Reduce the time engineers spend reading log files related to the Kubernetes cluster by using keyword search. Query any indexed keyword within seconds for any timeframe. Review collected by and hosted on G2.com.

Over time, the query time will increase due to the heavy volume of logs, and Elasticsearch might sometimes hang due to the large volumes of log data. However, backing up old logs and clearing them would help to maintain Elasticsearch's health in a good way. Review collected by and hosted on G2.com.

I like three things about Elasticsearch:

1 - Its flexibility

2 - Its reliability

3 - How much the product has evolved over time

I have been using Elasticsearch for some time and even after a few years, I'm still amazed at how flexible and reliable it is. I have been able to use Elasticsearch to ingest millions of events and build queries/dashboards on top of it and every time Elastic has delivered above and beyond. Review collected by and hosted on G2.com.

There is very little I do not like about Elastic. Maybe one thing that could see improvement over time is the Kibana UI. Sometimes is not counter-intuitive how it works, especially if you're trying to build complex visualizations. Review collected by and hosted on G2.com.

1) Flexibility of integration with almost all the tools and components around the globe.

2) Ease of use.

3) Developer friendly API's and Query mechanism.

4) Super quick.

5) Support for Distributed Computing.

6)Very powerful analytics tool called the Kibana which is the 'K' part of the ELK stack. Review collected by and hosted on G2.com.

1) No multi language support for handling request and response. Means, the request and response can be sent andd received in the same language only. No cross language support.

2) Works on near real time. It means there is a lag of atleast 1 sec between the time of data input and the time when the data becomes available for search. Review collected by and hosted on G2.com.

What I like the most is the simplicity of using Elastic Observability Review collected by and hosted on G2.com.

I dislike in "Elastic Observability" is the fact that there is no option to combine the logs with our log files and to see all application info at the same place Review collected by and hosted on G2.com.

I have been impressed by Kibana's flexible layout, which makes it easy to visualize large volumes of data in one place quickly. Kibana has allowed me to put everything I need to see right at my fingertips to make real-time decisions. Review collected by and hosted on G2.com.

It would be great to have more support materials to guide new users in connecting their data and setting up their visualizations. I am intrigued by the machine learning options and would love to understand that more, but I struggle to find suitable materials. Review collected by and hosted on G2.com.

Dashboards and visualization feature in Kibana is really great. There are tons of ways you can visualize and analyse your data. The feature of importing and exporting object helps save time. Review collected by and hosted on G2.com.

It's a bit complex to integrate kibana as application logging tool. There will be many challenges on setting up agents and if the agent faces some issue then that can cause issues in log file rotation.

Data is retained for less number of days and it can become more expensive if you need more data retention period. However, it does offer cold storage. Review collected by and hosted on G2.com.

Kibana along with Elasticsearch is such an useful and great open-source tool. In several projects we depend on ELK stack for monitoring and alters. When it comes to searching for logs and erros this is one of the best solutions out there in the market. Review collected by and hosted on G2.com.

The query language can be tricky. Even setting up certain alters needs a certain level of tool and scripting. With the understanding of its scripting syntax, it can be hard to use this tool. Review collected by and hosted on G2.com.

There are a bunch of things that I like about Kibana:

1. Beautiful visualization: The visualization provided on the interface is a very handy tool during debugging.

2. It also provides an interface to monitor and manage our Elastic cluster

3. We can filter logs on the basis of various parameters. This has come out to be the most important tool in our daily work and especially during incidents. Review collected by and hosted on G2.com.

There is nothing I dislike. It is going great with the application. The details we are provided are very specific and you can also use Search API and python packages to integrate with your scripts. Review collected by and hosted on G2.com.

The Best Part of AWS Elasticsearch is the Managed Integrations and Easy Dashboards for Mostly Used Applications. Review collected by and hosted on G2.com.

There is Still Some Improvements Needed for Source Data For Monitoring, and There Should to Option to Monitor Old Data From SE Buckets. Review collected by and hosted on G2.com.

It has the ability to search with any text from the log records, this helps a lot and saves lot of time. We can filter the log records based on conditions like environment, application, timestamp etc. Review collected by and hosted on G2.com.

There should be a feature to save the current result set of the logs. View surrounding documents has bugs when we try to load more. Review collected by and hosted on G2.com.