The latest News and Information on Log Management, Log Analytics and related technologies.
If you’re in the cloud engineering and DevOps space, you’ve probably seen the name OpenSearch a lot over the last couple of years. But, what is your current understanding of OpenSearch, and the components around it? Let’s take a closer look.
Any software application or a system can have bugs and issues in testing or production environments. Therefore, logging is essential to help troubleshoot issues easily and introduce fixes on time. However, logging is useful only if it provides the required information from the log messages without adversely impacting the system’s performance. Traditionally, implementing logging that satisfies these criteria in Java applications was a tedious process.
Modern, high-scale applications can generate hundreds of millions of logs per day. Each log provides point-in-time insights into the state of the services and systems that emitted it. But logs are not created in isolation. Each log event represents a small, sequential step in a larger story, such as a user request, database restart process, or CI/CD pipeline.
Observability has become a critical part of the digital economy and software engineering, enabling teams to monitor and troubleshoot their applications in real-time. Properly managing logs, metrics, traces, and events generated from your applications and infrastructure is critical for observability. A telemetry pipeline can help you gather data from different sources, process it, and turn it into meaningful insights.
Cloud infrastructure and application monitoring dashboards are critical to gaining visibility into the health and performance of your system. But what are the best metrics to monitor? What are the best types of visualizations to monitor them? How can you ensure your alerts are actionable? We answered these questions on our webinar Build the Ultimate Cloud Monitoring Dashboard.
