Operations | Monitoring | ITSM | DevOps | Cloud

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.

At Mezmo, we consider Understand, Optimize, and Respond, the three tenets that help control telemetry data and maximize the value derived from it. We have previously discussed data Understanding and Optimization in depth. This blog discusses the need for responsive pipelines and what it takes to design them.

One of the most common sentiments across the industry, let alone this world, is burnout. Burnout is prevalent, the World Health Organization (WHO) estimates it costs the global economy $1 trillion dollars a year. A Gallup poll equated that to $3,400 lost for every $10,000 of salary due to lack of productivity. This problem isn’t ending anytime soon either, with the global Cybersecurity industry alone having a talent shortage of 4 Million people.

In most situations, you will have several sources of telemetry data that you want to send to multiple destinations, such as storage locations and observability tools. In turn, the data that you are sending needs to be optimized for its specific destination. If your data contains Personally Identifying Information (PII) for example, this data will need to be redacted or encrypted before reaching its destination.

A couple of weeks back, I had the opportunity to participate in the Gartner Security and Risk Summit held in National Harbor, MD. While my colleague, April Yep, has already shared insights on the sessions she attended, this blog will delve into the emerging data privacy concerns and explore how telemetry pipelines can effectively tackle these challenges. Two key drivers behind current privacy concerns are the adoption of Gen AI and increasing government regulations.