"Big Data Automation Management" is more of a fire than big data.

Now everyone is talking about big data, but in fact, much of the talk is too exaggerated. Employment data show that large numbers seem to be needed by corporate recruiters. However, more data suggest that companies do not know what to do with these big data professionals.

However, more important than large data itself is the analysis and management of large data. This trend is allowing server Automation configuration system tools to emerge in large numbers. Puppet is the power behind the "DevOps" trend.

As dice.com data shows, Puppet is a trend because it provides an easier way for businesses to manage a certain scale of IT infrastructure. These infrastructures are not called "Big data", or they are called "Server operation Maintenance" that sounds silly.

Puppet is manipulating everything behind the scenes.

Dice.com's focus on technological talent is an accurate barometer for tracking the ups and downs of the job market for technology professionals. This is not measured by the Google search engine or any other soft factor, because dice has tracked about 80,000 jobs posted on dice.com every day. It then determines the top 10 "killer" job skills each year based on the number of jobs that appear in open recruitment.

According to the latest Dice report, Puppet is now behind the scenes. Let's take a look at the dice form of the fastest-growing job skills.

In these figures, two are extremely prominent:

No matter how hot the big data and its related technologies are, IT management is still the old market.

Puppet makes Big Data a reality. The underlying data is the server, and the server needs to be managed. Puppet makes it easier to manage servers of a certain size, and it is already the "leader" in Hadtoop related management tools, like Bigtop.

DevOps's pro, Sean Carolan, said on Twitter: "Whether or not companies publicly define themselves as" big data "operators, they are beginning to realize that" either automate or die ". "This kind of automation will not stop in an age when software distribution is non-stop." "Although there is fierce competition between puppet and chef,ansible and salt today, it has become a market leader," he said.

Puppet Lab's CEO, Luke Kanies (also founder of Puppet), explained the data:

The field of puppet-automation-is not the same as other fields, which is difficult to compare. All companies have been working on databases, so NoSQL has been helped by this tradition and hindered by this tradition. Whether they want to or not, they are fundamentally an industry that can be replaced.

With Puppet, we made up for the flaw. Many people who use puppet do not have to manually do things like writing custom scripts, and they can use automated technologies that have broader markets and better ecosystems. They do not have to terminate any programs or discard any existing skills, so it is more convenient from a humanistic standpoint. Moreover, it management market is becoming more and more stalemate, all enterprises know that these problems must not be solved--puppet can meet your basic needs, rather than as a better way to replace your previous habits.

Kanies listed several big reasons why puppet would be more popular. But can it really do bigger than big data?

The battle between puppet and Big Data

Automatic configuration Management market is in the early stages of development, menacing, it also has a lot of space for development. Puppet dice.com the top of the list just shows that its development base is small.

Again, the fact that dice.com data is not exactly in line with the employment data provided by Indeed.com.

Indeed.com tracked job information from more than 1000 websites, including dice.com. So in the analysis of employment trends, Indeed.com has a more complete database. Indeed.com's data suggest that the size of big data and Hadoop is much larger than puppet in open recruitment:

Even in terms of relative growth-which is exactly what dice.com cares about-is Hadoop and NoSQL ahead.

However, this is not the whole situation. Hadoop, for example, is not a separate Web site. It is a technical system that receives from hive (a distributed storage system that facilitates querying and managing large data sets) to HBase (a key-value data storage System) to pig (a platform for analyzing large datasets) to a range of technology data that has been evolving and expanding.

In fact, "NoSQL" is the same, but the difference between the database is much more obvious than the similarities. A document database is very different from a key-value data store. Publishing a generic "NoSQL" database job actually means that businesses don't know what they need. Broadly speaking, all those who need "big data" expertise are as dazed as these companies.

Puppet make Big Data no more empty talk

Companies that work with big data don't necessarily know what the secret of their success is. As I've written before, Gartner's data on this is clear: everyone knows they need to do something with "big data", but it's still a mystery what to do or do.

Not surprisingly, companies that really use big data start after media hype, which is strikingly consistent with 451, analyst Michael Coté, in this chart on large data storage use:

While companies are still exploring large data areas, they are increasingly finding it necessary to manage infrastructure more effectively. Puppet is the tool that helps you "how" to manage your infrastructure-or, crucially, how.

In fact, as long as you understand that all the basic and large data-related open jobs are more or less grandstanding, it's easy to assume that the obvious data difference between dice.com and indeed.com is reasonable. Organizations don't know what they need, they just know they have to do something meaningful with big data, so they're only trying to hire people.

However, when they are looking for puppet expertise, they also know what they really need-the tools to help configure and manage a large group of servers. Although those servers will eventually be called "Big data", they need to be managed regardless of their fashionable name.

Source:readwrite

(Responsible editor: Mengyishan)