Operations | Monitoring | ITSM | DevOps | Cloud

Observability costs are exploding as businesses strive to deliver maximum customer satisfaction with high performance and 24/7 availability. Global annual spending on observability in 2024 is well over 2.4 billion USD and is expected to reach 4.1 billion USD by 2028. On an individual company basis, this is reflected by observability costs ranging from 10-30% of overall infrastructure spend. These costs will undoubtedly rise with digital environments expanding and becoming ever more complex.

Coralogix continues to invest in and develop solutions to address modern business challenges. One such example of modern business challenges is the field of observability with data complexity and volume increasing all the time. Observability solutions play a key role in digital transformation and operational excellence, helping companies aggregate a growing amount of data, effectively analyze it, and initiate the needed actions to maintain optimal performance and uptime.

So, your company uses LLMs? You’re not the only ones. A survey by Gartner in October 2023 revealed that 55% of organizations were piloting or releasing generative AI projects, and it’s safe to assume that this number has increased since that survey was published. From personalized recommendations in e-commerce, to automated grading in education and fraud detection in finance, LLMs have helped many organizations level up.

Application performance monitoring (APM) setup and strategies vary based on the application’s infrastructure design. Containers managed by orchestration tools like Docker Swarm or Kubernetes are dynamic and ephemeral, significantly affecting monitoring strategies. Container development speeds up an organization’s ability to build, deploy and scale new features.

There are many solutions on the market that are promising insight into the four key metrics. Alas, these solutions often come with a significant price tag. Coralogix doesn’t charge per feature, per user, per host or per query. We charge by GB. And that, coupled with some incredible analytics and indexless observability, makes for some incredible insights that cost almost nothing.

One more season and one more clean sweep! The G2 Spring 2024 Reports are out, and Coralogix has secured 106 badges across various categories and market segments. Coralogix has also secured a “Users Love Us” badge that showcases our customers’ trust in Coralogix. We are excited because there’s a lot more. Read on! Every quarter, G2 releases reports highlighting the best software and services of the season.

A healthy relationship between services and databases is fundamental to overall application performance. Unchecked database issues can compromise application efficiency, user experience, and ultimately, your organization’s bottom line. To steer clear of these consequences, monitoring your databases should be a key component of your observability—and with the launch of Coralogix Database Monitoring, it can be.

As Coralogix is a full-stack observability platform with log analytics, RUM, APM, SIEM and more, it’s hard to really compare it to Sentry’s very limited offering of error tracking and some other real user monitoring functionality. Sentry is also insanely expensive in comparison to Coralogix. Nonetheless, we shall attempt to assess how Sentry’s RUM offering stacks up.

When discussing observability pricing models, there are three dimensions that must be considered The first, Cost per Unit, is an easy-to-understand metric, but in practice it is often overshadowed by a lack of transparency and predictability for other costs. The question is simple: how does a usage based pricing model impact these variables?

As data keeps growing at incredible rates, it’s becoming increasingly difficult to store and monitor at a reasonable cost leaving you to cherry-pick which data to store. As developers are accustomed to integrating metrics within their logs and spans, this can result in poor monitoring & analysis, alert fatigue, and longer MTTR. Teams are left having to dig out the most relevant data, which results in missed trends and analysis.