![]() While needs will vary by customer use case, our experience shows the efficiencies in the Elastic Stack and Elastic data lifecycle management allow the Elasticsearch Warm Tier, Kibana, and Proxy servers can be supported by 1 physical CPU to 2 vCPUs and the Cold Tier can be upwards of 4 vCPUs to a physical CPU.īecause Elasticsearch tiers data on independent data nodes versus multiple mount points on a single data node or indexer, the multiple types and classes of software-defined storage defined for independent HCI clusters can be easily leveraged between Elasticsearch clusters to address data temperatures. The Elastic Stack tends to take advantage of hyperthreading and resource overcommitment more effectively. While this is admittedly like the VMware guidance for some similar analytics platforms, these VMs tend to consume a significantly smaller CPU footprint per data node. We would recommend sizing for 1 physical CPU to 1 virtual CPU (vCPU) for Elasticsearch Hot Tier along with the management and control plane resources. Additionally, the Elastic Stack is also significantly more CPU efficient than some alternative products improving the cost-effectiveness of deploying Elastic with VMware or other virtualization technologies. With the current ability to support up to 112 cores and 6TB of RAM in a single 2RU Dell server, Elasticsearch is an attractive application for virtualization. Elasticsearch data nodes tend to have average allocations of 8-16 cores and 64GB of RAM. Virtualization has long been a strategy for achieving more efficient resource utilization and data center density. Additionally, the Elastic Stack can be deployed on Kubernetes clusters, therefor admins can also choose to leverage VMware Tanzu for Kubernetes management. VxFlex admins use their preferred hypervisor and VxFLEX OS and for VxRail it is done with VMware ESX and vSAN. However, unlike bare-metal deployments, HCI also scales vertically by adding resources dynamically to Elasticsearch data nodes or any other Elastic Stack roles through virtualization. HCI also uses a scale-out deployment model that allows for easy, seamless scalability horizontally by adding additional nodes to the cluster(s). ![]() Data nodes can be added to an Elasticsearch cluster to provide additional compute and storage resources. The Elastic Stack, and Elasticsearch specifically, is designed for scale-out. It will be shown how the features of HCI provide distinct benefits and cost savings as an integrated solution for the Elastic Stack. ![]() In March 2020, Dell Technologies validated the Elastic Stack running on our VxFlex family of HCI 2. Platforms designed for scale-out performance running the Elastic Stack provides the ability to analyze and correlate data in near real-time. With the Elastic Stack, organizations can collect data from across the enterprise, normalize the format, and enrich the data as desired. Elasticsearch is an end-to-end solution for searching, analyzing, and visualizing machine data from diverse source formats. Elasticsearch is an open-source, distributed, scalable, enterprise-grade search engine based on Lucene. The Elastic Stack is a collection of four open-source projects: Elasticsearch, Logstash, Kibana, and Beats. We show below why both HCI offerings are highly efficient and effective platforms for a truly scalable Elastic Stack deployment. VxRail is the only fully integrated, pre-configured, and pre-tested VMware HCI system powered with VMware vSAN. Dell Technologies also offers the VxRail HCI platform for VMware-centric environments. VxFlex OS is the software that creates a server and IP-based SAN from direct-attached storage as an alternative to a traditional SAN infrastructure. VxFlex is a Dell Technologies developed, hypervisor agnostic, HCI platform integrated with high-performance, software-defined block storage. Local resources from each server in the cluster are combined to create virtual pools of compute and storage with multiple performance tiers. ![]() The breadth of server offerings in the Dell PowerEdge portfolio gives system architects many options for designing the right blend of compute and storage resources. HCI integrates the compute and storage resources from a cluster of servers using virtualization software for both CPU and disk resources to deliver flexible, scalable performance and capacity on demand. Dell Technologies is an Elastic Technology Partner 1 This blog covers some basics of hyper-converged infrastructure (HCI), some Elastic Stack fundamentals, and the benefits of deploying Elastic Stack on HCI. ![]() The Elastic Stack is useful for a wide range of applications including observability (logging, metrics, APM), security, and general-purpose enterprise search. The Elastic Stack, also known as the “ELK Stack”, is a widely used, collection of software products based on open source used for search, analysis, and visualization of data. ![]()
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