Overcoming modern observability challenges | InfoWorld

Observability Challenge #1: Fragmentation and Complexity

Traditionally, organizations have deployed multiple observability tools in their technology stack to meet different needs such as monitoring logs, metrics, or tracing. While these specialized tools perform well individually, they rarely communicate well, leading to data silos. This fragmentation prevents teams from gaining comprehensive insights, forcing Development and operation and SRE (Site Reliability Engineering) teams rely on manual integration to piece together a complete picture of how the system is functioning. The result is increased insight latency and mean time to resolution (MTTR), slowing down effective problem response.

Additionally, organizations now need to integrate data streams outside of the traditional MELT (metrics, events, logs and traces) framework, such as digital experience monitoring (DEM) and continuous analytics, to achieve comprehensive observability. DEM and its subset Real User Monitoring (RUM) can provide valuable insights into user interactions, while continuous analysis can pinpoint inefficient code. Without integrating these data streams, teams struggle to connect real-world customer experiences to specific code-level issues, leading to data gaps, delayed issue detection, and customer dissatisfaction.

Observability Challenge #2: Rising Costs

As tools become fragmented and data volumes increase, the cost of observability soars. SaaS-based observability solutions—which manage data ingestion, storage, and analysis for customers—have become particularly expensive, and costs add up quickly. according to a Recent IDC reportsnearly 40% of large enterprises cite high cost of ownership as a major issue with observability tools, with median annual spend for large organizations (10,000+ employees) Number of operations and observability tools to $1.4 million.