Cloud computing refers to the provision of IT infrastructure and platform services to provide a flexible, scalable, and on-demand IT environment. At the simplest level of abstraction, it may refer only to IT infrastructure, such as a remotely hosted server (or bare metal), while at the furthest level of abstraction, it refers to a remotely hosted software application together with all the computing elements required to provide that software.
Listed below are the key technology trends impacting cloud computing environments, as identified by GlobalData.
Hybrid IT management optimisation
Organisations have embraced both more virtualised operating models and infrastructure. With this evolution, enterprises are becoming more comfortable with using third-party cloud and hosting services to support some application workloads while retaining control of other aspects, either on their own premises or in a co-location facility. This amalgamated approach is driving the need for technology and best practices to ensure organisations design, deploy, and optimise the management of these hybrid environments.
The DevOps model
Cloud technology breakthroughs support digital transformation projects through cost savings, improved efficiency, agile application development, and simplified deployment. They use modern microservices and serverless architectures, which reduce infrastructure configuration complexities. Those are largely enabled through cloud management technologies that adhere to key open source software applications. With OpenStack players entering, the DevOps model will be further shored up via infrastructure integration such as security, helping promote autonomy and automation.
Application lifecycle management (ALM)
Infrastructure providers are moving up the cloud stack, beyond private or hybrid models, and into technologies that use ALM capabilities to help support a DevOps model that orchestrates the whole application and platform ecosystem of technology across the entire lifecycle. Technologies such as security and application performance monitoring (APM) play an important role in filling out ALM solutions, also known as application and platforms lifecycle management (APLM).
After significant delays in the adoption of a microservices architecture due to configuration complexities, innovations in the form of new tools and frameworks have triggered an interest among infrastructure and cloud providers to integrate service mesh technologies into their management solutions. This will be followed by increased demand for a serverless computing architecture for supporting platforms and pricing that scale up with application demand and scale down to zero when not in use, leaving server management to the cloud provider.
Open source software (OSS)
Open source software (OSS) is highly relevant to cloud computing for its community culture and shared technology, agility, and interoperability. Its momentum has enabled the cloud’s advanced technology development more so than any vendor or service provider could have achieved independently. Key initiatives were formed on OpenStack, the de facto standard for private cloud deployments (launched in 2010), and Cloud Foundry, the de facto standard for public cloud (launched in 2013). Since then, containerisation and orchestration have largely been successful due to industry-wide acceptance of Kubernetes.
Automation and orchestration
Kubernetes played a large role in the trend towards orchestration and management of modernised application deployment through containerisation. The movement to ease operational management and automation has increased over the past 12 months, as traditional data centre vendors have begun partnering with cloud providers to help abstract complex configuration requirements. The aim is to help enterprises move modern apps into production and keep pace with large-scale digital transformations more easily through automatic software updates and ALM across various cloud environments.
Enterprises are deploying data centre resources such as compute, storage, and data management and analytics software at the edge of their operational footprints, to support applications that require high levels of performance and low latency, and to manage and process data associated with IoT initiatives. Edge computing will complement traditional data centres and the use of cloud-based IT. In many cases, enterprises will rely on cloud consumption models to access edge IT resources.
Several issues are behind the rapid advance of multi-cloud environments, in which an organisation uses the on-demand infrastructures of multiple providers to support a common application or applications. Enterprises were drawn to this model as a way to ensure redundancy and also avoid cloud lock-in. Regulations might also require organisations to store data in certain geographies or nations, requiring the use of multiple cloud providers. The challenge is managing these heterogeneous environments as if they are a single architecture. Some vendors and service providers offer solutions to streamline the management of workloads across multiple cloud service provider platforms.
While compliance does not equate to security, it can provide a framework for developing best practices. New regulations on protecting data privacy are pushing organisations to re-evaluate their controls and the technologies they apply to safeguard critical information such as encryption. However, organisations still struggle to execute effective cloud security and maintain consistent compliance between audits.
This is an edited extract from the Cloud Computing – Thematic Research report produced by GlobalData Thematic Research.