With the growth in the volume and increasing complexity of production deployments and operational pipelines, managing logs and metrics is a crucial component of successful IT deployment. DevOps teams and administrators need logs and metrics to gain operational insights, meet their SLA obligations, prevent unauthorized access, and to identify errors, anomalies, or suspicious activity. For that, many companies turn to Elasticsearch.
But Elasticsearch comes with a host of challenges on its own, including ensuring high performance, data protection, and lowering costs for that large amount of data. How can you overcome these Elasticsearch optimization challenges? These are all areas where NetApp Cloud Volumes ONTAP can help.
How does this work? In our new ebook on Elasticsearch optimization with Cloud Volumes ONTAP we go in depth into how Elasticsearch users can enhance their deployments with Cloud Volumes ONTAP for improved performance, and reduced storage costs and operational overheads.
In this post, let’s take a look at some of the challenges that can come up in an Elasticsearch deployment which would require a solution like Cloud Volumes ONTAP to be used.
Elasticsearch is a distributed search engine and data analytics platform based on the Apache Lucene search and indexing library. While Elasticsearch is one of the most efficient systems for collecting, indexing, and unifying log, metrics, and other mission-critical data across different environments, there are challenges that can arise when running it in production at scale. Some of these challenges are:
How can these performance and cost challenges that come with high-volume Elasticsearch deployments be solved? With NetApp Cloud Volumes ONTAP, Elasticsearch users can experience dramatic improvements in performance, and considerable reductions of storage costs and operational overheads for Elasticsearch clusters.
Cloud Volumes ONTAP is NetApp’s software-defined storage solution that provides enterprise storage features such as data protection, high availability, and storage efficiencies for cloud-based block storage on AWS, Azure, and Google Cloud. These capabilities, when used in conjunction with Elasticsearch can considerably improve performance and lower costs.
Elasticsearch optimization with Cloud Volumes ONTAP begins at the storage layer. When using Cloud Volumes ONTAP together with Elasticsearch, Cloud Volumes ONTAP serves as a storage management layer for the cloud volumes (e.g., Amazon EBS) used by Elasticsearch to store and manage data (see the image below).
This solution gives Elasticsearch users three essential benefits for their deployment: a clear boost in performance, significantly lower storage costs, and an overall reduction in operational overheads.
NetApp’s Cloud Volumes ONTAP is a powerful cloud storage management tool that provides a host of enterprise-grade features for cloud storage deployments. Its built-in storage deduplication, compression, data tiering, and thin provisioning can dramatically improve the performance of Elasticsearch deployments in the cloud and cut storage costs. High availability, data protection, and disc cloning features also decrease operational overheads for managing storage in the cloud making it easy for DevOps to ensure the fault tolerance of Elasticsearch deployments.
To find out more about Elasticsearch optimization with Cloud Volumes ONTAP, from enhanced performance to decreased storage costs, check out the full ebook here.