From 61bafef70ac2e6e9fbd24c4763eaff0e9111187c Mon Sep 17 00:00:00 2001 From: George Wallace Date: Fri, 8 Nov 2024 15:42:42 -0700 Subject: [PATCH] updates --- .../reference-architectures/index.asciidoc | 4 +-- .../reference-architecture-overview.asciidoc | 35 +++++++++++++++++++ 2 files changed, 37 insertions(+), 2 deletions(-) create mode 100644 docs/reference/reference-architectures/reference-architecture-overview.asciidoc diff --git a/docs/reference/reference-architectures/index.asciidoc b/docs/reference/reference-architectures/index.asciidoc index d044cebd47834..b230899566548 100644 --- a/docs/reference/reference-architectures/index.asciidoc +++ b/docs/reference/reference-architectures/index.asciidoc @@ -1,7 +1,7 @@ [[reference-architectures]] = Reference architectures -Elasticsearch reference architectures are blueprints for deploying Elasticsearch clusters tailored to different use cases. Whether you're handling logs or metrics these reference architectures focus on scalability, reliability, and efficient resource utilization. Use these guidelines to deploy Elasticsearch for your use case. +Elasticsearch reference architectures are blueprints for deploying Elasticsearch clusters tailored to different use cases. Whether you're handling logs or metrics these reference architectureßs focus on scalability, reliability, and efficient resource utilization. Use these guidelines to deploy Elasticsearch for your use case. These architectures are designed by architects and engineers to provide standardized, proven solutions that help users follow best practices when deploying Elasticsearch. Some of the key areas of focus are listed below. @@ -19,7 +19,7 @@ These reference architectures are recommendations and should be adapted to fit y [cols="50, 50"] |=== | *Architecture* | *When to use* -| <> +| <> The Hot / Frozen – High Availability architecture is cost optimized for large time-series datasets. diff --git a/docs/reference/reference-architectures/reference-architecture-overview.asciidoc b/docs/reference/reference-architectures/reference-architecture-overview.asciidoc new file mode 100644 index 0000000000000..d044cebd47834 --- /dev/null +++ b/docs/reference/reference-architectures/reference-architecture-overview.asciidoc @@ -0,0 +1,35 @@ +[[reference-architectures]] += Reference architectures + +Elasticsearch reference architectures are blueprints for deploying Elasticsearch clusters tailored to different use cases. Whether you're handling logs or metrics these reference architectures focus on scalability, reliability, and efficient resource utilization. Use these guidelines to deploy Elasticsearch for your use case. + +These architectures are designed by architects and engineers to provide standardized, proven solutions that help users follow best practices when deploying Elasticsearch. Some of the key areas of focus are listed below. + +* High availability +* Scalability + +TIP: These architectures are specific to running your deployment on-premises or cloud. If you are using Elastic serverless your Elasticsearch clusters are autoscaled and fully managed by Elastic. For all the deployment options, see https://www.elastic.co/guide/en/elasticsearch/reference/current/elasticsearch-intro-deploy.html[Run Elasticsearch]. + +These reference architectures are recommendations and should be adapted to fit your specific environment and needs. Each solution can vary based on the unique requirements and conditions of your deployment. In these architectures we discuss about how to deploy cluster components. For information about designing ingest architectures to feed content into your cluster, refer to https://www.elastic.co/guide/en/ingest/current/use-case-arch.html[Ingest architectures] + +[discrete] +[[reference-architectures-time-series-2]] +=== Architectures + +[cols="50, 50"] +|=== +| *Architecture* | *When to use* +| <> + +The Hot / Frozen – High Availability architecture is cost optimized for large time-series datasets. + +a| +* Have a requirement for cost effective long term data storage (many months or years) +* Provide insights and alerts using logs, metrics, traces, or various event types to ensure optimal performance and quick issue resolution for applications. +* Apply Machine Learning and Search AI to assist in dealing with the large amount of data. +* Deploy an architecture model that allows for maximum flexibility between storage cost and performance. + + +|=== + +include::hot-frozen.asciidoc[]