Share your experience using Anodot

We use Coralogix to analyze our log metrics. We were looking for an enhanced tool to help us secure our real-time data.

We have integrated Coralogix with Slack and other tools, which has helped us receive real-time alerts. We don't have to constantly monitor the tool because it generates alerts and pushes them to us, providing notifications on Slack. This enhancement has strengthened our security, fulfilling our need when searching for such a tool. 

Numerous data monitoring tools are available, but Coralogix somehow fine-tunes our policies and effectively supports our teams. This SaaS platform utilizes machine learning for behavioral analysis of logs, yielding the results we need. For instance, there was a scenario where we received extension logs that were difficult to interpret. However, we obtained the analysis with the help of the product.

Almost all the features we currently use in our product subscription are important to us. Regarding alerting or incident management, incident alert mapping, and suppression rules, we utilize almost all the features available on Coralogix. Additionally, we are sending all the logs, such as app logs, EPC flow logs, etcetera.

Nowadays, tools are often divided into modules. It would be helpful if Coralogix could integrate the main modules that any organization requires into a single subscription. It would streamline the process for organizations like ours.

Merging some of the modules into a single subscription would be beneficial. Nowadays, modules are often separated, so if an organization needs additional modules after subscribing to one, they may have to purchase another subscription. Combining the availability module with tracing metrics or other relevant modules would be beneficial.

I rate the platform's stability a nine out of ten.

I rate the platform's scalability an eight.

We did contact the technical support team when we encountered a deployment issue with Cloudflare. They assisted us promptly and provided helpful answers within the expected time frame.

Before adopting Coralogix, we relied on open-source solutions, but they needed to meet our needs effectively. It led us to explore and eventually invest in a commercial product.

The platform has a reasonable cost. I rate the pricing a three out of ten.

We also evaluated Palo Alto and other Palo Alto products as potential solutions. We opted for Coralogix over Palo Alto because its subscription plan offered better visibility and more features.

The alerting feature in Coralogix, integrated with Slack, has helped your team respond to incidents more quickly and effectively. We haven't experienced any incidents since implementation. Still, during the POC phase, the alerting feature proved to be prompt and reliable, assisting your team in promptly addressing potential issues.

It provides visualization tools that facilitate data analysis. These tools are available directly on the dashboard.

I recommend analyzing their organization's use case and scenario for new users. They should compare it with other tools to see if it suits their needs. If they find it suitable, then they should proceed with it. However, they should be prepared for the possibility that the tool may only suit some organizations. In our case, it worked well in pricing, scenario, and overall performance, so we opted to use it.


I rate it a nine out of ten.

In my university, we used Weka. Weka was used in marketing by my professor, I was preparing a presentation for PhD proposals specifically on energy consumption and renewable resource utilization. So, I needed data mining tools.

Weka's is fine for basic results, no big issues there. 

But if you need visualizations, it's not the best choice. For someone who just needs analysis, Weka serves the purpose. 

But nowadays, good visuals are crucial for presenting findings and telling a story. In my practical experience at the university, when people need quick results with strong visualizations, I don't recommend Weka.

I haven't found it particularly useful. It lacks state-of-the-art algorithms and impressive outcomes. While it might offer insights for basic warehouse tasks, it falls short of deeper understanding and results. 

Moreover, a new user interface would be great, especially for beginners. Something that guides them through the available tools and helps them achieve their goals. I haven't seen anything like that myself, though maybe it's there and I missed it. 

I worked with Weka for about a year and a half.

It is a stable product.

It is very easy to scale. I would rate the scalability a seven out of ten. 

My primary interest lies in energy analytics, optimization, and related fields.

Unfortunately, I couldn't complete the project due to work commitments, but I realized KNIME would have been far better suited for such analysis. For data mining, I had two main options: Python libraries and KNIME. KNIME is a bit expensive, requiring membership, so I opted for Python's ease of use.

Python libraries offer free access and flexibility for various data mining tasks. Python is better than some of the state-of-the-art software.

Weka's ease of use is around seven out of ten. Anyone can pick it up. But the results could be improved, especially visualizations.

We used it offline, directly on the software.

The deployment is in between. Not super fast, but I haven't used other software for comparison. 

Python libraries seem quicker at giving results, but Weka's not terribly slow for backups. It took a good three hours, but not excessively long.

Weka is free and open-source software. That is why I used it over KNIME.

I recommend it. It's been around in the industry for a while, and I consider it one of the best, except for the visualization issue. It does not have good user-friendly graphics. It does not offer good visualization or presentation. Otherwise, it's very viable.

Overall, I would rate the solution a seven out of ten.