16 Results Found
If you want to stay relevant as an IT professional, you have two choices: evolve your current skills or make a big change.
This article defines many of the most commonly used terms in the virtualization vocabulary.
Let's look at 10 ways the cloud will change (and to a large degree already has changed) the world.
We spoke with Doug Cutting about his role with Cloudera and learned more about Big Data, training options for IT professionals interested in Big Data, and how Cloudera compares to Red Hat.
The change we have been talking about for years is here: IT Departments are being torn apart and reassembled in new and interesting ways, as one by one companies make their move to the Cloud. As predicted, IT Pros are being asked to take on new and different roles and to be more involved in the business. In this session, we will look at some of these new roles; what’s working, what’s failing, who is succeeding and who has been left behind. Being an IT professional today is exciting as it is scary. There is lots of opportunity; but so many gaps to fall into. It is time to take inventory and ask yourself: are you well positioned to succeed? Related: Ten IT Skills on the Brink of Extinction
To help you stay ahead of the game, here are ten IT skills that are on the brink of extinction.
Google Cloud Platform (GCP) is Google’s public cloud offering comparable to Amazon Web Services and Microsoft Azure. The difference is that GCP is built upon Google's massive, cutting-edge infrastructure that handles the traffic and workload of all Google users. There is a wide range of services available in GCP ranging from Infrastructure-as-a-Service (IaaS), Platform-as-a-Service (PaaS) to completely managed Software-as-a-Service (SaaS). We will discuss the available infrastructure components and how they provide a powerful and flexible foundation on which to build your applications.
Yes, there’s big money in AWS Certification, which tends to outpace other cloud certification salaries, but there’s more to the cloud than dollars and cents.
As far as modern architectures go, there are few more complicated than an IoT pipeline. You’ve got to consider an ingestion layer (typically streaming) that may undergo manic load. You’ve got to think of data tagging, storage (probably across multiple engines), archival and access—both internal and external. And all of it has to scale like crazy, be as cost effective as possible, and use automation wherever it can. Oh, and your boss needs the IoT pipeline built by tomorrow. Short timelines? Tight budget? Unrealistic expectations? Unfortunately, these asks are realities for many cloud professionals. AWS knows this and is here to help.
It’s been about 10 years since public cloud offerings like AWS opened up the world of big data analytics. This post examines the top five most useful architectures used for big data stacks to learn the sweet spots of each.