Operations | Monitoring | ITSM | DevOps | Cloud

Developing a proactive security strategy can potentially save an organization millions of dollars per year. According to IBM, the average cost of a data breach in 2023 added up to a staggering $4.45 million, up 15% over the last three years. This is especially true for cloud-native environments, which face unique security challenges due to their dynamic nature. Instead of waiting to respond to cybersecurity incidents after they happen, it's much better to embrace a proactive approach, and prevent them in the first place.

Establishing an effective cyber threat hunting program is among the top priorities of enterprise security leaders seeking a proactive approach to detecting and counteracting potential threats. Furthermore, implementing a proactive threat hunting program, security teams that leverage formalized frameworks or threat hunting methodologies are far more likely to detect vulnerabilities or in-process malicious activities in their environments than those that do not. However, data from a 2023 threat hunting survey revealed that while 73% of organizations have adopted a defined threat hunting framework, only 38% actually follow it.

Modern data-driven organizations are synergizing operations observability, business intelligence, and data science with digital business observability programs that break down data silos, increase productivity, and drive innovation. Digital business observability combines IT and business data with cutting-edge data science techniques, enabling deeper analysis and unlocking valuable insights that propel innovation across use cases from sales and marketing to product design and financial operations.

Today's applications demand efficient data handling to provide users with seamless experiences. One solution that has gained prominence is the use of embedded databases, which are integrated within applications rather than relying on external servers. Different from a database for embedded systems, databases embedded within applications offer several advantages for storing data and analyzing it, especially in scenarios where performance, deployment simplicity, and data security are important. Embedded databases, or an embedded database management system (DBMS), can serve a variety of use cases, but are especially valuable for applications that need to provide analytics capabilities.

Elasticsearch and OpenSearch are powerful enterprise search and analytics engines that have become popular in the world of data management and telemetry analysis. Their ability to swiftly search, analyze, and visualize data has made them indispensable for businesses and organizations. However, in this blog, we will explore a few key challenges faced by companies using Elasticsearch and OpenSearch, shedding light on important considerations when selecting the right tool for your needs.