The latest News and Information on Observabilty for complex systems and related technologies.
Financial technology (FinTech) companies today are shaping how consumers will save, spend, invest, and borrow in the economy of the future. But with that innovation comes a critical need for scalable cloud observability solutions that can support FinTech application performance, security, and compliance objectives through periods of exponential customer growth. In this blog, we explore why cloud observability is becoming increasingly vital for FinTech companies and three ways that FinTechs can improve cloud observability at scale.
Throughout the third quarter of this year, Lightrun continued its efforts to develop a multitude of solutions and improvements focused on enhancing developer productivity. Their primary objectives were to improve troubleshooting for distributed workload applications, reduce mean time to resolution (MTTR) for complex issues, and optimize costs in the realm of cloud computing. Read more below the main new features as well as the key product enhancements that were released in Q3 of 2023!
Elastic® SQL inputs (metricbeat module and input package) allows the user to execute SQL queries against many supported databases in a flexible way and ingest the resulting metrics to Elasticsearch®. This blog dives into the functionality of generic SQL and provides various use cases for advanced users to ingest custom metrics to Elastic®, for database observability. The blog also introduces the fetch from all database new capability, released in 8.10.
Do you want to build software faster and release it more often without the risks of negatively impacting your user experience? Imagine a world where there is not only less fear around testing and releasing in production, but one where it becomes routine. That is the world of feature flags. A feature flag lets you deliver different functionality to different users without maintaining feature branches and running different binary artifacts.
The shift from traditional monitoring to observability is widespread, and necessary. It's the way we make sense of increasingly complex and distributed systems. But when we capture all this data at scale... what do we do with it all? If this data itself had inherent value, we’d all be rich. But in the real world data does not provide us value until we can act on what it tells us.