Enterprise software development teams have historically had trouble ensuring the code that runs well on a developer's machine also runs well in production. DevOps has promoted more collaboration between developers and IT operations. Data scientists and data science teams face similar challenges, which DevOps concepts can help address.
Many people believe that workloads in the cloud always perform better because public clouds have access to an almost unlimited amount of resources. Although you can provision the resources you need?and even use serverless computing so the allocation of resources is done for you?the fact is that having the right amount of resources is only half the battle.
About a decade ago, the software engineering industry reinvented itself with the development and codification of so-called devops practices. Devops, a compound of ?development? and ?operations,? refers to a set of core practices and processes that aim to decrease time to market by thoughtfully orchestrating the tight integration between software developers and IT operations, emphasizing reuse, monitoring, and automation. In the years since its introduction, devops has taken the enterprise software community by storm garnering respect and almost-religious-like reverence from practitioners and devotees.
Click to learn more about author Paul Stanton. There is a disconnect between the goals of DevOps, and the realities of working with relational data. Relational databases are core to many enterprise applications, and the Gartner Group projects that 80% of new projects will rely on relational data through 2020 (available courtesy of Microsoft here). [?]
In 2018, ?hybrid IT? will be the most overused term in the IT industry. That?s not to say that hybrid IT isn?t a real thing. It very much is. Enterprise IT organizations have found themselves in a position where they are surrounded on all sides by both emerging and legacy systems, which creates the conditions for operating an environment that is anything but standardized. Hence the hybrid moniker.
by Angela Guess According to a recent press release, ?StreamSets Inc., provider of the industry?s first enterprise data operations platform, today announced immediate availability of StreamSets Control Hub, engineered to streamline the development and operational management of many-to-many dataflows. Available in StreamSets Enterprise Edition, StreamSets Control Hub adds DevOps sensibilities to data movement architectures. It [?]
Most enterprises have an accidental hybrid IT reality, rather than a strategy. As various groups and geographies in enterprise organizations procure their own cloud services independently of the IT organization, conflict emerges between the use of traditional computing infrastructure and of cloud options. As this situation grows, it exposes inefficiencies and risks that demand a more strategic approach.