Today’s post continues the trend of covering log-related topics, by answering the question: “what is log analysis?” What is this, and why is it essential for your organization?

Logs. You have them. You need to keep track of them. The process of log monitoring can be tedious. Typically it’s one of those things we take for granted and only look at when it stops working. So, how do you deal with them? In this post, we’re going to talk about why and how to monitor logs. Toward the end, we’ll discuss a few tools that’ll help, mostly to avoid manual labor.

Do you own or manage a business? Managing a company involves many steps. These steps begin right from the genesis of an idea through its execution. They also involve choosing a development procedure and managing risks. Most software companies these days are adopting the latest project methodologies, like DevOps and agile.

This is the one post I hope you’ll never need. However, should you ever need it, this is your one-stop shop for understanding how to proceed with DevOps incident management. Have you just been attacked? Did the commit go wrong? A CI pipeline went haywire? Don’t worry. I got you.

Measuring the maturity of your DevOps team might sound difficult, but it isn’t at all. Simple key performance indicators (KPIs), such as the deployment success rate or mean time between failure, give a good indication of the maturity of your DevOps team. By “mature,” I mean that your team consistently and smoothly operates at a high level and can deploy several times a day with very little risk.

Today’s post covers yet another log-related concept: log forensics. What’s this, and why should your organization care about it? Well, this is a topic related to logs, which are ubiquitous in the technology field. An IT organization that doesn’t generate many MBs worth of logs each day would be a rare occurrence nowadays. Even though logs are omnipresent, specific terms might not be so well-known. Not long ago, we covered log analytics, and today it’s log forensics time.

If you work in IT, especially on the decision-making side, then you should be aware of how vital logging is. When things go wrong with software in production, a solid logging approach often is the difference between hours of fruitless troubleshooting and an easy fix. Today, we’re here to talk about logging by covering a specific angle. Namely, we’ll answer the question, “What is log collection?”

Cloud computing, mobile devices, and IoT technologies continue to evolve and proliferate. As a result, businesses are generating and collecting more data than ever before. Data is generated and stored every time a customer interacts with a website or device. Savvy companies understand the importance of capitalizing on that data. It enables them to enhance customer experiences and increase profitability, among other countless benefits.

Before the need for log correlation, there was a time not so long ago when reading software application logs was simple. Your application would output log files in sequential order, and you’d read through them. In the event of a bug, software outage, or security incident, you could easily parse what happened and when. It was a tedious process, but it was simple.

Time for another installment in the series where we explain in detail yet another important metric for tech organizations. After covering MTTD and MTTF, today we answer the question, “What is MTBF?” As the post title makes clear, MTBF stands for “Mean time between failures.” The acronym refers—like the others that came before it—to an important DevOps KPI. But what actually is it? What is it good for? How do I implement it?