Cloud computing has opened new paradigms that enable enterprises to reach new levels of productivity and scale. At the tip of that spear is serverless computing, enabling developers, teams, and organizations to focus on business logic and leave hosting and scaling of resources to the cloud platform.
It's always been a tricky business to handle mission-critical processes. Much of the technical debt that companies assume comes from having to architect systems that have multiple layers of redundancy, to mitigate the chance of outages that may severely impact customers. The process of both architecting and subsequently maintaining these systems has resulted in huge losses in productivity and agility throughout many enterprises across all industries.
The emergence of the cloud and the edge as the new frontiers for computing is an exciting direction—data is now dispersed within and beyond the enterprise, on-premises, in the cloud, and at the edge.
Most modern-day businesses employ analytics pipelines for real-time and batch processing. A common characteristic of these pipelines is that data arrives at irregular intervals from diverse sources. This adds complexity in terms of having to orchestrate the pipeline such that data gets processed in a timely fashion.
Personal computers revolutionized the way work was done. New software unlocked unprecedented levels of productivity, and for a time, business flourished. As the personal computer exploded in popularity, more and more software was created. For the individual, this was a golden age. For the enterprise, this was also a golden age... with an asterisk.
For businesses today, data is indispensable. Innovative ideas in manufacturing, health care, transportation, and financial industries are often the result of capturing and correlating data from multiple sources.
Event-driven architectures are increasingly replacing and outpacing less dynamic polling-based systems, bringing the benefits of serverless computing to IoT scenarios, data processing tasks or infrastructure automation jobs.
Unlocking new possibilities with Window Server containers and Azure Kubernetes Service.
Optimizing compute resource allocation to achieve performance goals while controlling costs can be a challenging balance to strike especially for database workloads with complex usage patterns. SQL Database serverless automatically scales compute based on workload demand and bills for compute used per second.
Starting the process of migrating to the cloud can be daunting. Legacy systems that are colossal in scale often overwhelm the average team tasked with the mission of digital transformation. How can they possibly untangle years of legacy code to start this new digital transformation initiative? Not only are these systems colossal in scale, but also colossal in terms of business importance.