Cloud computing has moved past its “self-centered teenage years” to become a “turbocharged engine powering digital transformation around the world,” – Forrester 

In today’s world, anything related to Cloud Computing is gaining attention and is becoming a trending market buzzword. This is because it is bringing innovative development services to enterprise apps and is no more – “just serving up cheaper temporary servers and storage”.

According to Gartner, organizations are moving away from the lift-and-shift strategy and looking to refactor or rebuild their cloud migration. It also says, more than half of enterprises already using cloud now will have an “all-in” cloud strategy by 2021. That means it will be a combination of multiple clouds and multiple cloud providers. As more and more workloads move into the cloud, the architecture around that becomes increasingly complex. Only Automation and related tools can help you to stay on top of all the systems. Gartner advises the companies to plan a clear roadmap for their cloud strategy henceforth.

As we look ahead to end 2019 on a good note and begin with “year of the future” 2020, what’s in store for Cloud Computing? How should large and small enterprises prepare themselves to embrace the competitive world of Cloud? What are the humming words to ponder by one who practices cloud?

A)The Rise of ‘Service Mesh’

New applications are taking the form of micro-services and they are built as interconnected containers. Thus the rise of the ‘Service Mesh’ – an emerging technology that connects, discovers, monitors and authenticates communications between containerized micro-services running across environments. A service mesh can help oversee traffic through service discovery, load balancing, and routing. It also helps in reducing the complexity of containers and improve network functionality.

With the release of AWS App Mesh and Istio(a project stemming from an alliance of Google, IBM and Lyft) saw the arrival of the ‘service mesh’. By 2020, it is a way out for organizations who look to unify traffic flow management, access policy enforcement and telemetry data aggregation across microservices into a shared management console.

That being said there is still plenty of room for innovation, and uncertainty, around the technology as more and more open-source service mesh are releasing online.

B)’Serverless’ Momentum Picked Up

“Serverless computation is going to fundamentally change not only the economics of what is back-end computing, but it’s going to be the core of the future of distributed computing” — Satya Nadella, Chief Executive Officer at Microsoft

Serverless computing referred to as Functions as a Service (FaaS). With serverless computing, a cloud provider manages the code execution, executes it only when required and charges it only when the code is running.

Several emerging and niche players are already delivering Serverless model independent of hyper-scalers like AWS, Azure or GCP, in which all the focus is on developer quality of life improvement. Developers can simply execute snippets of code without bothering about managing and provisioning underlying infrastructure.

Werner Vogels, Amazon’s CTO, described Serverless as the “next generation of how we are going to build the systems”.

Open-source frameworks like Lambda, Firecracker, Nuclio, OpenWhisk, Fission, and Iron.IO will accelerate and broaden the portfolio of how developers architect applications and manage APIs and SLAs.

It never means to eradicate server!

The developers can write code at the functional level and leave it with cloud vendor to decide how much cloud infrastructure is required to run it effectively. Companies don’t have to bother about the costs, admin, and threats involved in managing servers. But there can be the risk of the vendor lock-in.

C)’Micro-Services, Containers, and Kubernetes’ to Reshape Core Apps

Cloud computing adoption is not just making enterprises replace hardware-based systems, but they are taking out software-based systems too. Their virtual machines are being replaced by Cloud-Based Container Systems. It is like a respectful cause-and-effect relationship between micro-services and functional codes hosted over continuously improving cloud architecture.

Forrester estimates that a third of enterprises are testing containers for use in production; while 451 Research forecasts that the application containers market will grow 40% annually to $2.7 billion in 2020. 53% of organizations are either investigating or using containers in development or in production, according to a Cloud Foundry report.

These containers contain the entire package: an application, plus all its dependencies, libraries and other binaries, and configuration files needed to run it. DevOps officials are empowered with containerized deployment of their applications with great controls of flexibility and customization.

All prominent cloud solutions offer hosted versions of leading on-premises container platforms like Docker Enterprise, Google Kubernetes, Redhat Openshift, Tectonic, Rancher, Mesosphere, Amazon’s EKS, and Azure’s AKS for lightweight, quick deployment and highly flexible development operations.

D)’Internet of Things’ – Becoming Mainstream

Continuous innovation in real-time of data analytics and cloud computing has led to the Internet of Things (IoT) or more promptly internet-of-everything (IoE).

It enables machine-to-machine, machine-to-data, machine-to-human communication easier. A cloud offers benefits to IoT including speed, performance, and connectivity to other connected devices. IoT systems generate useful data based on the habits and patterns of users. The data generated by this new generation of device boosts the demand for cloud storage and cloud-based applications.

E)’Edge Computing’ – Reimagining the Cloud

Edge computing is purely encouraged by the growing trend of IoT-based applications. IoT requires collection and processing of big amounts of data in real-time and with low latency level. Edge computing is the practice of processing data on machines that constitute a vast interconnected network of IoT devices. It is called a distributed cloud infrastructure.

Organizations require near-instant access to data and computing power to serve their customers, and they are increasingly looking at edge computing to provide a suitable infrastructure.

IDC depicts it as a “mesh network of microdata centers that process or store critical information locally and push every received data to a central data centers or cloud storage archive, in an impression of under 100 square feet”.

This is another trend that does not replace the cloud but augments it and the critical time frame for organizations to adopt this trend is between 2020 and 2023.

F)’Quantum Computing’ – The Holy Grail for Global Tech Giants

IBM is competing with Microsoft, Google continuing its race with Intel. AWS and Azure have up the game. But on What?

To develop a first quantum system which will – resolve complex medical problems, seamless data encryption, weather prediction, and better financial modeling.

The day is nearing! It is predicted that cloud computing will introduce material science, mathematical and computer science theories to reality.

In November 2017, IBM began offering quantum computing as a cloud service when it released a 5-qubit and a 20-qubit version. JPMorgan Chase, Daimler Honda, Barclays, and Samsung were the first to sign up for testing.

Soon after that Alibaba joined hands with the CAS and launched an 11-qubit quantum computing service that is now publicly available on the cloud platform.

The global quantum computing market may be worth $1.9 billion in 2023, increasing to $8.0 billion by 2027 as per a recent report.

It uses quantum physics to increase the processing power of computers and users can access it using the internet.  Quantum mechanics can process massive and complex datasets quickly. Quantum computer can also break the code to encrypt electronic communications to reinvent cybersecurity. It improves the overall process and reduces the cost of hiring an additional IT resource.

G)’Machine Learning’ and ‘Artificial Intelligence’ – Fad or Future?

Machine learning has been the talk of the town since 2015. It has quite impressively grown all these years into a mature technology and a technique for achieving artificial intelligence and practicing data mining. This is making a new trend of business products under the label Machine Learning as a Service (MLaaS).

AI offers organizations the ability to automate, manage, scale and adapt to the changing needs of the business mainly by providing intelligent business functionalities. According to Gartner, global AI-derived business value will reach nearly $3.9 trillion by 2022. The amalgamation of both artificial intelligence and cloud computing is “The Intelligent Cloud”.

The two critical pillars of AI are data and compute. It’s capable of processing big data with greater efficiency and speed. AI has also automated businesses with the robotic process. It can help to reduce costs in a variety of ways, such as making simple tasks automated, preventing the duplication of effort, and taking over some expensive labor tasks, such as copying or extraction of data.

AI also helps in deploying across chatbots, recommendation engines, predictive analytics tools, voice-based interfaces, and automated security & management operations.

H)’Blockchain’ – Is It Worth the Hype?

Blockchain seems to be the most overhyped trend. Though many activities like bringing the server into cloud and enabling data analysis on the cloud can be done using Blockchain, most companies have better options like IoT or machine learning or container platforms.

I)’Opensource’ Continues its Reign

Opensource enterprise software has never been more popular as it is now. Many organizations are introducing opensource software into their processes and even building entire businesses around it. The cloud has ensured that the opensource ecosystem is thriving by relying on a large range of opensource DevOps tools, aggressive use of build automation and infrastructure platforms like OpenStack and Kubernetes.

As organizations continue to migrate their operations to the cloud, opensource will play one of the key parts in IT innovations beyond 2020. As per the predictions by Statista, opensource software income will grow to €32.95 billion by 2022.

IBM acquired Red Hat for $33 billion and Microsoft bought GitHub for $7.5 billion. There was a high-profile merger of opensource data platforms Hortonworks and Cloudera. Amazon EC2 and Google Compute Engine are built on opensource software.

So why the pricey acquisitions or service offerings?

Opensource development in the cloud offers easy access and use of resources. It also saves cost and reduces business risk. These cloud players want to deliver that functionality to their customers and remain in the competition.

J)’Cloud Security’ – Biggest Challenge

Cloud computing security is a set of policies, controls, technologies, and procedures working together to protect cloud-based systems, data and infrastructure. Massive regulatory shifts in 2018 (e.g., GDPR in Europe, new data privacy laws in India), made personal data protection an organizational priority, with severe financial repercussions in case of non-compliance.

Results from a recent survey done by Commvault showed that only a small number (12% of the 177 global IT organizations surveyed) understand how GDPR will affect their cloud services. With greater cloud adoption, data privacy and security will have greater attention and investment by 2020 and companies must realize it sooner.

Companies need to implement built-in controls such as identity access management, network security groups, gateway network firewalls, data encryption, threat intelligence, DNS filtering, and next-gen firewalls with contemporary computational models such as containers and serverless computing.

K) ‘Cloud-Native’: A New Wave of Digital Disruption

Many organizations who have migrated applications to the cloud, want to go “cloud-native”—meaning, creating apps with the cloud specifically in mind rather than sticking on to the old-world architectures. Cloud-Native Applications natively utilizes services and infrastructure provided by cloud computing providers, such as Amazon Web Services (AWS) or Google Cloud Platform (GCP).

Native Cloud Applications exhibit a combined usage of the three fundamental technologies:

-Computational grid – loosely, e.g. MapReduce
-Data grids (e.g. distributed in-memory data caches)
-Auto-scaling on any managed infrastructure

Organizations need to connect together various technologies, processes, and services of cloud-native to produce an outcome that has an actual business value. This can change the entire lifecycle of how requirements are collaboratively incepted, coded, tested and deployed.

L) Cloud Datacenters Changing into Ecosystems

The massive amounts of data being generated by people (social data), devices (including IoT, wearables, sensors) and enterprises (EDW, data lakes) will start to bring value through analytics. Many industries such as banking, healthcare, e-commerce, social networking and supply chain management have already undergone significant digital transformation. Datacenters are becoming integral to hybrid strategies of many organizations and transforming into an ecosystem.

Hardware will be commoditized and software abstracted to be consumed as a service rather than license based subscriptions. Overarching systems will also be able to manage software and hardware components from a single point, enabling task automation, self-correction, and operation.  This should result in targeted function based output and measured results, decreasing inefficient processes and redundancy. Data virtualization are accelerating this trend.

This will enable the automation of tasks such as updating equipment and patching, and the datacenters will expand and contract according to the size and type of the workload they are under at the time.

Social and Emerging Aspects of Cloud Software

By 2020, cloud computing software could involve programs forming automatic associations with software and hardware like in facebook or twitter. The database can look like a storage array or server. This empowers the developers not to worry about providing hardware such as a server, storage, and switch.

Currently, clouds are categorized based on models like – infrastructure as a service (IaaS), platform as a service (PaaS), software as a service (SaaS), mobile backend as a service (MBaaS/BaaS), function as a service (FaaS), or serverless computing.

By 2020, companies may see dynamic business process outsourcing (BPO) services and middle virtualization tools. There could be a rise of vendors providing specific cloud services enabling businesses to utilize cloud capabilities for specific workloads. This can lead to rise of a whole new set of cloud classes.

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