As digital transformation and the consequent move towards cloud-native continues to accelerate, and customer demands increase, traditional approaches to debugging and troubleshooting are limited and insufficient. Developers must quickly understand the relationships between user sessions, topology, and end-to-end transactions during incidents.
Logs are the core of the human-machine interface for software developers and operators. Historically, they are very much like caveman paintings. They were our first attempt to express and understand how our software was working. For several decades, logs were an island of calm in a rapidly changing technological ecosystem. Logs remained the same even as software services became web-based and grew in scale.
Data observability is a critical aspect of any data-driven business. It refers to the ability to monitor, understand, and troubleshoot data quality issues in real-time. In essence, data observability ensures that data is accurate, reliable, and accessible. It involves collecting and analyzing data from various sources to gain insight into how data is being used, how it is flowing through the system, and whether it is meeting the required quality standards.
A lot has been written about data observability by authors, analysts, and vendors over the past few years as it is becoming an increasingly important component of organizations' data architectures. This blog will examine why organizations need data observability and how they should approach the buying experience/cycle.
Harness the power of data observability across your modern data stack.
Learn what observability is and why it matters to Site Reliability Engineers.
Today, we are very excited to announce the acquisition of Aspecto, an OpenTelemetry (OTel) pioneer whose capabilities will further extend SmartBear’s modern, developer-focused observability capabilities. Aspecto’s solution discovers modern microservice based architectures and visualizes all the real-time interactions between services and APIs through advanced distributed tracing capabilities.
Organizations use load and performance testing to prevent issues from impacting customers, which is essential if they want to stay relevant in today’s digital-first world. And with the rise of cloud native technology and DevOps, software teams must shift performance testing left, towards development. However, traditional load and performance testing tools simply haven’t kept pace, leaving developers, operations, and QA teams siloed.
