Kafka is an open-source distributed streaming platform for high-throughput and fault-tolerant real-time data streaming in large-scale systems. It can integrate with a wide range of data sources and sinks, which include databases, message queues, big data processing frameworks like Apache Spark and Apache Flink, and many more.

Time series data is particularly prevalent, seen across numerous different industries and use cases. It offers significant value to various organizations, highlighting the importance of effectively monitoring and analyzing the data. By analyzing and monitoring time series data you can understand trends, patterns, and anomalies in sequential data collected at many points in time.

If you’re considering OpenSearch for your search and analytics infrastructure, the first question that likely comes to mind is: what will it cost? OpenSearch, the powerful, open-source search engine and analytics platform, provides a highly scalable solution for businesses. However, while the software itself is free to use, there are still costs associated with hosting, maintaining, and scaling OpenSearch clusters.

For organizations, it is crucial to swiftly respond to evolving market dynamics, shifting customer preferences, and emerging operational challenges. This responsiveness is made possible through the use of real-time data streaming technologies, which provide a dynamic and profound understanding of the environment. In this article, we will outline why real-time data streaming is beneficial before listing the leading real-time data streaming tools currently available.

IIS (Internet Information Services) is a web server developed by Microsft, shipped as a part of the Windows Server services. It’s used to host and manage web applications and services. IIS is a particularly robust web server solution that is tightly integrated with the Windows operating system, making it a natural choice for organizations that rely on other Microsoft products.

For accurate and effective performance testing, synthetic monitoring has become a staple and this is only going to continue in the coming years. This is mainly due to the fact that this process is beneficial and offers numerous advantages to organizations. With synthetic monitoring, your organization can identify performance issues before they affect real users. By continuously simulating user interactions, your team can highlight and rectify performance bottlenecks and infrastructure issues in real time.

SNMP, which stands for Simple Network Management Protocol, is often viewed as a legacy protocol, with SNMP not being actively worked on anymore, which led to both Microsoft and Google pronouncing that SNMP was dead. Yet, SNMP is still commonly used by numerous industries as the advantages of SNMP, especially for network monitoring, are profound. Practically, all network components across all vendors possess built-in SNMP capability.

Cloud logging continues to grow in popularity and usage as more organizations transition to storing data in the cloud rather than on-premise storage. This is fueled, in part, due to the numerous advantages that can be gained from cloud logging. For example, cloud logging solutions can scale to increasing data volumes with ease as an organization grows.

Business operations are now almost completely digitalized, this means with the appropriate tools timely data and reporting of key performance indicators can be utilized to assist in driving accurate business decision-making. With these tools, organizations can begin monitoring and analyzing extensive amounts of data that offer significant advantages to them.

Prometheus is an open-source monitoring solution, it offers efficient, scalable, and flexible monitoring practices and has emerged as a trusted tool for organizations seeking insights into their systems. It’s written in Go, gathers metrics data, and stores it in a time series database. Also, Prometheus employs a robust query language, PromQL, to manipulate and analyze collected time series data, offering versatile monitoring capabilities for various systems and services.