
Overview

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Coralogix is the ultimate observability platform providing engineer teams deep insights with real-time analysis, monitoring, visualization, and alerting with no reliance on storage or indexing.
Using proprietary Streama© technology, easily ingest log, metric, tracing, and security data from any source for a single, aggregated view of system health. Automatically narrow down millions of events to common patterns for deeper insights and faster troubleshooting as data is ingested.
To deliver full observability, machine learning algorithms continuously monitor data patterns and flows between system components and trigger dynamic alerts. Hence, you know when a pattern deviates from the norm without static thresholds or the need for pre-configurations.
Connect any data in any format, and view your insights anywhere, including our purpose-built UI, Kibana, Grafana, SQL clients, Tableau, or using our CLI and full API support. Manage the setup yourself, or schedule a free 1:1 session with one of our experts.
Highlights
- Architecture: Unlike traditional solutions, Coralogix leverages in-stream analytics to investigate your data and provide actionable insights without relying on storage or indexing. Our unique architecture gives users the best of stateless speed and scale with the power and granularity of stateful correlation.
- Scale: Using advanced auto-scaling techniques, Coralogix seamlessly scales up and down to meet the demands of any environment at any scale with little to no changes required. The platform is currently processing 3M+ events per second.
- Cost Optimization: By analyzing data and extracting insights without needing to store or index it, users benefit from complete monitoring, visualization, and alerting capabilities with optimized storage and savings of up to 70%.
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Dimension | Description | Cost/month |
|---|---|---|
5GB per month, 7 days retention | Monthly Usage, Measured Daily: Feel free to reach out for any tailor made plan, we are available 24x7 | $30.00 |
30GB, 14 days retention | Monthly Usage, Measured Daily: Feel free to reach out for any tailor made plan, we are available 24x7 | $100.00 |
100GB, 14 days retention | Monthly Usage, Measured Daily: Feel free to reach out for any tailor made plan, we are available 24x7 | $250.00 |
150GB, 14 days retention | Monthly Usage, Measured Daily: Feel free to reach out for any tailor made plan, we are available 24x7 | $420.00 |
300GB, 14 days retention | Monthly Usage, Measured Daily: Feel free to reach out for any tailor made plan, we are available 24x7 | $750.00 |
600GB, 14 days retention | Monthly Usage, Measured Daily: Feel free to reach out for any tailor made plan, we are available 24x7 | $1,300.00 |
5GB, 30 days retention | Monthly Usage, Measured Daily: Feel free to reach out for any tailor made plan, we are available 24x7 | $60.00 |
30GB, 30 days retention | Monthly Usage, Measured Daily: Feel free to reach out for any tailor made plan, we are available 24x7 | $120.00 |
100GB, 30 days retention | Monthly Usage, Measured Daily: Feel free to reach out for any tailor made plan, we are available 24x7 | $280.00 |
150GB, 30 days retention | Monthly Usage, Measured Daily:Feel free to reach out for any tailor made plan, we are available 24x7 | $475.00 |
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Customer reviews
Centralized monitoring has transformed telecom troubleshooting and now reduces downtime proactively
What is our primary use case?
In my organization, particularly in Ericsson's telecom BSS domain, the primary use case of Coralogix is centralized log management and real-time monitoring of telecom applications, such as the BSS software products and infrastructure. We have multiple SDP and AIR components in our telecom stack, including application servers, network elements, microservices, and APIs. Coralogix acts as a single platform where all logs are aggregated, which makes troubleshooting much faster compared to using different systems. The platform also helps with monitoring live traffic and system behavior. We have configured alerts for critical scenarios such as service downtime, API failures, error rates, and spikes.
Using Coralogix has significantly improved the efficiency and structure of my daily work, especially in monitoring and troubleshooting. Previously, we relied on manual checks and customer complaints to identify different issues. Now, with real-time alerts in Coralogix, we get notified immediately when something goes wrong, such as API failures or abnormal error spikes. The approach has shifted from reactive troubleshooting to proactive monitoring. Previously, we had to log into multiple servers and manually check logs, which was time-consuming. Now, everything is centralized in Coralogix, and with powerful search and filtering, we can quickly pinpoint issues within minutes instead of hours.
One recent incident involved a production issue where one of our SDP application services started showing intermittent API failures during peak traffic hours. Subscribers in Singapore were experiencing delayed responses, and some transactions were failing. Initially, it was difficult to identify the root cause because multiple microservices and backend systems were involved. Using Coralogix, we were able to quickly narrow down the issue through real-time log monitoring, centralized log correlation, advanced filtering and search, and alerting dashboards. We observed through Coralogix dashboards that error rates suddenly increased for a particular service after a deployment. By filtering logs based on transaction IDs and timestamps, we traced the issue to a backend service timeout caused by a misconfigured connection pool. The biggest advantage was that we did not need to manually log into multiple servers to investigate. Everything was visible from a single platform, which saved considerable troubleshooting time. Because of Coralogix alerts, the operations team was informed immediately, and we resolved the issue much faster than our general earlier processes, significantly reducing troubleshooting time and providing faster root cause identification.
What is most valuable?
In my experience, a few features of Coralogix stand out and make it very effective for day-to-day operations. First, the centralized log management makes all logs from different systems, applications, servers, and microservices available in one place. This eliminates the need to check multiple servers and makes troubleshooting much faster. Second, the powerful search capability is very strong. We can filter logs based on time range, severity, transaction IDs, or specific keywords, which helps quickly identify issues in complex telecom environments such as our BSS products. Third, the real-time alerting allows us to configure alerts for critical events such as error spikes, service failures, and latency issues. This helps in immediate detection and faster response, reducing downtime.
Among all the features, the one that makes the biggest difference for our team is centralized log management with powerful search capability in Coralogix. In our environment, multiple systems are involved, including application servers, APIs, backend systems, and network components, all in production with customers and subscribers using them. Previously, troubleshooting meant logging into those servers and manually checking each log, which was time-consuming and inefficient. With Coralogix, all logs are available in one place. We can quickly search using filters such as transaction ID, particular timestamp, or error code. We can correlate logs across multiple services. This has drastically reduced our mean time to resolution. The real impact is faster issue identification and less manual effort.
What needs improvement?
Coralogix works well for our needs, but there are a few areas where improvements can be made. One area is querying performance for large-scale data sets. When we are dealing with very high log volumes, some complex queries take time to return results. Improving query speed and optimization would enhance the troubleshooting experience. Another point is the learning curve for advanced features. While basic usage is straightforward, advanced querying and dashboard configurations can take time for new users we are onboarding. We have faced this situation in our organization's domain frequently. More simplified UI options or guided templates would help new team members onboard faster. Additionally, dashboard customization flexibility needs improvement. Although dashboards are useful, having more flexibility in customization would make them even more powerful. An important point is cost optimization. Since log volume is high in our environment, better visibility and control over cost optimization would be beneficial.
These are minor improvements overall. Coralogix already provides strong capabilities for centralized logging and monitoring, but enhancing these areas would make it even more efficient for large-scale environments in our telecom servers. Improvements could include query performance, alert noise reduction, and ease of use for advanced features, especially for large-scale environments like ours.
For how long have I used the solution?
I have been using Coralogix for more than four years.
What do I think about the stability of the solution?
In our experience, Coralogix has been quite stable and reliable for our day-to-day operations. We use it continuously for monitoring and troubleshooting, and we have not faced any major stability issues that impacted our work significantly. The platform is generally highly available. Log ingestion and processing are consistent, even during high traffic. Our charging system dashboards and alerts work reliably in real time. There have been occasional minor delays or latency during very high log volume, but nothing critical or long-lasting.
What do I think about the scalability of the solution?
Coralogix has been highly scalable and well-suited for a high-volume environment such as our charging products. As our system usage and log volume increased, Coralogix was able to handle the growth without requiring any major changes from our side. Our systems generate a huge amount of logs, especially during peak hours, and Coralogix has been able to ingest and process the data smoothly without major performance issues. Since it is a managed SaaS platform, scaling is handled by Coralogix itself. We do not need to worry about infrastructure, storage, or cluster management. Even as new services or microservices were added, the platform continued to perform reliably in terms of search, monitoring, and alerting.
How are customer service and support?
Whenever we have raised issues or queries, the support team has generally responded in a timely manner and helped us resolve problems effectively. For most cases, especially critical issues, the response time has been quick, which is important in our charging environment in telecom. The support team has good technical knowledge and is able to understand log-related monitoring issues without much back and forth. During initial setup or when configuring alerts and dashboards, their guidance was useful. The support has been reliable and helpful for our day-to-day needs.
Which solution did I use previously and why did I switch?
Before Coralogix, we were using a combination of traditional logging approaches and tools such as the ELK stack and ElasticSearch specifically. While ELK is powerful, we faced a few challenges in our environment. It had a high maintenance overhead, and managing infrastructure storage and scaling ElasticSearch clusters required significant effort. As log volume increased day by day, query performance and indexing became slower. Compared to modern observability platforms, it had very limited real-time alerting capabilities. It also had operational complexity and required dedicated effort for tuning and upkeep. We switched to Coralogix because of its SaaS model with no need to manage infrastructure, better real-time monitoring and alerting, and faster and more efficient log search with scalability without operational burden. Previously using the ELK stack, we moved to Coralogix due to high maintenance and scalability challenges, choosing it for its SaaS model, better performance, and real-time monitoring capabilities.
How was the initial setup?
Before adopting Coralogix in our organization, our organization evaluated a few other observability and log management tools to find the best fit for our telecom environment. Some options were Splunk, Datadog , and the ELK stack. Tools such as Splunk can become quite expensive with high log volume. Coralogix provided a more cost-effective model for our use cases. In telecom, log ingestion is massive, and Coralogix handled high-volume logs efficiently without requiring us to manage infrastructure. Compared to ELK, Coralogix removed the need for managing cluster storage and scaling.
What about the implementation team?
In our case, the procurement of Coralogix was handled at the organizational or management level. I am not directly involved in the purchasing process. However, it can be purchased either directly from the vendor or through platforms such as the AWS marketplace. From a user perspective, we mainly focus on using the platform for monitoring and troubleshooting rather than the procurement side.
What was our ROI?
We have definitely seen a positive return on investment from using Coralogix, both in terms of time savings and improved system reliability. Regarding mean time to resolution, which I have already discussed, previously one to two hours were required to resolve major issues. Now it takes around ten to twenty minutes, representing approximately a sixty to seventy percent reduction in resolution time. Less downtime means fewer service disruptions, which is very critical in our telecom services. Even a small outage can have significant business impacts. Another point is reduced service downtime for revenue protection. With faster detection and resolution, approximately thirty to forty percent reduction in downtime has been achieved over these years. In one incident involving an API failure during peak hours, Coralogix helped us quickly identify a backend timeout issue. Because we resolved it faster, we avoided prolonged service impact and potential customer complaints. Engineers spend less time manually checking logs across the system, with approximately forty to fifty percent of time saved in troubleshooting activities.
What's my experience with pricing, setup cost, and licensing?
My experience with Coralogix pricing and licensing has been generally positive, especially considering the value it provides in terms of monitoring and troubleshooting. It follows a usage-based pricing model that mainly depends on log volume and data ingestion. This works well for us because it is scalable, and we can adjust based on our needs. Some challenges we faced include the fact that in our environment, log volume is very high, so cost management becomes important, and we need to be mindful about which logs to ingest and retain to avoid unnecessary costs. Sometimes, it requires fine-tuning log levels and retention policies. Overall, the pricing is reasonable for the value it delivers, but it needs proper optimization to be cost-effective at scale.
Which other solutions did I evaluate?
As far as I am aware, our organization's relationship with Coralogix is primarily as a customer using their platform for observability and log management. I am not aware of any additional business relationships such as partnerships, reselling, or strategic collaboration beyond that. My involvement is mainly on the technical and usage side, so procurement or partnership details would be handled by management. We are primarily customers of Coralogix and do not have any additional business relationship beyond that.
What other advice do I have?
While exact numbers can vary across teams, based on our current usage, we have observed clear improvements in a few key areas. I have already discussed mean time to resolution. Previously, one to two hours were easily required to identify and resolve issues. Now, it is twenty to thirty minutes in most cases, representing approximately a sixty to seventy percent reduction in resolution time. The second point is faster issue detection. Previously, issues were often detected after user complaints or manual checks. Now, real-time alerts detect issues within minutes, achieving approximately seventy to eighty percent faster detection. Downtime has also been reduced by thirty to forty percent in service terms. Additionally, team productivity has increased by forty to fifty percent due to less time spent on manual log checking across all servers.
Based on our experience, Coralogix is a powerful tool, but to get the best value out of it, I would suggest a few things. You should always plan your log strategy early and avoid ingesting everything blindly. Define which logs are critical and set proper log levels. This will help with both performance and cost optimization. Second, you need to set up meaningful alerts by configuring them carefully to avoid noise and focus on actionable alerts that really need attention. Too many alerts can reduce effectiveness. Additionally, you should use structured logging. If logs are well-structured in JSON format or with proper fields, searching and analysis become much easier and faster. Finally, build dashboards for key metrics by creating dashboards for important KPIs such as error rates, latency, and service health, which will help in quick monitoring and decision-making. I would rate this product an eight out of ten based on my overall experience.
Log tracing has improved debugging across microservices but the interface still needs refinement
What is our primary use case?
My main use case for Coralogix is to trace logs and debug the telemetry that we have across the microservices. Whenever our microservices get deployed on production or in stage, we emit these logs to Coralogix, and whenever something goes wrong, I go to Coralogix and debug it based on the applications and the services, looking after all the traces to find out what went wrong.
I sometimes also perform log searches based on certain keyword pattern matching with certain logs across different traces. We put that keyword in the complex search, and then it gives us all the logs that are included in it.
There were multiple scenarios where we have different microservices connected to each other, and if we want to know at what place and which microservice is failing and what the issue is, we search based on the request ID and get all the logs from all different microservices, then figure out where it is failing.
What is most valuable?
The best features Coralogix offers include the search feature, and the regex search is quite good. The period, network, and all those filters about why the same logs or trace has been connected across different services and microservices help tremendously.
The AI feature is also quite good for writing down the queries and those things. Coralogix improves the resolution speed because we have these logs integrated with our native AI agents, so it automatically fetches the data from Coralogix, and then we have it on Slack to resolve or identify the issue quite quickly.
Time is being saved in tracing logs or debugging any production issues or incidents.
What needs improvement?
Coralogix can be improved by cleaning up the UI, as it is too cluttered. If the search speed could also be improved, that would be helpful.
I chose seven for my rating because it is good for traces and logs, but I still feel that it can improve its UI and the search feature.
For how long have I used the solution?
I have been using Coralogix for more than two years.
What do I think about the stability of the solution?
Coralogix is quite stable.
What do I think about the scalability of the solution?
Coralogix is quite scalable. It is distributed, so we have never felt any issue with Coralogix's scalability.
How are customer service and support?
Customer support is quite good.
Which solution did I use previously and why did I switch?
Earlier, we were using Sumo Logic, and we migrated from Sumo Logic to Coralogix.
How was the initial setup?
We purchased Coralogix through the AWS Marketplace, but I have less knowledge about the infrastructure and those things. I don't have information about the pricing, setup cost, and licensing, because the infrastructure and those things are handled by a different team.
What was our ROI?
Time is being saved in tracing logs or debugging any production issues or incidents, but I don't have any handy numbers because I am not the right person to look into the infrastructure or the metrics of Coralogix.
What's my experience with pricing, setup cost, and licensing?
I don't have information about the pricing, setup cost, and licensing, because the infrastructure and those things are handled by a different team.
Which other solutions did I evaluate?
I didn't evaluate other options before choosing Coralogix. It was our team who did that.
What other advice do I have?
Others looking into using Coralogix can trust it and can adopt it because it is good enough to use, with costs also being less than competitors. I gave this product a rating of seven.
Which deployment model are you using for this solution?
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Centralized logs have streamlined debugging and alert handling across our cloud applications
What is our primary use case?
My main use case for Coralogix is inspecting the application logs and system logs, such as logs from Kubernetes .
In my day-to-day work with Coralogix , we have some alerts, and when alerts are triggered, we can take a look at any incoming issue from the application. I also use Coralogix for debugging issues in the application by reviewing the Coralogix logs.
What is most valuable?
I find that Coralogix is very useful in our day-to-day work.
The best features that Coralogix offers include the ability to see in one place all the logs related to the application from end-to-end. Having all the logs in one place with Coralogix saves time and makes troubleshooting much easier than previously.
Coralogix has positively impacted my organization by allowing us to save time in troubleshooting problems and in troubleshooting a new feature or new code that we are writing.
What needs improvement?
I see room for improvement in Coralogix regarding the cost, as they can reduce the costs for the license. Because of the cost, we cannot see logs for more than thirty days. The main concern regarding improvements is the cost.
For how long have I used the solution?
I have been using Coralogix for three years.
What do I think about the stability of the solution?
Coralogix is quite stable.
What do I think about the scalability of the solution?
The scalability of Coralogix is great since the infrastructure is sitting on the cloud.
How are customer service and support?
Customer support for Coralogix is great, and it is one of the best supports I have experienced.
Which solution did I use previously and why did I switch?
I previously used an on-premises solution that did not have a solution at all. I was checking the logs from each application and syslog on the var log files, but nothing like what Coralogix offers.
What was our ROI?
I have seen a return on investment as it is time-saving for debugging since this costs a lot over a period of time.
What's my experience with pricing, setup cost, and licensing?
My experience with pricing, setup cost, and licensing is that it is pretty easy and not an issue at all. I did not need to negotiate for the pricing, and the implementation licensing was very easy.
Which other solutions did I evaluate?
Before choosing Coralogix, I evaluated other options including Splunk, but it was very expensive, and I also looked into Sumo Logic.
What other advice do I have?
My advice for others looking into using Coralogix is that I would suggest using Coralogix as it is a great tool that can help your engineers with alerting and allows you to see all the logs in one place, which is beneficial. I rate this product an 8 overall.
Which deployment model are you using for this solution?
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Cost-efficient logging has reduced storage overhead and provides clear metrics visibility
What is our primary use case?
My main use case for Coralogix is a streaming platform where we log data to store in an S3 bucket for streaming purposes. When we require specific data, we store it in an S3 bucket, including S3 replication. This is how we utilize it.
A specific example of how I use Coralogix in my streaming platform is for analyzing data and addressing data fidelity concerns. We have also used AI features for this purpose. For logging aggregation, we also use it on Kubernetes , which is part of our day-to-day work.
What is most valuable?
The best features include processing data in streams and enabling alerting through real-time analytics. I also appreciate the cost-efficient storage with AI-powered insights.
Out of real-time analytics, cost-efficient storage, and AI-powered insights, the most valuable for my team has been the cost-efficient storage. We generally store data on some of my customers' clouds, avoiding expensive storage markups. That is why we use it for cost-cutting storage.
Coralogix has positively impacted my organization as we use S3 buckets for logging purposes. We previously used DataDog and Prometheus for that, but later we switched to Coralogix for log management, tracing, security, and AI features.
What needs improvement?
I believe there is no improvement needed for Coralogix. For our use case, things are working well right now.
For how long have I used the solution?
I have been using Coralogix for around 2.5 years.
What do I think about the stability of the solution?
Coralogix is stable.
What do I think about the scalability of the solution?
The scalability of Coralogix is also working well.
How are customer service and support?
The customer support provided by Coralogix is good.
Which solution did I use previously and why did I switch?
We previously used DataDog and Prometheus for metrics, but we switched to Coralogix because of the clear visibility and the metrics perspective. The readability and usability are very good. Additionally, there were features such as storing data in customer clouds that are better than other logging and metrics platforms.
Before choosing Coralogix, we used DataDog and Prometheus for metrics and switched because there was a clear understanding of metrics and logging with a cost-efficient aspect. We can store data in the customer's cloud without needing separate storage, which allows us to reduce costs. These are the aspects that we appreciate about Coralogix.
What was our ROI?
With Coralogix, we have saved money and time. These are the key benefits we have observed.
What's my experience with pricing, setup cost, and licensing?
My experience with pricing, setup cost, and licensing is that the overall cost is good. The setup is also very understandable and straightforward. Overall, things are working well right now.
What other advice do I have?
The advice I would give to others looking into Coralogix is that it is a simple platform to use. The integration is also very good. Additionally, you can see the logging and metrics clearly. It is simple to use, and there is a cost-efficient aspect to the storage. These are the features that I value in Coralogix. I would rate this product a 9.
Improved observability has enabled faster incident response and clearer service health tracking
What is our primary use case?
My main use case for Coralogix was that we transferred from DataDog because DataDog was expensive at the time, and we wanted something more cost-effective. The VP of R&D thought Coralogix would be a great solution to replace DataDog. We used it for observability, logs of services, traceability of services that reach from certain endpoints, and everything related to metrics. We also used it in the queries and their Grafana managed dashboards, so we could view all of our Kubernetes workloads, whether it was RabbitMQ brokers panels or Kafka. We integrated it with so many things.
A specific example of how I used Coralogix in my daily work is that I opened Coralogix when developers had issues with their services, such as having 500 error codes or 400 error codes. We would observe the logs and see the logs that were transferred to Coralogix for the service, which were enriched with the data of the name of their service, the tags, and many other things that we did with the help of OpenTelemetry agents that transferred the data to Coralogix. We also sent log groups of specific RDSs that we managed via AWS , so it was better for metrics gathering and logs observability.
What is most valuable?
The best features Coralogix offers include its very nice tool and the usage of AI, which was very useful. The AI could describe the log that was received, providing a window that explains what the log actually says, what the issues are, the impact, and many things that help to summarize the log. The console is pretty fine; you can navigate and see many things that you want.
The AI feature impacted my work by helping me to reduce my time wasted on exploring what the error means and going to Google to search for it or maybe going inside the pods of the services to see what the issue actually is. The AI summarizes the data, enriches it, and provides a better view of what I actually need to handle.
Coralogix has positively impacted my organization by handling the responsibility for the developers to track their services and see what is actually going on there in terms of logs of their services, whether it is info, debug, error, or warnings. It gave a better view of things, and you can query against things that you want to see in terms of logs. The Grafana-managed dashboards allow you to actually see the metrics of your specific workloads. I believe it provides better observability and visibility. Coralogix is a nice tool that helps developers, DevOps, and SRE track services and see their health status.
After implementing Coralogix, we noticed improvements such as integrating it with our Squadcast , which is an alerting system that actually alerts when an incident arises. We used the alerting system of Coralogix and explained via PromQL, which is a query language that helped us write alerts based on queries. When we saw a pod's CPU utilization metrics exceed the predefined limit, we wanted to alert our SRE and DevOps team so they can open and see the alert URL and log URL. Via Coralogix, we could examine the logs and see the actual issue. It was very nice to integrate it with Squadcast and have SMS and calls when an alert is received.
This setup helped our team respond to incidents more quickly, and I think we improved our incident response time. The SMS and phone calls are received immediately; once the alert is triggered, it triggers Squadcast, which notifies me with SMS and then calls me.
What needs improvement?
Coralogix can be improved by having better documentation to help new people onboard into this platform and understand the systems, including how they can integrate their cloud provider to better understand how Coralogix and the cloud provider work in sync. If you really want to understand it, I think you need to find someone who has worked with it for at least a couple of years.
There are other improvements needed for Coralogix, such as their Helm charts and Terraform providers. I remember back at that time, the Terraform providers were without any support from the engineering team, and they were outdated and had many bugs.
For how long have I used the solution?
I have been using Coralogix for at least two years.
What other advice do I have?
I do not have any specific advice for others looking into using Coralogix. My overall review rating for Coralogix is eight out of ten.
