for log-monitoring, observability, and real-time application performance-tracking.
The latest update integrates GenAI features powered by Amazon Q Developer into OpenSearch. This introduces natural language querying and AI-generated incident summaries to help developers with increasingly complex infrastructure management needs. Consider a typical scenario where a DevOps engineer is tasked with diagnosing a performance issue tied to a recent code deployment. Normally, this involves scanning through hundreds of log entries and writing queries in OpenSearch’s domain-specific syntax to identify the root cause. However, with the new GenAI integration, engineers can ask in plain English a question like: “Why did latency spike in the EU region after 3pm yesterday.” The AI assistant will then parse the logs and analyze patterns to return a concise answer, even accompanied by visual breakdowns by region, endpoint, and other key factors.
Enhancing digital experiences with proactive incident response
Customers are more demanding than ever when it comes to seamless digital experiences. Employees also depend on high performance and availability to maintain peak productivity. By introducing GenAI into remediation workflows, most incidents can be resolved in a fraction of the time compared to the reactive and largely manual workflows of old. Moreover, even those with relatively limited technical skills can do much more than they were previously able to.
Another key feature of this latest integration is the ability to generate easily understandable incident summaries—similar to what an experienced DevOps engineer might compile after the event. In high-volume environments where even just a few minutes of unscheduled downtime can be very costly, these accelerated diagnoses can significantly reduce mean time to resolution (MTTR) and provide the insights needed to prevent the issue from reoccurring.
AWS has also designed the system to help teams set up and customize anomaly detection workflows. For instance, instead of engineers having to manually configure things like performance thresholds or patterns, AI can now recommend settings based on previously observed system behavior. This should prove especially helpful when managing systems distributed across multiple regions and data centers, where the variables are simply too numerous for one-size-fits-all solutions.
Ultimately, OpenSearch’s newly integrated GenAI capabilities give teams a new layer of intelligence—albeit one in which outputs still need to be vetted carefully. In practice, this new functionality should change the rhythm of DevOps work by greatly reducing the need to cross-reference dashboards or manually construct queries.