Posts about user interface, custom views, configuration.
In my last post, I discussed how enterprise application sprawl, if left unchecked, puts organizations at risk. In this post, I’m going to discuss what to do about the problem. Today, any single department within even a mid-market enterprise will have more applications deployed than was standard – organization wide – just a dozen or so years ago. These apps include everything from cloud-based CRM to social media tools to AWS workloads to various big data tools to collaboration suites, and on and on and on.
Enterprise application and computing environments have changed radically over the past fifteen years. Anyone who has spent even a day in an IT role can tell you that.What gets less attention, however, is how those changes undermine the ability of operations teams to do their jobs. The problem is that as computing and application environments have changed dramatically, workflows and org charts have not.
Last week was an exciting week. BigPanda announced $7 Million in funding from Sequoia Capital and Mayfield. We are super excited that these two firms share our vision for changing the way that IT and DevOps teams manage and respond to the thousands of IT issues they face every day. Last week, we also launched our offering into general availability. Check out some of the highlights from last week’s coverage on BigPanda from TechCrunch, GigaOm, Computerworld, 451 Research and more.
In many ways, incident management for devops is similar to typical issue tracking processes: it facilitates coordination and collaboration of daily tasks. For this reason, tools such as Jira, Zendesk, and even email are often used as solutions for incident management. But incident management faces one unique challenge that makes it different from other issue tracking processes. In addition to human-operated workflows, incident management also relies heavily on machine-driven workflows. Unfortunately, traditional issue trackers and ticketing systems cannot accommodate for this with their current product mechanics.
We engineers love measuring stuff. Whether it helps us solve an immediate problem, gets us ready for a bad day or just because most of us are information junkies, we love keeping track of metrics. The spectrum of what can be measured is very wide. It can include data from every part of our system: from technical metrics such as disk space or RPM, through UI metrics like page load times, to business KPIs such as revenue, conversion rates and so on. When choosing which metrics to collect, we usually start with the obvious ones: those that reflect the current state of the system (e.g., CPU, memory and load). There are quite a few articles and blog posts about these metrics, so I’m not going to discuss that here. Rather, I would like to focus on metrics that reflect the user experience.
Here are the four metrics that we at BigPanda see as the most important in this category: