Observability architecture and design is becoming more important than ever among all types of IT teams. That’s because core elements in observability architecture are pivotal in ensuring complex software systems’ smooth functioning, reliability and resilience. And observability design can help you achieve operational excellence and deliver exceptional user experiences. In this article, we’ll delve into the vital role of observability design and architecture in IT environments.

How you choose to store and process your system data can have significant implications on the cost and performance of your system. These implications are magnified when your system has data-intensive operations such as machine learning, AI, or microservices. And that’s why it’s crucial to find the right data format. For example, Parquet file format can help you save storage space and costs, without compromising on performance.

Splunk has become one of several players in the observability industry, offering a set of features and a specific focus on legacy and security use cases. That being said, how does Splunk compare to Coralogix as a complete full-stack observability solution? Let’s dive into the key differences between Coralogix vs Splunk, including customer support, pricing, cost optimization, and more.

Amid a big data boom, more and more information is being generated from various sources at staggering rates. But without the proper metrics for your data, businesses with large quantities of information may find it challenging to effectively and grow in competitive markets. For example, high-quality data lets you make informed decisions that are based on derived insights, enhance customer experiences, and drive sustainable growth.

Extracting insights from log and security data can be a slow and resource-intensive endeavor, which is unfavorable for our data-driven world. Fortunately, lookup tables can help accelerate the interpretation of log data, enabling analysts to swiftly make sense of logs and transform them into actionable intelligence. This article will examine lookup tables and their relationship with log analysis.

The Content Delivery Network (CDN) market is projected to grow from 17.70 billion USD to 81.86 billion USD by 2026, according to a recent study. As more businesses adopt CDNs for their content distribution, CDN log tracking is becoming essential to achieve full-stack observability. That being said, the widespread distribution of the CDN servers can also make it challenging when you want visibility into your visitors’ behavior, optimize performance, and identify distribution issues.

Artificial intelligence (AI) has emerged as a transformative force, empowering businesses and software engineers to scale and push the boundaries of what was once thought impossible. However as AI is accepted in more professional spaces, the complexity of managing AI systems seems to grow. Monitoring AI usage has become a critical practice for organizations to ensure optimal performance, resource efficiency, and provide a seamless user experience.

While Coralogix Remote Query is a solution to constant reingestion of logs, there are few other options today that also offer customers the ability to query unindexed log data. For instance, DataDog has recently introduced Flex Logs to enable their customers to store logs in a lower cost storage tier. Let’s go over the differences between Coralogix Remote Query vs Flex Logs and see how DataDog compares. Get a strong full-stack observability platform to scale your organization now.

Businesses are increasingly turning to cloud computing to drive innovation, scalability, and cost efficiencies. For many, managing cloud costs becomes a complex and daunting task, especially as organizations scale their cloud infrastructure and workloads. In turn, cloud cost management tools can help teams gain better visibility, control, and cost optimization of their cloud spending. These tools not only provide comprehensive solutions to track and analyze, they also optimize cloud expenses.