Coralogix

Coralogix works as a SIEM solution with an intuitive interface and effortless implementation, thanks to hundreds of pre-built integrations. It integrates well with various tools, making it efficient. Overall, it's an affordable option that simplifies security data management while offering powerful features and excellent support. Data extraction is limited to a single format, which could be improved. Coralogix tackles key security and observability challenges by reducing data processing costs and alert fatigue through automated log parsing and machine learning-driven alerts. It also provides a unified platform for logs, metrics, and security data with complete visibility. It helps us streamline data management, improve security outcomes, and maximize efficiency across the organization.

The Coralogix user interface is pleasant and intuitive. I really like the AI (LLM) assistance for Dataprime queries, which simplifies creating custom dashboards. However, sometimes they make backend changes to the portal without giving customers advance notice, which can be annoying. Coralogix allows us to manage and analyze vast amounts of logs and security events in real-time without feeling overwhelmed. Its smart alerting cuts down on unnecessary noise, and the dashboards make investigations easier. Overall, it helps us detect and respond to issues much more quickly.

Coralogix has enabled us to keep observability costs in check while still maintaining deep visibility into our distributed systems. As of now, I haven't noticed any APM monitoring features for our services. Overall, my experience with Coralogix has been very positive. The product is continuously improving with meaningful feature updates, demonstrating strong customer feedback and a clear product direction. It also aids in end-to-end correlation.

Coralogix provides an exceptionally rapid and user-friendly platform for managing logs, metrics, and traces. We ingest around 500 GB of logs daily from over 200 microservices on AWS EKS, and their real-time indexing and alerting engine detects anomalies in less than 5 seconds. Their ML-driven anomaly detection flagged two production incidents last quarter before our clients even noticed anything wrong. The TCO Optimizer lets us tier older logs into archival storage while keeping them searchable, cutting our observability costs by more than 30% in six months. Integration with AWS CloudWatch, Kubernetes, Jenkins, and Slack was smooth, and dashboards are fully customizable with drill-down filters. The learning curve for advanced features—like custom parsing pipelines, data enrichment rules, and the REST API—can be steep. Documentation is decent for basic use cases but lacks comprehensive end-to-end examples for non-standard workflows (e.g., parsing syslog from third-party firewalls). The mobile app is useful for acknowledging alerts on the go but doesn't support building or editing dashboards remotely. We use Coralogix to consolidate logs, metrics, and traces in one place. It has helped us slash logging costs by over 40%, improved our MTTR with real-time alerts and correlation, and enhanced cross-team collaboration through granular access controls. Once properly configured, the platform is stable, scalable, and very developer-friendly.

The pricing is very reasonable and support is generally accessible, which is handy since you might need them often. However, the platform is quite buggy, with features and releases that feel incomplete; each upgrade feels like beta testing their code, and it often fails, forcing us to roll back. It's nowhere near as intuitive or user-friendly as other observability platforms. We currently send logs, traces, metrics, and profiling data to Coralogix.

Coralogix delivers excellent monitoring and alerting. Its Slack and PagerDuty integrations ensure we're always aware of critical issues. The standout feature is the quick and responsive chat support from the Coralogix team—they resolve problems almost immediately. 1. At present, bulk editing of alerts is tricky (like adding or removing a label across multiple alerts at once). A feature like that would make managing large numbers of alerts far more efficient. 2. The page sometimes takes a while to reload, looking like it's hung. 3. The Alerts section could use more capabilities. We use Coralogix to monitor databases, Kafka, cache performance, and API errors across our services. It has boosted real-time visibility, cut down incident resolution time, and enabled proactive anomaly detection. The dashboards provide actionable insights, and the alerting system has made our operations far more reliable.

I really appreciate how Coralogix allows us to correlate logs, metrics, and traces in a single interface, which greatly facilitates debugging. It also saves time by eliminating the need to switch between multiple tools. The alerting is flexible and dependable, notifying us at the right moments. Search and filtering are robust as well. Setting it up was quick and effortless, which was a definite plus for our team. However, when dealing with high volumes of logs, searches can occasionally be a bit slow, especially during busy periods. I use Coralogix to alert, monitor, and trace our production services, helping with debugging and resource usage tracking. Its centralized approach to logs, metrics, and traces reduces tool switching and saves time. The alerts are trustworthy, and the search/filter functions are powerful.

I've been using Coralogix for half a year now, and we've integrated RUM, user sessions, and web vitals into our multi-page React application. RUM has given us deep insights into real-time user behavior and experience, and it's definitely my favorite feature. So far, I haven't encountered any problems with Coralogix; it even has features I didn't realize I needed. We have a long onboarding flow that spans over 10 screens with many logic branches and conditions, and we struggled to identify where and why users were dropping off—whether it was a technical glitch, UX problem, or another cause. After incorporating Coralogix RUM, we can now watch actual video sessions of users interacting with our app. Through this, we've uncovered multiple UX issues, a few implementation bugs, and some production defects. We're also leveraging these insights to speed up our application.

Coralogix was a pleasure to work with; finding the relevant logs was straightforward with simple queries, and it also supported PagerDuty integration. Whenever we ran into problems, their support was easy to reach and responsive. Implementation was quick, and I used it often to debug live issues or PD alerts. Occasionally, it would capture duplicate logs and consume double tokens for certain services, which we couldn't pinpoint the cause of, but aside from that, everything else was fine. It offers a centralized logging system that simplifies debugging across many microservices, and with PagerDuty support, we get alerts immediately when something goes wrong. Without it, we'd have to manually access logs in k8s pods and set up another system to store and centralize them.

Coralogix stands out for its helpful integrations and the TCO optimizer, which is great for managing costs at the subsystem level and improving unit efficiency. It's also very useful for keeping an eye on our metrics, which really aids our on-call crew. Setting it up for new clusters is a breeze, making it easy to document our various EKS configurations. The ability to hook it up with AWS CloudTrail and send alerts via mail or PagerDuty is a big win. However, there are times when the website doesn't load and I end up waiting around. Also, the Metric Explorer can crash when there's a ton of data to display. I rely on Coralogix for log monitoring, alerting, and tracing, which boosts developer productivity and makes our on-call team more efficient. It also helps with cost optimization thanks to the TCO optimizer and integrates smoothly.