Where data meets insight:
Data convergence is important in observability because it allows organizations to bring together data from various sources and analyze it in a single place.
This can be especially useful when it comes to understanding the performance and health of your organization’s systems and applications, as it allows for a more comprehensive view of the entire system.
One of the main benefits of data convergence is that it allows organizations to identify patterns and correlations that might not be apparent when looking at data from a single source. By bringing together data from multiple sources, you get a more complete picture of how the systems are functioning and identify potential issues more quickly.
Logiq’s Data convergence offers several advantages, including:
- The elimination of the need to connect different data stores for the same data to be displayed on a dashboard for analytical purposes
- The elimination of the need to maintain separate ETL pipelines for ingested data
- A reduction in maintenance costs as there is only one data store that needs to be managed
- An increased ability to focus on addressing customer problems and solutions rather than solving data problems
- A single source of truth for all applications, eliminating the need for duplication and cleaning of data
A few key useful features of Data convergence include:
- Overcoming the problem of running multiple applications in silos
- Simplified scalability – with a single location for data storage, scaling becomes faster and easier
- Increased security – with fewer routes for unethical sources to access the system, the data becomes more secure and less vulnerable to attacks
- Improved disaster recovery – data can be backed up across multiple geographical locations, and the overhead of backing up multiple data stores is eliminated as all data is located in one place
How it works?
Logiq allows to converge of and analyze any data source, including logs, metrics, events, and traces.
With the use of relational databases and “machine data,” Logiq wants to make it simple for businesses to combine operational intelligence.
Logiq’s main platform for monitoring, processing, and analyzing machine data, can now integrate structured data from traditional relational databases such as PostgreSQL, Redis, SQLite, MySQL, and MongoDB. This serves a variety of purposes, such as tracking events, identifying patterns, and troubleshooting issues.
Our objectives are clear which is to enhance network visibility to increase visibility, which ultimately will improve operational intelligence and better analytics throughout a business.
Logiq has a range of tools and features that make it easy to collect and analyze data from various sources. For instance, the intuitive user interface allows users to perform queries, generate reports, and visualize data in various ways. It also includes integrations with a variety of data sources, such as cloud services, application servers, and databases, making it easy to bring together data from different parts of your organization’s infrastructure.
Additionally, the following are the key convergence characteristics of the Logiq platform:
- Customers do not have to spend time and money monitoring and upgrading hundreds of reportedly ideal solutions because Logiq extends from edge to cloud (both private and public) and supports both monolithic apps and containers. This lessens vendor lock-in and aids in preventing early cloud migrations and inconsistent tools between environments.
- In order to further reduce fragmentation, Logiq uses the same data for a variety of use cases. This saves customers from having to ingest and store the same data in distinct tools several times. This helps to connect data from various sources so that users may see everything in its entirety.
- Furthering the notion of extensibility, logiq offers cloud-to-cloud data transfer. Customers can store enormous volumes of data affordably because of this, which also hinders lock-in.
- Scalability is a strength of Logiq. The capability to digest data in any format and then search it at scale allows ingesting data, executing ETL, and then running quick queries. Customers require authoritative and trustworthy data that enables them to take precise measures when breaches or app outages happen, in addition to quick solutions.
Overall, the observability platform from LOGIQ.AI is a powerful tool for organizations looking to improve the performance and reliability of their systems and applications by converging and analyzing data from any source.