While Grafana is one of the better known names in the industry, Coralogix offers a full-stack observability platform. Despite the popularity of the Grafana brand, the cloud based solution lacks in some key areas. This article will go over the differences between Coralogix and Grafana Cloud, from features, customer support, pricing and more.
Google Cloud Operations, formerly known as Stackdriver, is relatively new to the observability space. That being said, its position in the GCP ecosystem makes the platform a serious contender. Let’s explore some of the key ways in which Google Cloud Operations differs from Coralogix, a strong full-stack observability platform and leader in providing in-stream log analysis for logs, metrics, tracing and security data.
In recent years, microservices have emerged as a popular architectural pattern. Although these self-contained services offer greater flexibility, scalability, and maintainability compared to monolithic applications, they can be difficult to manage without dedicated tools. Kubernetes, a scalable platform for orchestrating containerized applications, can help navigate your microservices.
Mezmo, formerly known as LogDNA, offers log analytics without any native capabilities around metrics and tracing data. While Coralogix’s full-stack observability supports logs, metrics, tracing and security data, for the purpose of this comparison with Mezmo, we will focus primarily on logs.
Google Cloud Platform (GCP) offers a wide range of features to support their core deliverable, highly available and scalable infrastructure-as-a-service. One of the features—GCP’s log management and available via GCP Log Explorer— is offered to support customers’ basic logging requirements.
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.
