Edit file File name : es_s3_hybrid.yaml Content :# Elasticsearch / S3 Hybrid Vector Configuration Example # ------------------------------------------------------------------------------ # This demonstrates a hybrid pipeline, writing data to both Elasticsearch and # AWS S3. This is advantageous because each storage helps to offset its # counterpart's weaknesses. You can provision Elasticsearch for performance # and delegate durability to S3. data_dir: "/var/lib/vector" # Ingest data by tailing one or more files # Docs: https://vector.dev/docs/reference/sources/file sources: apache_logs: type: "file" include: ["/var/log/*.log"] ignore_older_secs: 86400 # 1 day # Optionally parse, structure and transform data here. # Docs: https://vector.dev/docs/reference/transforms # Send structured data to Elasticsearch for searching of recent data sinks: es_cluster: inputs: ["apache_logs"] type: "elasticsearch" endpoint: "79.12.221.222:9200" doc_type: "_doc" # Send structured data to S3, a durable long-term storage s3_archives: inputs: ["apache_logs"] # don't sample type: "aws_s3" region: "us-east-1" bucket: "my_log_archives" framing: method: "newline_delimited" encoding: codec: "json" compression: "gzip" batch: max_size: 10000000 # 10mb uncompressed Save