What’s new in Elasticsearch-7.7.0 ?
This year Elastic NV released a stable version of ElasticSearch-7.7.0, which is based on Leucine 8.5.1. They have added several key features that will boost your logging, mapping, searching, scripting, and more. If you are planning to upgrade your existing ES service system, have a look at this article.
New to Elasticsearch?
Elasticsearch is a real-time, distributed storage, search, and analytics engine. It has got many applications, but one context where it excels is indexing streams of semi-structured data, such as logs or decoded network packets.
Some of the key features are:
1. Asynchronous search.
We are all experienced with how putting complex queries on a vast amount of data leads you to a heap crash.
But now with the release of Elastisearch 7.7.0, asynchronous search makes long-running queries viable and reliable. Async Search allows users to run long-running queries in the background, track query progress, and obtain partial results as they are available. It enables users to search on large data with great ease as well as no risks of timeout.
2. Protect your Keystore.
As we all know that privacy is one factor that no company will compromise about, Elasticsearch is constantly coming up with improvised security futures. Initially, it provided sensitive cluster settings and Keystores to prevent unwanted access to your data. Now, Elasticsearch-7.7.0 provides an extra layer of protection to protect your Keystore. The Keystore can optionally be password protected. If you’re looking for additional tips on how to secure your cluster, then check out this blog on how to prevent an Elasticsearch server breach.
3. Reduced heap consumption.
Heap consumption is always been a challenging task for developers. Excessive heap consumption can lead to out of memory error, degrading the performance, etc. Although Elasticsearch was using an off-heap/on-disk column store to reduce heap consumption, alongside it was allowing an index to be “frozen”. Nevertheless, some security and observational cases require the use of large stack sizes in clusters, given the amount and retention of data.
With the release of Elasticsearch-7.7.0, they have reduced heap memory consumption for these time-series use cases by moving the terms index of the _id off-heap. While having the terms index of _id on-heap was useful when indexing with explicit IDs.
4. Painless Lab.
In 2016, Elasticsearch introduced Painless — a simple, fast, and secure scripting language designed specifically for use with Elasticsearch. It was a huge plus for the community. With the release of Elasticsearch-7.7.0, they added the beta availability of the new Painless Lab (available in the Dev Tools section of Kibana).
5. Alerting.
Elasticsearch has announced a new alerting framework that delivers a first-class alerting experience natively within the SIEM, Uptime, APM, and Metrics applications as part of the Kibana 7.7.0 release.
So far, developers are liking this feature the most.
Other than major upgrades, there are also changes in Elasticsearch 7.7.0 that have to consider if you are planning to migrate. For more detailed changes, please visit breaking changes in ES 7.7.
The richer your data, the better the story it can tell for observability, security, or any other use case.
