This is an updated version of an earlier blog post that now includes links to our documentation. Full-text searches are a marvel of modern computing. In less than a second, search engines can match a query against hundreds of millions of documents. In the early days of search engines, you often had to use specific search operators and terms to get accurate results.

You’ve likely noticed how some pizza places promise delivery in 30 minutes, or they’ll give you your money back. But what are they really promising? They’re setting a clear performance goal and backing it up with confidence. How do they measure their performance? They track how long each delivery takes. And why do they make this promise? Because fast service is key to keeping their business thriving.

During our webinar, Next Gen Log Management: Maximize Log Value with Telemetry Pipelines, we discussed how you can take your log management strategy to the next level with telemetry pipelines and unlock the full potential of your data. Bill explained that the rapid growth of log data is driving up storage and management costs. He emphasized the need for an intelligent, adaptable log management system to efficiently handle this situation.

One challenge for the widespread adoption of telemetry pipelines for SRE teams within an organization is knowing where to start when building a pipeline. Faced with a wide assortment of sources, processors, and destinations, setting up a telemetry pipeline can seem like trying to build a Lego set without any instructions. The solution is to provide teams with pre-defined components that provide specific functionality, that they can then use to build pipelines that meet their own requirements.

Alerts that you receive from your observability tool are based on conditions that existed seconds to minutes in the past, because the alert is only triggered after the data has been indexed within the tool. This means that your ability to take timely action in response to the condition is significantly limited, and often your window of opportunity to react is past by the time you receive the alert.

Once upon a time, we thought “Log everything” was the way to go to ensure we have all the data we needed to identify, troubleshoot, and debug issues. But we soon had new problems: cost, noisiness, and time spent sifting through all that log data. Enter log analysis tools to help refine volumes of log data and differentiate signal from the noise to reduce mental toil to process. Log beast tamed, for now….

Once upon a time, we thought “Log everything” was the way to go to ensure we have all the data we needed to identify, troubleshoot, and debug issues. But we soon had new problems: cost, noisiness, and time spent sifting through all that log data. Enter log analysis tools to help refine volumes of log data and differentiate signal from the noise to reduce mental toil to process. Log beast tamed, for now….

What keeps an SRE at the top of his game? I had an insightful conversation with Jon Duarte, a Site Reliability Engineer (SRE) at Mezmo and he walked me through his role and the various tasks he manages on a typical day. Here’s Jon offering a brief glimpse into the challenges he faces, the thought processes behind his approach, and the innovative solutions SREs come up with.

Like many other organizations, we at Mezmo struggle with a lot of telemetry data, and for a while our team configured our logs to be sent to a global Mezmo Log Analysis account in our SaaS so we would have a single pane of glass to view all of our logs. Our SRE team wanted to make sure that we have experience utilizing our new pipeline product. We set out some goals before we started using telemetry pipeline.

Imagine running a large company where data-driven decisions give you a competitive edge. You use a lot of business intelligence tools that tap into vast amounts of data, such as sales figures, inventories, and expenses. This analysis tells you how your company is performing. However, it does not reveal how your "company infrastructure" is performing. This crucial information comes from your systems in the form of telemetry data, such as logs and events.