WHY DO WE NEED DATAOPS OBSERVABILITY?
By Jason English, Principal Analyst, Intellyx
Don’t we already have DevOps?
DevOps was started more than a decade ago as a movement, not a product or solution category.
DevOps offered us a way of collaborating between development and operations teams, using automation and optimization practices to continually accelerate the release of code, measure everything, lower costs, and improve the quality of application delivery to meet customer needs.
Today, almost every application delivery shop naturally aspires to take flight with DevOps practices, and operate with more shared empathy and a shared commitment to progress through faster feature releases and feedback cycles.
DevOps practices also include better management practices such as self-service environments, test and release automation, monitoring, and cost optimization.
On the journey toward DevOps, teams who apply this methodology deliver software more quickly, securely, reliably, and with less burnout.
For dynamic applications to deliver a successful user experience at scale, we still need DevOps to keep delivery flowing. But as organizations increasingly view data as a primary source of business value, data teams are tasked with building and delivering reliable data products and data applications. Just as DevOps principles emerged to enable efficient and reliable delivery of applications by software development teams, DataOps best practices are helping data teams solve a new Read more here
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