Tsunami detection. Crop dusting. Biohazard monitoring. What may sound like innuendos in the next EL James novel are also fields being revolutionized by quant jocks and smart algorithms. And yet, despite all the innovation, we technorati continue to bastardize the terms “data science”, “machine learning,” and “big data”. They’ve become lazy speak for “we’re not sure what we’re doing so we’ll hand wave cliches until we have real technology and a business model."
In 1792, the New York Stock Exchange opened its doors on Wall Street with five stocks available for trade. Today, more than 2,800 companies list on the NYSE with a combined market value of more than $15 trillion. In 223 years, everything except the name has changed.
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.
We’re excited to announce BigPanda Environments, a powerful new feature that enables IT teams to create customized monitoring views for any slice of their IT infrastructure. From application to team – by cloud, customer or data center – create custom monitoring views for virtually any logical grouping of an IT environment.
The last ten years have brought enormous changes to production environments, driven by a best-of-breed approach to production infrastructure enabled by open source and cloud. This has been a boon for developers in terms of flexibility and productivity, but it’s also placed a new set of challenges and expectations on Ops.