Graylogis a leading centralized log management solution built to open standards for capturing, storing, and enabling real-time analysis of terabytes of machine data. Tens of thousands of IT professionals rely on Graylog’s scalability, comprehensive access to complete data, and exceptional user experience to solve security, compliance, operational, and DevOps issues every day.Purpose-built for modern log analytics, Graylog removes complexity from data exploration, compliance audits, and threat hunting so you can quickly and easily find meaning in data and take action faster. Graylog is fully multi-tenant, includes multi-threaded Elasticsearch, and is easily integrated with other components in your tech stack -even other log management solutions -to meet all yourorganization's log management needs.
Graylog Use Cases
The main advantage of Graylog is that it provides a perfect single instance of log collection for the whole system. This comes in handy if the system infrastructure is large and complex. It could be distributed around multiple places, and not all team members could have immediate access to all its components. We tackle these issues and ensure our incident response time is rapid.
We use Graylog both for the applications under development and the ones already released publicly. In both cases, some modes of Graylog application are unique, while some intersect.
Advantages of Graylog
There are a few advantages of Graylog we have noticed so far, and these are what make the tool perfectly fit into our workflow and delivery.
1.Graylog is a free, open-source software.
2.Its trigger actions or notifications immediately inform us when something needs attention, so we constantly keep abreast of the system performance.
3.With error stack traces received from Graylog, engineers understand the context of any issues in the source code. This saves time and effort for debugging/troubleshooting and bug fixing.
4.The tool has a powerful search syntax, so it is easy to find exactly what you are looking for, even if you have terabytes of log data. The search queries could be saved.
5.Graylog offers archiving functionality, so everything older than 30 days could be stored on slow storage and re-imported into Graylog when such a need appears (for example, when the dev team needs to investigate a certain event from the past).
6.Python applications could be easily connected with Graylog as there is an out-of-box library for this.
A Short History
The Graylog project was started by Lennart Koopmann in 2009. When he needed log management, their product was so expensive that he decided to write a log management system himself. Now you might call this a bit over-optimisticoptimistic but the situation was hopeless: there was basically no other product on the market and especially no open-source alternatives.
Graylognodes should have a focus on CPU power. These also serve the user interface to the browser.
Elasticsearch nodes should have as much RAM as possible and the fastest disks you can get MongoDB stores meta information and configuration data and doesn’t need many resources.Graylog server stands in the middle and works on elasticsearch's shortcomings for daily management. It creates an abstraction layer to facilitate data access.
How It Works?
1.ElasticSearch: ElasticSearch is useful for storing logs and searching text.
2.MongoDB: MongoDB is useful for Metadata Management. 3.Graylog: Graylogcan help you to better understand the use made within your applications, improve their security, and reduce costs.
4. Kibana: Kibana provides the interface shape and visual.
Closed search tools often act as black boxes with how your data is sorted. This not only restricts what you can do with your data but makes you dependent on your vendor for search solutions. With Elasticsearch, this is all transparent and customizable. Many core functions rely on Elasticsearch to work, so unfortunately there is no easy alternative to using Elasticsearch as a data search tool at this time.