Although microservices and cloud architectures are the new norm for modern applications, cloud cost optimization could run high in observability. High costs are largely due to the number of components involved in cloud architectures. According to Cloud Data Insights in a recent report, around 71% of IT companies say that cloud observability logs are growing at an alarming rate— a driving factor for rising observability costs.

Having a strong full-stack observability has become increasingly crucial in modern IT environments, as organizations strive to gain deep insights into their systems’ behavior, performance and overall health. However, achieving effective observability can be challenging without the right tools and strategies in place. In this article, we will explore the key challenges associated with observability and how Coralogix can help overcome those issues.

In a rapidly evolving realm of IT, organizations are constantly seeking peak performance and dependability, leading them to rely on a reliable observability platform to obtain valuable system insights. Logs vs metrics play a vital role, as any full-stack observability guide would tell you, serving as essential elements for efficient system monitoring and troubleshooting. But what are logs and metrics, exactly?

Python is a highly skilled language with a large developer community, which is essential in data science, machine learning, embedded applications, and back-end web and cloud applications. And logging is critical to understanding software behavior in Python. Once logs are in place, log monitoring can be utilized to make sense of what is happening in the software. Python includes several logging libraries that create and direct logs to their assigned targets.

For a game to provide the best user experience, certain elements come into play. These factors can be hardware components in the user’s computer, like the CPU and GPU, operating system settings, or specific game settings. In fact, if there’s misalignment between these components and a game’s intensity, performance issues can crop up. The most common performance issues in gaming include frame rate drops, input lag, stuttering, rendering issues and network latency.

As a leading full-stack observability platform, Coralogix enables you to gather, monitor and analyze your infrastructure and application telemetry. And Coralogix now offers synthetic monitoring for proactive end-to-end testing across development with Checkly.

With various open source platforms on the market, engineers have to make smart and cost-effective choices for their teams in order to scale. Elastic Cloud, and its flagship product Elasticsearch, are one of several options available, but how do they compare to a full-stack observability platform like Coralogix? This article will provide a complete breakdown between Coralogix and Elastic Cloud, from essential industry features, like logs, metrics and traces, to pricing models and support services.

Fintech companies operate in a complex technological and regulatory environment. They rely heavily on cloud-native technologies and microservices architectures to handle financial transactions and data, often at a massive scale. To maximize application reliability, fintech companies need full visibility into their software systems and applications. An agile monitoring solution like observability is crucial to improving performance and user experience.

Distributed microservices and cloud computing have been game changers for developers and enterprises. These services have helped enterprises develop complex systems easily and deploy apps faster. That being said, these new system architectures have also introduced some modern challenges. For example, monitoring data logs generated across various distributed systems can be problematic.

Gaming apps are complex systems. They combine multi-function systems, like the game engine, to other resources such as server containers, proxies and CDNs in order to give users a real-time interactive experience. At the same time, managing cross-functional behavior also means that games could generate massive amounts of data, commonly known as logs. You’ll want to turn that data into useful information to help improve game performance.