As we enter a crucial phase of the industrial revolution, where remote-work, BYOD, and CYOD has taken precedence without warning, tackling the challenges of cloud computing has never been more important. To provide context, digital transformation was set in motion thanks to the big data revolution. However, data democratization is almost impossible without the cloud.
Simply put, today, if start-ups, small-scale and medium-scale enterprises can thrive, the only reason is Cloud. One of the challenges of cloud computing is being able to allow smaller ventures to also enter the AI, VR, ML, and data analytics arena, as companies can rent infrastructure without having to flame out in capital costs.
- Cloud spending was at $24.65 billion in 2010, $80 billion in 2010, and will surpass $150 billion in 2020.
- 67% of enterprise infrastructure will be cloud-based by the end of 2020.
- 83% of workload will reside in the cloud by 2020.
- The average person interacts with approximately 36 cloud-based services each day
This means that the shift to the cloud is inevitable for any organization. This article isn’t intended to poke holes at cloud computing as against traditional infrastructure solutions. It is merely a timeline representation of challenges of cloud computing and the crucial decisions that the ITpreneurs, stakeholders, Change Managers, and ITSM Managers of today and tomorrow will undertake during the transitional phase.
First things first, choosing the infrastructure:
Choosing the base for deployment is the first step towards moving to the cloud.
Deployment Types Include
1. Private cloud
Private cloud infrastructure is solely dedicated to the data of one organization alone. This may mean that companies with existing hardware data infrastructure are merely moving their hub to the cloud, but maintaining their own on-site centers.
Some third-party services also provide private cloud infrastructure in such a way that a private network is a sole gateway to accessing data from the cloud.
A private cloud requires higher capital costs than traditional data centers but is necessary when organizations want to be able to provide remote access to their employees and customers. It is the only choice for organizations that are required to prioritize security by law, such as government organizations, military centers, IBFS enterprises, etc. Since private clouds are in absolute control of the organization alone, scalability and security are of the highest order here.
2. Public cloud
In contrast to the private cloud, public clouds share external infrastructure. They are the go-to choice for start-ups and medium-scale ventures who wish to make use of more massive computing capabilities without having to shell big bucks on purchasing and maintaining on-premise hardware. Microsoft Azure, Amazon Web Services and Google Cloud are examples of the public cloud.
The public cloud allows companies to become remote-ready in no time. However, security may be compromised, and it is not advisable to store critical data on the public cloud.
Given that you can expand infinitely and keep purchasing more shares of the public cloud, the point of scalability becomes moot. In the same light, entrepreneurs must have a fair idea of how much they want to purchase upfront, how much leeway they want to provide for scaling, and how much they want to bank on the pay-per-use schemes.
These challenges of cloud computing ring especially true for start-up ventures, which often will have to negotiate deals and zero-in on one choice from a myriad of confusing schemes that various public cloud providers present in order to maintain low costs.
3. Hybrid cloud
An answer to the scalability, security, and cost challenges of cloud computing in private and public deployments, hybrid cloud is the best-of-both-worlds model. Here, sensitive data is stored in a private cloud using the on-site infrastructure. But, non-critical workloads and resources are hosted on the public cloud. This way, scalability is simple for both arenas.
As they say, though, every cloud has a silver lining. Getting the public and private clouds to interact seamlessly is one of the challenges of cloud computing that the IT team will have to tackle. Hybrid has its drawbacks, and its popularity has decreased by 7% between 2018 and 2019 according to a Gartner survey.
In multi-cloud arrangements, two or more cloud vendors are employed by organizations. A company could be using multiple public cloud vendors like Microsoft Azure, AWS, and Google Cloud environments apart from their own private cloud to execute the various functions of the organization. While this may seem tedious, a multi-cloud strategy is fast gaining traction. In fact, 81% of organizations already have a multi-cloud strategy laid out.
It would be quite reckless to call multi-cloud a strategy at times because the reason behind organizations using more than one vendor is not just for flexibility in terms of functionality. Using the multi-cloud method is a consequence of organizational needs to break themselves from the clutches of having to rely on a single provider, effectively reducing downtime and data loss.
Selecting the Service Mode
Once the cloud infrastructure model is developed, and the vendors are chosen, organizations will be required to define the depth of their relationship with the infrastructure-provider.
1. Infrastructure as a Service (IaaS)
IaaS is a wholly contained self-service model. Here, organizations are given access to servers, networks, OS, and storage using virtualization technology. Companies have sole control over monitoring computers, networking storage, and other services. They can choose to include more resources on-demand.
2. Platform as a Service (PaaS)
Apart from the infrastructure, PaaS lays out a foundation for developers to build software that may mainly be used for applications. Servers, networking, and storage are maintained by the third-party service provider. Scalable middleware applications are the biggest argument for PaaS. These can be construed as long-term solutions for cloud service providers.
3. Software as a Service (SaaS)
This is the most commonly utilized cloud market. It uses the internet to deliver applications that are managed by third-party vendors. Many SaaS applications run directly on a browser. SaaS is rudimentary and gives no control to the organization. Small eCommerce firms, short-term projects, and seasonal projects are often undertaken in SaaS mode.
Companies can use a combination of vendors to perform various functions within the organization.
Migrating to the cloud
The real challenges of cloud computing are encountered when the process of migrating to the cloud commences. To make the transition smooth, organizations need to consider a variety of factors. But the foremost among them is investing in bandwidth. Connecting to the cloud requires adequate bandwidth availability to ensure that there are no compromises. Companies often find it challenging to address bandwidth requirements without allocating monetary resources to this crucial aspect.
Companies also need to be prepared for extensive troubleshooting, slow data migrations, working with agents, and preceding sophisticated features to ensure lower downtimes.
One of the major challenges of cloud computing that large organizations are facing today is finding a point of Zen between on-premise and cloud infrastructure. Not all data and resources can be moved to the cloud, but all customer data requires to be accessible from the cloud. Hands are needed to ensure that on-premise infrastructure is maintained, and customized cloud computing environments are being built while ensuring that normal business operations are being carried out smoothly.
Addressing IT management
While transitioning existing applications to the cloud, data breach and leakage are also causes of concern. It is ensuring readiness before the transition is of utmost priority. Choosing service providers who can equip organizations with a robust set of tools and services that provide adequate performance-monitoring of applications on the cloud is also important.
Companies can choose to have in-house IT teams to ensure readiness, but it may be preferable to employ third-party services as upskilling existing IT workers to new cloud environments takes time. Many organizations today are equipping themselves with cloud experts while also using third-party services for IT solutions for the time being. This is because deploying to the cloud has become a race against time, but reliance on third-party vendors will incur higher costs in the long run.
In this regard, versatile tech professionals who can adapt to changing environments and are equipped with the skillset to carry organizations through forthcoming changes are at a substantial advantage in today’s world. In fact, cloud architects are the third most in-demand workers/jobs of 2020.
Dealing with immature technology
While the advantages are all fine and dandy, it should be noted that we are dealing with new technologies that are yet to saturate in terms of innovation. Artificial Intelligence, Machine Learning, Big Data, Augmented Reality and Virtual Reality are continually making the impossible a little closer to reality. We encounter these applications in our day to day life, from cancer detection to road-traffic management.
But, many of these applications are still nascent, and often seem to be throwing curveballs where no problems seemed to exist. They also very often underperform and underachieve. So, cloud computing remains underutilized. Adjusting expectations requires a modicum of leniency both in terms of morality and cost-considerations. While vendors clamor to provide service and invest profits into more R&D, being patient but cautious becomes key.
In the same regard, introspection is also crucial to ensure that the boundaries of innovation and creativity are always being pushed while accepting existing internal limitations.
Maintaining and optimizing performance
Cloud and on-premise are poles apart in terms of functioning. Most companies opt for using a CDN – Content Delivery Network. Organizations must ensure that employees are reskilled and upskilled adequately to undertake the mammoth task of migration. Existing employees need to undergo training to ensure staff efficiency. Having cloud experts on board will go a long way in determining whether an organization is taking full advantage of cloud computing.
Many companies are also investing in talent transformation programs to ensure resource-readiness. Several others are also turning to DevOps tools to monitor cloud usage patterns solely for the sake of optimization.
Ensuring a tight grip on data security
Setting up role-based access, minimizing endpoints, ensuring third-party reliability, preparing for BYOD, CYOD, and remote work without compromising on the privacy of employees or customers is of utmost importance while dealing with the cloud.
Security is often touted as the biggest roadblock to a smooth cloud transition, as the place where your data is mainly stored remains in the unknown. Increasing data breach and hijacking incidents that compromise company credentials have not made things any easier to digest.
However, there is no cause for concern as all laws are maintained and adequate red team vs blue team campaigns are carried out by organizations. As more organizations hop onto the cloud, cybersecurity automatically gets more robust.
One of the ways to tackle the security challenges of cloud computing is to mandate multi-factor authentication across the board. Cumbersome as it may be, until the eye of the storm collapses, being as cautious as possible is crucial. Companies should also invest time in training employees as well as customers about the importance of maintaining the best safety practices.
Passwords and usernames must be changed regularly, and encryption systems must be put in place. Setting up cybersecurity policies before even transitioning employees and applications to the cloud must be given priority.
Controlling cloud spend
The backbreaking work of today’s risk analysts and change managers, controlling cloud-spend, especially with the advent of multi-cloud is one of the main challenges of cloud computing. As mentioned before, tracking and forecasting usage are so critical that sometimes, it can crack the spine of a transitioning company if not estimated correctly.
Making use of financial analytics tools is one way to tackle the issue of pay-as-you-go vs. upfront cost calculations. While pay-as-you-go is slightly more convenient, choosing smaller upfront payments also comes with a downside – the vendor lock-in period. Lock-in periods bar organizations from switching applications between clouds and this are where the trouble with surmounting costs begins in the multi-cloud environment. Negotiating vendor lock-in periods must insure against downtime.
While the infrastructure in itself is affordable, making it function is where the costs seam to soar. Integration with third-party security and management vendors needs to be done with care. One must understand that those cost computations are multi-fold – even increased downtime leads to diminishing ROI.
Unless companies choose IaaS, the IT team will not have complete control over delivery, positioning, and operation. In this regard, the role of IT has evolved to several degrees of complexity, especially when companies are working with so many third-party vendors.
Setting up IT protocols that are closely parallel to maintaining traditional infrastructure is also necessary. The core IT team must also be part of the entire cloud movement, right from the get-go, as they will likely be able to pin-point many of the company’s special needs before making purchases.
Another one of the significant challenges of cloud computing is having a handle on legal issues. Maintaining industry-standard practices, regulations, and laws come up when it’s time to choose backup services. In recent years, there has been a surge in the hiring of data protection officers for this very purpose.
Government rules are evolving at a rapid pace and many times will work against the company’s favor. It is also one of the causes for a sudden increase in expenditure. To ensure that no downtime occurs simply because legal obligations are not met, having dedicated personnel to look over such matters can be quite handy.
As always, though, Europe has been on top of such matters, and more countries are likely to follow suit. The EU General Data Protection Regulation has vowed to make compliance easier in the future. Data Protection Officers have now been mandated by GDPR law so that compliance responsibilities are centralized.
Check out: Cloud Engineer Salary in India
Common troubleshooting problems
While the above points cover the main aspects to document while transitioning to the cloud, some small glitches could also come underway once the cloud starts performing.
Below is a list of common issues that companies encounter while dealing with the cloud:
Many times, companies have to face challenges like moving applications from on-premise Windows-based environments to cloud-based Linux environments or vice versa. In such cases, some functionality may be lost. Portability needs not to be a limited OS. Such unforeseen challenges may prop up while undertaking any form of data or application movement.
One way to tackle the challenge is to restrict dependencies in the source atmosphere. Although it may take time, it is possible to reprocess almost any data or application to fit a new environment given the right set of tools.
2. Developing new architecture
As of today, almost all cloud infrastructure is housed in substantial commercial data centers that are controlled in a centralized manner. This has many advantages as it can be scaled and managed efficiently. But, some challenges in heterogeneous environments remain, while new architectures are incentivized.
Although it may seem quite astonishing, the availability of cloud infrastructure is now posing a threat to many migration processes. This is because the upsurge in the cloud has not been gradual. In such cases, choosing the right service providers will require much deliberation but it also opens up the possibility of negotiations tending to the enterprise’s favor.
4. Lack of standards
While scalability can be addressed quickly with multi-cloud infrastructure, the same solution brings with it another set of challenges. Since every cloud service provider has its own set of protocols, and there are currently no performance measurement facilities for the service providers themselves, a havoc situation is becoming increasingly evident. While this problem should subside with the entrance of compliance regulations, currently, the situation remains in a messy transient state.
For those using IaaS, choosing environments that meter performance, and employing third-party vendors to perform this role is inevitable. Yet again, with multi-cloud, lack of standardization brings with it another set of challenges in cloud computing.
6. Energy efficiency
Especially for global firms, cloud environments always function in on mode. But this can lead to extreme inefficiency in terms of energy usage. Data centers, especially of those in a private cloud, must use the latest energy equipment to ensure the minimization of expenditure and conservation. This aspect may seem silly, but climate change and the energy crisis along with the need for uninterrupted data usage has made this question quite relevant today. Many innovations are underway to address these challenges.
6. Denial of Service (DoS)
As of today, many cloud-computing firms are relying on manual intervention to deal with DoS attacks. But, what happens if a heavy attack is underway? Is investing in DoS protection necessary? These are some of the questions that companies will need to decide for themselves in the near future until compliance mandates it.
Many firms today are also asking the question as to whether the core cloud infrastructure in itself is reliable to undertake migrations. To close these loopholes, AI is heavily being employed by cloud service providers.
AI is increasingly being embedded into IT infrastructure. So much so, that many organizations predict that as AI becomes more sophisticated, AI will not only be able to monitor and manage cloud instances, but even self-heal! Initially, though, AI is being used to automate and streamline some workflows and other routine processes. Over time, analytical features will gain momentum.
AI is also being used to manage data within the infrastructure for tasks like identification, ingesting, cataloging, and so on. Data management using AI is a hot field. In fact, banks that require handling transactions are already using such tools for updating data.
AI tools that integrate with SaaS offer great functionality to users and are aiding the process of migrating to the cloud significantly. One such example is Salesforce Einstein, which was unveiled in 2016. Einstein helps users connect to engage with customers. It sets up calendars, provides sales members with follow-up updates, automatically pings users, identifies customer behavior patterns, and much more. This recommendation tool is one to look out for!
In the end, choosing to stay on-premise is as crazy as using a 300-year old treasure chest to store all your money, while the rest of the world is making financial transactions on their cell-phones.
With changing technology, adequately skilled cloud experts and change managers are the need of the hour. If you think you have what it takes to upskill yourself and help organizations transform through these tidal changes, check out Machine Learning in Cloud program from upGrad! With upGrad’s courses, you can equip yourself with the know-how of tackling the challenges of cloud computing, and become an integral part of organizations- both large and small.