Elastic Stack provides all sorts of things, so it provides Elasticsearch for the transformations into a specific format, and pipelines can be defined for distributed applications along with the logs that come in the JSON format, which is clean. It's only the enhancements or the security that the product lacks and needs to be enhanced. I don't think further enhancement of the features needs to be added to the solution because it is already equivalent to a monitoring or alerting system, like Dynatrace and other tools. Some developments in the area of AI, which Elastic Stack is currently working on, should be fine in terms of the enhancements. Whenever some critical issue happens, there should be some kind of a co-pilot that helps resolve the issue. The tool should learn from its own previous issues. If you take Databricks, you see that it provides a co-pilot for Python, so a similar kind of development in Elastic Stack would be a real asset for it. AI would be considered a good way to enable the tool further for more in 2024, and even a beta launch would be helpful. If you take any sort of cloud-native monitoring product, like Azure Monitor or AWS CloudWatch, you see that such products don't provide much of the insights. If you go with Azure Monitor for any sort of ML models to be there, Sentinel needs to be used from Azure, which is very costly. AI-enablement would be a big improvement in Elastic Stack. Everyone in the monitoring space, including Dynatrace and New Relic, has lately been discussing AI, but it doesn't seem to be coming out. If there is room for an ML model in Elastic Stack, then it would be good.
