Security, Compliance
and Scale


Reliability is critical for observability and monitoring platforms to ensure the smooth functioning of a system. 

There are several key factors that contribute to the reliability of a platform, including performance and security, scale for ingestion, storage and retrieval capabilities, compute efficiency, and storage scale.

Using object storage for observability data storage can provide several benefits, including:

  • Scalability: Object storage is highly scalable and can handle large amounts of data without the need for manual partitioning or sharding. This makes it well-suited for storing large quantities of observability data.
  • Durability: Object storage is designed to provide high levels of data durability, often providing multiple copies of data across different locations. This ensures that data is not lost in the event of a hardware failure or other issues.
  • Flexibility: Object storage is a flexible data storage solution that can be accessed via various protocols, such as S3, Swift, and NFS. This allows you to use the protocol that is best suited for your use case.
  • Data Governance: Object storage allows for robust data governance, such as data versioning, encryption, access control, and compliance.
  • Accessibility: Object storage allows you to easily access data from anywhere, by providing an API or web interface, which can be useful when working with distributed systems.

The observability platform from LOGIQ.AI is built on a microservices architecture, which means that it is composed of small, independent services that communicate with each other through APIs. This architecture allows for greater flexibility, scalability, and reliability, as each service can be developed, tested, and deployed independently.

The platform also uses an object-storage model, which means that data is stored in “objects” rather than in a traditional file hierarchy. This allows for easier data management and access, as well as better scalability and reliability. The object-storage model is designed to handle large volumes of data and to ensure that data is always available and consistent.

In terms of platform reliability, the observability platform from LOGIQ.AI is designed to be highly available and to withstand failures. It uses redundant systems and automatic failover to ensure that the platform is always up and running. Moreover, our platform is monitored and maintained by a team of experts who work to prevent and resolve issues as they arise.

Performance and security are also crucial factors in the reliability of an observability and monitoring platform. Log management, Log2Metrics, Prometheus monitoring, and Role-based access controls can provide real-time performance metrics and alerts, while also ensuring that the data is protected against unauthorized access.

Scale for ingestion, storage, and retrieval is another important aspect of the reliability of an observability and monitoring platform. Logiq is able to handle large amounts of data and quickly retrieve and analyze it when needed.

Compute and storage scales are important for ensuring that the platform can handle the computational and storage needs of the system. Our platform scales up or down as needed to meet the changing demands of the system, while also providing sufficient storage capacity to handle large amounts of data.

Furthermore, LOGIQ has A Built-in, Powerful, And Flexible Events & Alert Management Engine that aids in the reduction of noise in your alerts. You can now make programmatic rules that can detect critical problems in real time using our easy UI.

With Logiq you may keep logs as long as you want. And use your bucket lifecycle policies to raise the retention period and lower it, if necessary. To meet high governance standards, archive data to colder tiers using your object store vendor’s lifecycle management tools.

Overall, the observability platform from LOGIQ.AI is a reliable and robust solution for businesses looking to improve visibility into the performance and health of their systems and applications.