Estimating the TCO to Build & Operate an ELK Stack

Scale an ELK Stack? Sure, but get ready for a PhD in ELK scaling and expect to provision 5x the storage for indices compared to your source. That’s right - 5x your source multiplied by the # of days of retention. Now consider how much RAM, the number of nodes, sharding, retention, tuning the OS, Java etc. - and you're just getting started!

ChaosSearch separates storage, compute, and system services that makes it possible to easily and dynamically scale system resources to accommodate additional data sources, users, and query volumes.

Looking for insights from new data via an ELK Stack? You have work to do first. New data, new fields... which ones do you index? How do you map them?  So much for quick.

ChaosSearch automates each aspect of the data journey, allowing workloads to be added within minutes, not weeks or months. With new fields automatically added on the fly, simply get your data to S3 and start querying and building visualizations right away.

Many set out to design and maintain a perfectly stable ELK Stack.  Unfortunately it's just not that simple, and the scenario often devolves into one of getting the master node ready, and then praying node failures don’t leave users unproductively waiting for the system to rebalance.  

ChaosSearch interacts directly with cloud object storage, like Amazon S3, that offers near-infinite scalability, availability, and durability.  S3 is bedrock. It's global, distributed, has great networking, and sits at the core of the ChaosSearch architecture.

ELK Stacks can perform fine when the perfect cluster is perfectly configured.  Unfortunately perfection is very hard to achieve, and regardless, performance deteriorates over time and with scale, unless dedicated maintenance effort is concurrently scaled.

Chaos Fabric® orchestrates indexing, search, and queries, which enable UltraHot® fully scalable performance with your Amazon S3.

It's no surprise that a self-managed ELK Stack requires, well, management. This includes maintenance and patching. Keep in mind that your end users often won’t have access to the data that they need while this maintenance is occurring. It takes time and attention to deal with these updates, and we haven't even touched on the thousands of Elasticsearch servers compromised with misconfigured security on the public internet.

ChaosSearch eliminates the need to add, deploy, and manage hardware or software. There’s no system to manage or software to update.

With an ELK Stack, you need to push data and transform in Logstash or Fluentd.  Subsequent changes then mean you must reindex and re-map.  Time consuming and tedious.

With ChaosSearch there is no data movement, transformation, or schema management. Instead, the Chaos Refinery® cleans, prepares, and virtually transforms data directly within your Amazon S3.

Do you really want to have constantly be concerned about shard quantity, multiple indices, mapping, a Java heap, performance, retention, node count and impact of data growth? Don’t you just want answers from your data with an index that is up to 95% smaller than the original source data?

Chaos Index® reduces the size of information by up to 95% while still fully indexing it, eliminates sharding, and natively supports text search, relational queries, and machine learning.

A true TCO of your ELK Stack must include the cost of administration and maintenance, as well as very tough decisions on what data you can afford to keep to stay within your budget. Data never gets smaller and costs accelerate with scale in the ELK world.

The unique ChaosSearch architecture and technologies consume far fewer resources than comparable search or relational analytics solutions — providing cost savings of up to 80%.