What is CloudOps vs. DevOps? What is CloudOps? DevOps links with cloud computing are easy to define. The centralized nature of cloud computing provides DevOps automation with a standard and centralized platform for testing, deployment, and production. DevOps Training Online
What is DevOps? DevOps is the practice of operations and development engineers participating together in the entire service lifecycle, from design through the development. DevOps is a term for a group of concepts that, while not all new, have catalysed into a movement and are rapidly spreading throughout the technical community. DevOps Training in Hyderabad
What does CloudOps offer DevOps teams? Contrary to traditional IT infrastructure and NOC-based org structures, DevOps creates an agile process for the rapid delivery of reliable services. It doesn’t eliminate the need for IT experts and software developers – it just brings them closer. Distributed, stateless and scalable: Capacity planning and asset management becomes virtualized. You can quickly spin up new servers or remove unnecessary storage. You can set rules to auto-provision servers in order to keep up with demand and maintain uptime. Also, CloudOps helps you monitor key performance metrics and quickly act from anywhere – increasing the flexibility and scalability of the underlying applications and infrastructure. Fault and latency tolerant: Because of the flexibility and scalability of cloud services, cloud-based applications and infrastructure are less prone to latency and error. Because cloud-centric applications and services can abstract themselves from the underlying infrastructure, your system becomes more tolerant to error.
Data redundant: In CloudOps, your data is much more protected from failures. Cloud-based environments provide tons of opportunity for data storage in multiple physical and logical locations – offering more failover options and protection from data loss. Data is stored in different locations and can be stored in multiple different ways, helping you remove single points of failure – leading to fewer dependencies and a more resilient data pipeline. Automated: You can create more robust self-healing systems and implement more automation across every part of the SDLC. By using IaC (Infrastructure-as-code), you can program more automated functions and use your infrastructure to perform commands and tasks based on monitoring thresholds and other key performance metrics.
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