My main use case for Logz.io is to better understand the logs that we have, providing smarter observability. We generally use the Elastic Stack, and Logz.io integrates very well with it, and they even have their own observability platform; so log management and observability is mainly what I use it for day-to-day. A specific example of how I use Logz.io for log management or observability involves our observability needs, where it helps us to trace the logs very effectively. It offers an out-of-the-box experience that is very easy to configure, allowing the team to debug issues in their applications easily, see how the data or the API call flows from one end to another, and identify bottlenecks in the application. On the log management front, it simplifies log management very well, especially with the AI capabilities it comes with out-of-the-box, analyzing the logs and mainly helping us in optimizing the cost of how we store the logs. Recent AI integrations in Logz.io have really changed the game here because they provide very specific, actionable insights, saving our team from spending time digging through the logs, which can consist of millions and millions of lines. The AI agent does that work, unblocking our team so we just interact with the agent, ask it questions, and get more insights about the logs, helping us reduce our downtimes and increasing uptime, service availability, and overall performance.
We have been using Logz.io for more than one year. Our main use case for Logz.io is centralized log management and observability. We collect logs from multiple applications and infrastructure components, which allows our team to troubleshoot issues quickly. A recent example involved an API that failed in our production environment. We have multiple Java services running and communicating with each other, and users were reporting transaction failures. Using Logz.io, we had all the logs centralized, so our developers quickly identified the database connection pool issue and fixed it without delay. This helped in finding the root cause very significantly. Beyond troubleshooting, we also use Logz.io for proactive monitoring, alerting, and security investigation. It has become one of our primary tools that our operation teams rely on daily.
Senior Manager of Operations at a comms service provider with 10,001+ employees
Real User
Dec 12, 2023
We have 1500 servers and 600 applications. They all use Logz.io. Most of our apps have a seven-day retention. We use the product for application health and security compliance. After seven days, it goes to the archive so we can recall if we somehow had a security incident. It’s our only logging solution.
Our primary use case is to monitor the live game observability. When our game is live, we can see how the servers are performing and how players are connecting around the world. Generally, we just monitor everything to make sure the stability is running smoothly. The secondary use of it is when we have things we want to dig deeper into, then we have a backup of the logging system. We can jump from a point in the metrics of the observability to a point in logging in which it happened, then observe what the server saw at that time in order to diagnose and fix whatever the issue might be.
Production Engineer at a healthcare company with 51-200 employees
Real User
Apr 18, 2021
We have a product that our customers are using on their servers, and we stream all the logs from our services that are on those servers to Logz.io. We do analysis of the logs and we also have alerts if we don't have enough logs or if a certain log is not arriving and then we know that there's a problem with the server.
AWS Technology Lead at a tech services company with 1,001-5,000 employees
Real User
Apr 12, 2021
One of our customers uses it as a central logs aggregation point. We forward over logs from our customer environment in AWS to Logz.io. We use it to carry out dashboarding and analytics as well as for carrying out some alarming for certain scenarios and events. Essentially, it is a centralized log platform for a customer solution. We use Logz.io for cloud monitoring. I predominantly work in the cloud. That is all I have worked in over the last 10 years or so.
Logz.io provides a robust platform designed to streamline log monitoring, offering features like real-time dashboards and AI Insights. It ensures efficient management of environments such as Kubernetes, enhancing operational effectiveness and cost management.Logz.io is built on an open-source foundation, facilitating quick setup and adaptability for users. Its real-time dashboards are accessible across multiple sub-accounts, allowing seamless scaling and integration into existing services....
My main use case for Logz.io is to better understand the logs that we have, providing smarter observability. We generally use the Elastic Stack, and Logz.io integrates very well with it, and they even have their own observability platform; so log management and observability is mainly what I use it for day-to-day. A specific example of how I use Logz.io for log management or observability involves our observability needs, where it helps us to trace the logs very effectively. It offers an out-of-the-box experience that is very easy to configure, allowing the team to debug issues in their applications easily, see how the data or the API call flows from one end to another, and identify bottlenecks in the application. On the log management front, it simplifies log management very well, especially with the AI capabilities it comes with out-of-the-box, analyzing the logs and mainly helping us in optimizing the cost of how we store the logs. Recent AI integrations in Logz.io have really changed the game here because they provide very specific, actionable insights, saving our team from spending time digging through the logs, which can consist of millions and millions of lines. The AI agent does that work, unblocking our team so we just interact with the agent, ask it questions, and get more insights about the logs, helping us reduce our downtimes and increasing uptime, service availability, and overall performance.
We have been using Logz.io for more than one year. Our main use case for Logz.io is centralized log management and observability. We collect logs from multiple applications and infrastructure components, which allows our team to troubleshoot issues quickly. A recent example involved an API that failed in our production environment. We have multiple Java services running and communicating with each other, and users were reporting transaction failures. Using Logz.io, we had all the logs centralized, so our developers quickly identified the database connection pool issue and fixed it without delay. This helped in finding the root cause very significantly. Beyond troubleshooting, we also use Logz.io for proactive monitoring, alerting, and security investigation. It has become one of our primary tools that our operation teams rely on daily.
We have 1500 servers and 600 applications. They all use Logz.io. Most of our apps have a seven-day retention. We use the product for application health and security compliance. After seven days, it goes to the archive so we can recall if we somehow had a security incident. It’s our only logging solution.
The solution was used for log management.
The tool helped us to make logs and dashboards for microservices. It also helped us to monitor the application.
We use the tool to track the dev and production environment.
We use the product for log collection and monitoring.
Our primary use case is to monitor the live game observability. When our game is live, we can see how the servers are performing and how players are connecting around the world. Generally, we just monitor everything to make sure the stability is running smoothly. The secondary use of it is when we have things we want to dig deeper into, then we have a backup of the logging system. We can jump from a point in the metrics of the observability to a point in logging in which it happened, then observe what the server saw at that time in order to diagnose and fix whatever the issue might be.
We have a product that our customers are using on their servers, and we stream all the logs from our services that are on those servers to Logz.io. We do analysis of the logs and we also have alerts if we don't have enough logs or if a certain log is not arriving and then we know that there's a problem with the server.
One of our customers uses it as a central logs aggregation point. We forward over logs from our customer environment in AWS to Logz.io. We use it to carry out dashboarding and analytics as well as for carrying out some alarming for certain scenarios and events. Essentially, it is a centralized log platform for a customer solution. We use Logz.io for cloud monitoring. I predominantly work in the cloud. That is all I have worked in over the last 10 years or so.