If you’re reading this, you likely know what a log is, and what a metric is. But sometimes there are questions on their differences, whether you really need both, and if you should use dedicated solutions to manage each type.
The answers? Yes, you need both; yes, they should be unified. Logs and metrics, aka machine data, are complementary. A log is the descriptive historical record of an event that has occurred, and they are generated by applications, infrastructure, and more. Logs allow you to track issues or other important details and also gain a bit of context of the issue – a log typically contains related details to paint a clear picture of what is going on at that moment. A metric speaks to the current health of a single component within a system at an instance in time, it’s akin to monitoring the vitals of an application or system, metrics are typically generated as a constant stream of data, whether something of note has occurred or not. It’s probably clear by just this fact that without corresponding logs to provide context, the metric doesn’t mean much.
One major business benefit of unifying your machine data is to make IT more strategic. Unified analytics give IT teams the opportunity to evolve beyond KPIs like page load times, towards using that data to become purveyors of information. It’s difficult to achieve this elevated position without the full visibility provided by metrics and logs.
To get there, IT Ops, Security, and DevOps teams need to adopt the mindset of instrumenting applications and infrastructure and collecting all the ensuing machine data. To get the most value of this data it should be fed into a single enterprise log management solution. Sound impossible? It shouldn’t, especially when you consider that most IT organizations have relied on legacy monitoring tools designed for static and monolithic architectures and individual tools focused on specific parts or even specific vendor components of an application or infrastructure. Businesses still maintain the status quo despite the silos and shards that must be managed, not to mention the impossible task of manually sorting through logs; in addition, monolithic applications are becoming less common in favor of dynamic applications with rapid dev cycles. When business stakeholders are calling for help in identifying and improving a company’s security posture or tracking and monitoring business services’ performance against network or application performance data the answer can no longer be “we can’t afford to do it” or that the insights are too slow to materialize.
Let’s take a look at the capabilities an enterprise log management solution must have in order to move the business forward through better analytics derived from log and metric data. They are:
- Able to collect 100% of your machine data
- Able to unify 100% of your machine data
- Able to support thousands of users, algorithms, and automation who need to have access to your machine data with minimal latency
- Ensure all data is always accessible and visualized, in its full granularity
- Scale to meet the demands of today and tomorrow
These core capabilities demonstrate the need for a full-stack enterprise log management (ELM) solution, one that democratizes access to machine data and enables easy collection, storage, and visualization of data. Technology is changing faster than ever; enterprises add new machine data sources all the time, and it becomes cumbersome to stand up and manage new point product solutions to gain full visibility. What’s more, a better understanding of environments is difficult to achieve with so many disparate tools – IT professionals would need to constantly be trained on these solutions, again creating more silos. With this knowledge in mind, it’s even more important to build using a scalable, source-agnostic tool.
Logs and metrics are too important to be independent of each other. The DevOps culture is built on the premise that the critical information they provide will be used to maintain continuous delivery, keeping applications running smoothly and users happy. When logs and metrics are integrated into a single ELM solution, it not only simplifies environmental complexities, but allows businesses to move beyond the constraints of slow data silos and to operationalize all their machine data.
Keep reading to find out more about turning logs and metrics into business value.