Elasticsearch reaches across different platforms to find data needed by developers and other technical users for an answer to different business needs within their data stores. It evolved from early versions of Lucene and Compass technologies developed by the company Elastic. They intended for Elasticsearch to become the primary RESTful distributed search engine in use.
It started off being used primarily for text searches on websites and other platforms. Elastic soon realized the potential of Elasticsearch as something more than a query engine. They’ve since made modifications expanding both its search and analysis capabilities.
This article explores the three main phases of Elasticsearch:
- Data ingestions
- Data transformation
- Data visualization
We’ll also cover how ObjectRocket DBaaS for Elasticsearch can provide businesses with needed guidance in fully utilizing its benefits.
Getting data into Elasticsearch can be overwhelming to those not used to working with it. Import methods vary depending on what’s being pulled in and why the data’s needed. Different tools are available to work with different file types. Data gets stored in nodes once it’s been imported, which can then be organized into related clusters.
ObjectRocket understands how to work with different open source shipper tools known as Beats. Businesses wanting to access log files on Apache might benefit from using Filebeat. Another company looking to probe the most popular sections of their websites might use a different tool like Packetbeat to analyze the most common paths taken by users.
Sometimes business store information in proprietary formats and don’t have the time to figure out a custom solution on their own. ObjectRocket steps in to provide aid and get them up and running. They make sure the final resolution continues to function once it’s been built.
A development team might have some difficulty coming up with a way to quickly figure out what’s causing issues with a piece of software. ObjectRocket can help figure out how to get to the files needed and configure them for input.
Data in log files or other formats isn’t always organized in the way businesses need. Sometimes values need to be translated for better understanding. Dates may need to be added to different fields. Organizations may want to add their own custom IDs to different fields for help with other processes.
Elaticsearch adds and removes features when they release different versions of the software. A feature that was recently removed was the ability to give documents types within an index. It’s no longer possible to identify documents as a user review in one instance and a product in another. Businesses that previously relied on this as a way of organizing data could find themselves stuck after an upgrade.
That means developers who spent hours learning one version of Elasticsearch can find themselves back at square one in many instances. ObjectRocket engineers stay up to date on these changes. This puts them in position to quickly bring IT personnel up to speed and be on-hand to assist in making any needed upgrades.
Elastic offers a visualization tool for Elasticsearch called Kibana. It takes in data from different Elasticsearch documents and turns them into visuals like charts, graphs, coordinates, maps, regions, and tag clouds.
Developers need to know how to read different documents gathered from different Beats, pinpoint needed fields, and work with Elasticsearch functions to translate information into the format they need. That can be a lot if a developers also trying to adjust to new changes in Elasticsearch.
ObjectRocket can fill the knowledge gap and get visualization solutions off the ground. Companies get to see physical representations of the information they’ve gathered from different business processes. It makes it easier to break things down for less technically inclined senior executives for presentations or pitches for making changes to different departments.
The technicians at ObjectRocket understand the ins and outs of working with Kibana and adapting it to different business needs. The company provides two Kibana nodes with each of their Elasticsearch plans.
Using Elasticsearch to its Full Potential
Many different open source tools can be used with Elasticsearch to provide the results users are looking for. Trying to figure out the best resource can be daunting for those new to Elasticsearch due to constant upgrades and modifications. It can be difficult keeping up with new additions and depreciated features without a subject matter expert available.
That’s where ObjectRocket steps in. The company keeps experts on staff who track the different changes made to Elasticsearch. That allows them to advise businesses on the best practices to use when working with this engine.
A tool like Elasticsearch can help transform business processes and allow them to gain better insight into their infrastructure. Learning how to use it properly or transitioning from one version to the next can be difficult for developers.
ObjectRocket can save companies hours of training time by being on-hand to aid in using Elasticsearch effectively. The company makes sure its employees keep up with changes in each version. They can also help build customized solutions for any files or processes distinct to the company. These processes continue to function effectively once the ObjectRocket team puts them into place.
The company also assists in building solutions to scale for MongoDB and Redis technologies. They offer a free 30-day pilot to businesses offering space to build out solutions for all three. Businesses also receive access to ObjectRocket 24/7 customer service assistance.