A recurring theme in our MesosCon North America 2016 series is solving difficult resource provisioning problems. The days of investing days or even weeks in spec’ing, acquiring, and setting up hardware and software to meet increased workloads are long gone. Now we see vast provisioning adjustments taking place in seconds.
Open source knowledge is very valuable in today’s job market. The 2016 Open Source Jobs Report from The Linux Foundation clearly showed that hiring managers are placing much value on open source cloud, networking, and security skills. It also showed that DevOps is emerging as a red hot job category.
Trying to maximize business efficiencies while staying within a budget is something that keeps CTOs and CIOs up at night. How to do senior IT leaders manage for change with a flexible infrastructure, especially one that is built on open-source?
You know the saying: fast, cheap, or good, pick two. Uber, Twitter, PayPal, and Hubspot show that you can have all three with Apache Mesos.
Apache Mesos is a cluster manager; it sits between the application layer and the operating system, and deploys and manages applications in large-scale clustered environments. But this dry description doesn't convey its vast scope for creative and ingenious solutions to large-scale problems.
Testing applications against Hadoop distributions is not fun, either for application developers or end users, and it takes up too much precious time.
On the data analytics front, profound change is in the air, and open source tools are leading many of the changes. Sure, you are probably familiar with some of the open source stars in this space, such as Hadoop and Apache Spark, but there is now a strong need for new tools that can holistically round out the data analytics ecosystem. Notably, many of these tools are customized to process streaming data.