Kibana Reviews and Ratings

Use Cases and Deployment Scope

Our organization uses Kibana primarily to visualize and analyze large volumes of logs and performance data generated by our applications and infrastructure.

Kibana is integrated with AWS OpenSearch. We use AWS OpenSearch to store AWS WAF logs. Whenever we identify an issue, we go to the Kibana console and search for various parameters related to our infrastructure that help us in searching the logs quickly and enable us to identify the issues.

Likelihood to Recommend

Kibana is indeed a powerful tool and has many use cases especially in environments that rely heavily on real-time log analysis and visualisation. Kibana’s ability to handle large volumes of log data and present it in an accessible, searchable format is invaluable. We use Kibana to monitor security related issues and it proactively alerts our Slack channels about any anomality or issues.

Use Cases and Deployment Scope

We use Kibana to visualize automated error reports on our website. We are able to find potential consumer issues and investigate.

Likelihood to Recommend

We are able to set alerts whenever a certain number of errors are appearing. These automated alerts allow us to have constant monitoring. Kibana is not very useful for much more edge cases or slow burn cases. These things will often hide under the noise of all the other indicators. Also, we need to find a way to ignore alerts.

Use Cases and Deployment Scope

Kibana is a cornerstone of our observability strategy. We use it for all aspects of our operational workflows, from tailing log files in production to debug events in real-time, to creating beautiful and enlightening dashboards for surfacing key metrics for our leadership team. Kibana helps us both with tracking our "known knowns" and our "unknown unknowns" via its expressive and powerful filters and customizations.

Likelihood to Recommend

Great for teams big and small that want a single pane of glass for understanding their systems, from dev, to staging, to production. Well-suited for teams that need to preserve logs for long-term compliance reasons, and also mine their logs for useful operational insights. Highly recommended as both an open source project and a commercial offering with fantastic paid support.

Use Cases and Deployment Scope

We use Kibana both for monitoring our production environment and debugging. The log parsing and aggregation are extremely helpful when trying to both get an overview and drill down into specific issues.

Likelihood to Recommend

It's well suited to creating dashboards for getting an overview of what is going on with an application.

Use Cases and Deployment Scope

Kibana is the front-end to Elasticsearch. Together they offer a "Google-like" interface for all logs produced by applications, allowing to quickly investigate potential issues and access audit logs. Search is happening in near-real time, which makes the information presented relevant. It offers various filters, as required to quickly churn through the vast amount of logs that a production application may produce. We generally use Kibana/Elasticsearch only for recent logs (e.g., retention period of 30 days) and distribute logs simultaneously to a longer-term storage solution, such as Azure Storage or AWS S3.

Likelihood to Recommend

Kibana (as a front-end to Elasticsearch) is particularly well suite for searching through recent logs, such as the last 30 days.

Elasticsearch is notoriously difficult to operate with large data volumes, which is why it does not serve well as cold / archival storage of logs.