The need for relevant and contextual telemetry data to support online services has grown in the last decade as businesses undergo digital transformation. These data are typically the difference between proactively remediating application performance issues or costly service downtime. Distributed tracing is a key capability for improving application performance and reliability, as noted in SRE best practices.

When it comes to comparing all of the best solutions for log management and analysis it can be incredibly difficult to compare key features and pricing per annum side by side to see what solutions you should consider trialling.

At Payoneer, we use Coralogix to collect logs from all our environments from QA to PROD. Each environment has its own account in Coralogix and thus its own limit. Coralogix price modules are calculated per account. We as a company have our budget per account and we know how much we pay per each one. In case you exceed the number of logs assigned per account you will pay for the “extra” logs. You can see the exact calculation in this link.

There’s something wrong with the pricing of observability services. Not just because it costs a lot – it certainly does – but also because it’s almost impossible to discern, in many cases, exactly how the costs are calculated. The service itself, the number of users, the number of sources, the analytics, the retention period, and extended data retention, and the engineers on staff who maintain the whole system are all relevant factors that feed into the final expense.

An often overlooked aspect of a company’s journey to the cloud is cost visibility. While the single number delivered by the cloud provider on a monthly invoice is straightforward, understanding where this number comes from is often more tricky. Fortunately, this task can be facilitated through the usage of various cost monitoring tools available on the market, coming from both third-party companies and the cloud providers themselves.

If you’re reading this, I’m pretty sure I don’t need to do much to convince you of the importance of logs. They are the core atomic unit for understanding your environments and provide the insights required to troubleshoot, debug, and more. The fact of the matter is that everyone in your organization needs logs to perform critical functions of their job.

Sifting through logs in real-time or post-mortem to pinpoint the problem can take hours – and is often like trying to find the needle in the alert/log haystack. Further, keeping the troubleshooting process efficient can be a challenge due to context switching and relying on manual interpretation of events and technology-specific knowledge.

The ELK Stack has millions of users globally due to its effectiveness for log management, SIEM, alerting, data analytics, e-commerce site search and data visualisation. In this extensive guide (updated for 2021) we cover all of the essential basics you need to know to get started with installing ELK, exploring its most popular use cases and the leading integrations you’ll want to start ingesting your logs and metrics data from.