Feb 2, 2023
Managing large datasets is a crucial challenge faced by many organizations today. With the increasing generation of data from business transactions, audit logs, and system logs, companies are struggling to keep up with the sheer volume of information they need to process. However, this does not mean that managing large datasets is an impossible task. With the right tools and techniques, companies can harness the power of their data to drive success, improve observability, and reduce overall risk.
One solution to the challenges posed by large datasets is using NoSQL databases and ecosystems based on them. Our experts have gained experience in designing systems to manage petabyte-sized databases, ensuring that they have the know-how to handle business requirements related to business cache solutions, audit information management, and ETL tools. Utilizing the Elasticsearch ecosystem, we have successfully solved the issues of handling heterogeneous data and implemented solutions for audit log information processing, network traffic analysis, and infrastructure log analysis. The use of observability has shown to reduce incidents by 60% and improve application and service resilience by 61%. Additionally, security measures have reduced overall risk by 60% by decreasing the impact of security threats by 69%. The Elastic Platform and Cloud have also driven success and profitability by reducing costs through tool consolidation by 68% and simplifying solution management by 67%.
In order to get visibility, it becomes necessary for companies to build a primary datastore, which contains the aggregated business information from existing systems. Our solution provides a suitable approach for building business cache solutions, which is excellent for both e-commerce and internal applications. Using this technique, frontend applications can be independent of backend systems and only based on the business data cache.
The Elasticsearch ecosystem also contains a machine learning component that can be used to find anomalies and outliers, forecast based on trends, and automatically identify areas of interest in the data. This component can only be done with in-depth technical knowledge and the proper configuration and tuning, and the web-based graphical user interface provides data analysis and query features.
Also it is important to mention that business logging and data collection play a crucial role in monitoring and aggregating an organization's internal parameters. A systematic approach is recommended when conducting business logging and data analysis, including conducting a thorough assessment of available metrics, determining standard parameters for business event logging, and creating a clear and intuitive dashboard interface for the KPIs. By following this approach, organizations can improve their data analysis and decision-making capabilities.
In conclusion, managing large datasets is a challenge faced by many organizations, but with the right tools and techniques, it is possible to harness the power of data to drive success and improve performance. The use of NoSQL databases, observability, security measures, and machine learning components can provide effective solutions to the challenges posed by large datasets.
Possible use cases for a unified monitoring system with a common schema and complete audit log:
Compliance Monitoring: The system can be used to monitor various applications and infrastructure components for compliance with industry regulations. The audit log feature can be used to track changes and ensure that all actions meet regulatory requirements.
IT Operations: The unified monitoring system can be used to track the performance and availability of applications, servers, and other infrastructure components. The common schema allows for easy comparison and analysis of data from multiple sources.
Security Monitoring: The system can be used to detect and respond to security incidents by monitoring network traffic, logs, and other security-related data. The audit log feature can be used to investigate the root cause of incidents and track the actions taken to mitigate them.
DevOps: The unified monitoring system can be used by DevOps teams to monitor the performance and availability of applications and infrastructure components during the development, testing, and deployment phases. The common schema allows for easy integration with continuous integration/continuous delivery (CI/CD) systems.
Business Monitoring: The system can be used to monitor key business metrics such as website traffic, user engagement, and sales. The common schema allows for easy integration with business intelligence tools for data analysis and reporting.
Infrastructure Monitoring: The system can be used to monitor the performance and availability of data centers, servers, and other infrastructure components. The common schema allows for easy comparison and analysis of data from multiple sources.
Cloud Monitoring: The system can be used to monitor the performance and availability of cloud-based infrastructure and applications. The common schema allows for easy comparison and analysis of data from multiple cloud providers.
Application Monitoring: The system can be used to monitor the performance and availability of individual applications, including web, mobile, and desktop applications. The common schema allows for easy comparison and analysis of data from multiple applications.
These are just a few examples of the many possible use cases for a unified monitoring system with a common schema and complete audit log. The system can be customized and configured to meet the specific needs of different organizations and industries.