Elastic Observability Reviews & Product Details

Real time Monitoring. Detailed insights, logs, and metrics, making it easier to pinpoint and resolve issues, reducing downtime.

Centralize data from various sources, such as logs, metrics, and traces, into a single platform, making it easier to correlate information.

Historical data to identify trends, plan capacity, and make data-driven decisions for optimization and cost-efficiency.

Easy to integrate. Review collected by and hosted on G2.com.

Teams need training to maximize the benefits of observability tools, and finding individuals with expertise in these tools are challenging. Review collected by and hosted on G2.com.

there are so many features, unfortunately it is overkill. You need to tune your solution for your own needs. Anyone on the IT industry, who is looking for a observability tool needs to try it at least once(POC, Testing).

Elastic defined all the standarts on this observability stack. Review collected by and hosted on G2.com.

Overkill for the details, you need to be preciese about the needs. Otherwise you will get lot of information with no result. The latest AI additions are useless, there needs to be some templating to make things simpler.

Ressource consumption is another downside. You need a real cluster with a lot of fast IO disks. Review collected by and hosted on G2.com.

It is a suite of tools and features provided by Elastic that enables organizations to monitor and gain insights into the performance, availability, and health of their applications and infrastructure. Review collected by and hosted on G2.com.

Log generation with APM is difficult. Knowledge of ELK is required. Review collected by and hosted on G2.com.

User-Friendly Interface - It has a very intuitive and user-friendly interface that allows both professionals and novice users to quickly get started with monitoring and analyzing their applications and infrastructure.

Excellent Data Collection - Elastic Observability has an ability to collect and ingest data from a wide array of sources, including logs, metrics, traces, and more which makes adding a new data source and analysing it much easier than other platforms Review collected by and hosted on G2.com.

Cost Factor: For larger companies it becomes a bit cumbersome to set it up and also manage costs since it can be a bit expensive (for big companies) if not optimised well Review collected by and hosted on G2.com.

Best way to analize and store million log traces in graphs. The best big data open source platform Review collected by and hosted on G2.com.

The timestamp fields are very restricted. It should be more open and automatically detecting the needed timestamp Review collected by and hosted on G2.com.

Elastic Observability is a powerful platform for observing transactions & telemetry customer data so that we can correlate issues within a short duration. This also helps us to handle Mean Time To Resolution (MTTR) efficiently, which is crucial for our end users. Along with the internal state of our applications, we can also gain insights into their dependencies & potential vulnerabilities to prevent production failures. Review collected by and hosted on G2.com.

Improvements in the documentation would be helpful while we work with various data connection and visualization requirements. It will also ease the complexities faced during Agent setup for our environment. Elastic Observability is apt for our enterprise needs as it aggregates, correlates and inspects our application's telemetry data to visualize our functionalities. Review collected by and hosted on G2.com.

It allows to search keywords or attributes pushed by fluent D filter in text format and returns JSON documents based on the search keywords and selected time frame. More than going through each Kubernetes log it's easy to search any issue within a few seconds around whole log files. Review collected by and hosted on G2.com.

When we use the elastic search API over HTTP it will take much time to return the JSON response when the log files' weight becomes terabytes. However, it can be avoided using backup and clearing the old logs from the storage. Review collected by and hosted on G2.com.

I like the watchers feature the most. It is very useful in support lifecycle. we create events n our logging and then we once we create the watchers for the given event. the watcher gets alerted. we can also write an action like triggering a slack notification that will alert the monitoring team. this has helped our team in championing the proactive monitoring. Review collected by and hosted on G2.com.

in watchers, the queries are limited unlike the free search/ lucene query. sometimes, its difficult to write a complex query for filtering an event in watcher script. Review collected by and hosted on G2.com.

Reduce Engineers' time when reading the log files related to the Kubernetes cluster with keyword search and query any index keyword within seconds in any timeframe. Review collected by and hosted on G2.com.

With time, the query time will increase due to the heavy logs volume, and elastic search might sometimes hang due to the large volumes of logs data. However,backup old logs and clear would help to keep the elastic search 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.