Many big businesses depend on Elasticsearch, a highly scalable, full-text, open-source search and analytics engine. All of its applications are so vital that enterprises are ready to cover the costs regardless of what they may be. Moreover, Elasticsearch users are dependent on the extensive data storage services it offers. Since data storage and accessibility are generally expensive, reducing your Elasticsearch may seem to tricky to even be worth trying, but it’s still absolutely possible. This article will offer three useful cost-cutting hacks for a dramatic change in your bills for this platform.
1. Clear the Data log
Clearing data logs is a major way to lower costs. Your elastic cloud enterprise service comes with data logs on the console. When monitoring data logs, you’ll find cluster after cluster of unnecessary information. For one, certain types of data repeat themselves regularly. Though you may need some of this information, you don’t need so many repeats of it and it’s better to filter those out. Also, take a look at other equally efficient platforms to execute your Elasticsearch enterprise needs.
SearchBlox is one service provider that will help you optimize your enterprise search operations. Their tool offers users more intelligent searches on an enterprise level. In fact, with this elastic cloud platform, you’ll have your very own web admin console with easy index management. There are 150+ connectors, including Google Drive, Github, Salesforce, Dropbox, and more. With this service, you’ll probably have less unnecessary information clogging up your database. The last thing you want is a glitchy search engine that’s making your account bleed. So, besides removing items you don’t regularly use, make sure you use the right platform.
2. Rollup Organizational Data
Whether you are using cloud or Elasticsearch for data storage and accessibility, there are ways to maximize your benefits. One way is to roll up your organizational data into one compressed summary document. Once done, simply delete the main copy, which, in turn, frees up space. It makes the information even more accessible since the compressed index only contains data that you need.
Even more, these rollups are just like any other indexes you’d create but a lot smaller. There’s no special way to store them. Just categorize them like any other index. Using up less space immediately translates to fewer costs.
3. Retrieve Data by Compound Query
Retrieving data by compound query is another smart method to reduce your costs. When dealing with any sort of Elasticsearch API, you should always try to reshape, join, and specify the search query into one single query. This method is known as a compound query. Retrieving data in this way will be enough on its own to reduce the search quantity to a major degree and, therefore, directly impact your costs. Creating a compound query is certainly not possible for each input. However, by regularly implementing this best practice, your Elasticsearch costs will drastically reduce.
To implement a compound query, knowledge of the available data types and data structures is vital. Armed with this knowledge, querying an Elasticsearch by a compound query is a no-brainer. It’s also worth noting that each cloud-based Elasticsearch provider has their way of manipulating search queries. So, to implement a compound query, you will need to get familiar with the Elasticsearch console of your cloud service provider. The console is where you can directly experiment and manipulate search queries and see the results there and then.
One last pro tip: remember Elasticsearch API will take longer to process compound queries due to the task’s complexity. To get started, check out the above video for step by step instruction.