Introduction Search is not just traditional TF/IDF any more but the current trend of machine learning and models has opened another dimension for search. This talk gives an overview of: Classic search and its limitations. What is a model and how can you use it. How to use vector search or hybrid search in Elasticsearch. Where OpenAI’s ChatGPT or similar LLMs come into play to with Elastic. Check how to leverage Leverage ChatGPT with Elasticsearch ....
Introduction Bring logs, metrics, and traces from your Kubernetes cluster and the workloads running on it into a single, unified solution. Elastic observability gives better visibility on your kubernetes ecosystem where you can monitor your pods, services, workload etc. Use a centrally managed Elastic Agent to gain visibility into your Kubernetes deployments on EKS, AKS, GKE or self-managed clusters. Talk Video
In this blog, we will see how you can quickly setup ELK (Elasticsearch, Logstash, Kibana) stack to receive the HTTP webhook. Mostly ELK stack is known for logging purposes. But Elastic stacks are much more beyond the logging use case. Elastic provides Search, Observability & Security you can check more on this with official documentation . What is Webhook ? Webhook enables the two programs to communicate or transfer the data with the help of callback functions / hooks....
What this talk is all about ? Elastic Stack (Elasticsearch, Logstash, Kibana and Beats) is such a platform which is built for scalability, performance and “You know… for Search”. When you have a system which scales to the horizons of your data, helps you in your data quest, shows you insights - imagine what you can do with it. Talk Video Feel free to comment below, If you have any doubts or suggestion about this talk....