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Cloud Computing Trends 2022

Β· 11 min read
Stephane Boghossian

Trends are among the things we monitor, here at Brainboard.

For the past few years, we saw the Cloud shifting course towards a more sustainable long-term future. According to predictions from Gartner, global spending on cloud services is expected to reach over $482 billion in 2022, up from $313 billion in 2020. That's promising for the industry!

Lets deep dive into the trends that matter for the Cloud Computing industry and how they can help shape the industry, in the next year or so.

A fight for a sustainable cause 🌎#

Green Cloud

According to Forbes, the effects of climate change with cost companies up to $1.6 trillion per year by 2025.

Among trends we look upon, building a sustainable cloud infrastructure & electronic / hardware waste is another area of growing concern, as aging hardware is being discarded in the tens of millions of tons every year. According to Quartz, we risk shortage in rare earth minerals and production cycles are at stake. The need for robust recycling of computer hardware is growing by the day, possibly reducing energy usage associated with increasingly powerful computing engines that need larger digital storage requirements, without mentioning energy costs related to running a 24/7 'always-on' service to customers.

So, as every industry is reshaping their production cycles by implementing measures and innovations, the aim here is to keep helping businesses achieve their net-zero carbon aspirations. Some leading industry actors even pledged of moving their business and expansion over the world towards a 100% renewable energy.

As a source of example,

  • πŸ‡«πŸ‡· Scaleway has recently launched a new eco-responsible datacenter using DC5 -- an Hyper-Scale Mechanical-Cooling Datacenter. You can find more information here. Compared to the DC3, the DC5's PUE is measured at 1.22 (versus 1.34)
  • Amazon, the world's biggest cloud company (and our Partner) is the world's biggest buyer of renewable energy, running a 206 sustainable energy projects worldwide, generating around 8.50W per year. They are not stopping here, tackling around reducing the downstream energy usage created by their products, for a greener home.
  • πŸ‡«πŸ‡· Capgemini, Orange and Microsoft partnered to create Bleu, an initiative around building the future of the cloud, more inclusive.
  • πŸ‡ΊπŸ‡Έ Google recently implemented historical weather data to preempt server farm cooling needs.
  • πŸ‡ΊπŸ‡Έ Microsoft is experimenting with aquatic data centers, letting the vast ocean absorb the heat.
  • πŸ‡¨πŸ‡³ Huawei Cloud is planning to deploy five regional centers and over 30 city nodes across China with the new Huawei Cloud Prefabricated Modular Data Center. Have a look, it is impressive how the whole datacenter is constructed in 13 days rather than 6 months.

Trust in Hybrid Cloud models πŸ˜‡#

Paradigm shift

Hybrid models blur the distinction between public and private clouds.

AWS or Azure servers and their various tools for businesses and end-customers help manage the accessibility of data over the Cloud. More sensible or mission-critical data is kept in private servers, where access is constantly monitored and processes by proprietary applications.

The avenue of multi-Cloud environments (several different suppliers) allow businesses to manage their infrastructures across different suppliers, choosing what best suits them from each.

An Hybrid Cloud approach can reduce the complexity thanks to the emphasis put on streamlining the user experience and keeping the tech stack invisible, deciding when needed not to be seen by third parties.

We can see 4 micro-trends with existing use cases to discover:

  1. Cloud-native platforms allow you to build new application architectures that are resilient, elastic and agile, enabling you to respond to rapid digital improvements. It improves the traditional lift-and-shift approach to Cloud, adding complexity to maintenance.
  2. Serverless offers like AWS Lambda, Azure Fuctions or IBM Cloud Fuctions offer a new pricing model, pioneering business models: fuctions-as-as-service allow businesses to truly pay-as-you-go where the infrastructure scales invisibly as an application requires it. This allows not to be tied into leasing servers or paying for fixed amounts of storage or bandwidth. Serverless doesn't necessary means serverless β€” the servers are still here β€” but adds another layer of abstraction between the user and the platform, not involving the user to configure almost anything and manage IT technicalities.
  3. With an open-source innovation platform, organizations can see various advantages. They can rapidly scale their cloud framework, adding highlights is a lot less difficult than with a shut source stage. Fewer security concerns rise and the effect on rapid market push is effective, in some cases. The tech business is moving to a shared workplace and settling on an open-source distributed computing administration to scale properly and control every aspect of their businesses.
  4. Human Cloud are talent platforms that give business on-demand access to the workforce, connecting skilled workers to various roles, develops crowd-based networks of staff recruiters and giving multiple resources at low overhead cost. Such cloud-based platforms contribute to greater labor compliance and quality than contemporary staffing norms. With the pandemic, the marketplace is likely to go deeper into the cloud as it offers businesses a clearer picture of skill sets and opportunities.

Data Management πŸ“Š & Automation πŸ€–#

Data Management, among other things, is a key to unlock opportunities, for both Cloud Providers or companies using their services.

More complex infrastructures and managerial models are everyday discovered, with added complexity into components, workflows and the appearance of hyper-automation.

We can see 8 micro-trends with existing use cases to discover:

  1. Data fabricΒ provides a flexible, resilient integration of data sources across platforms and business users, making data available everywhere it’s needed regardless where the data lives. Data fabric can use analytics to learn and actively recommend where data should be used and changed. This can reduce data management efforts by up to 70%.
  2. The Industrial Internet of Things (#IoT) Architecture, cross pathing between Cloud and Big Data, is arising some concerns. With the coming of soon-to-be 5G or Wi-Fi 6E, we can see new types of data that can be steamed over. We clearly can see this shift with the Cloud Gaming platforms (Google's Stadia and Amazon Luna), among the most shaken industry, with the arrival of augmented reality (with more accessible headsets) in Social interactions and experiences.
  3. Blockchain's decentralized system are refining every industry out there, including but not limited to the Fin-tech industry, with direct effect into the Cloud. As both the Dark and Open Net is for the first time challenged by both the users and the businesses launching their services online, the challenge here is to integrate these complex decision-making tasks into workflows, without a direct impact into the data collected.
  4. Machine learning platforms require huge processing power and data bandwidth for training and processing data. Most of everyday AI we see around us (Google Search or Instagram filters) lives in the Cloud and the technology that routes traffic from data centers to our phones, laptops or other smart devices is built on machine learning. The development and the evolution of AI is inextricably interwoven. 'Creative algorithms' can generate anything from art to synthetic data to train more. Language modelling increases the accuracy with machines and understands human languages. That could also improve management of these complex infrastructures and allow users to improve their experiences online.
  5. Hyper-automations is a business-driven approach to rapidly identify, vet and automate many businesses. It simplifies several aspects of managing any business like enabling scalability, remote operation and business model disruption. Functions like dashboards allow you to see different activities in one window while providing avenues for machine learnings. This means, the organization will gather even more data, creating even more complex business models around that idea.
  6. Services like Docker or Google's Kubernetes offer users the advent of containerized applications, making applications ready for the Cloud faster, changing monolithic legacy applications to microservice-based architecture, managed through an orchestration platform. In aΒ Gartner news report, they stateΒ that containers have become popular because they provide a powerful tool for addressing several critical concerns of application developers, including the need for faster delivery, agility, portability, modernization, and life cycle management.
  7. Composable applications are built from business-centric modular components, making it easier to use and reuse code. It generally accelerates the time-to-market for new software solutions and improving business value.
  8. While we fetch structured and unstructured data from nearly everyone β€” machines, people, assets, plants, cars, appliances, etc. through wearables, RFID tags, cameras, sensors, and satellite images β€” enabling to complexity of data distribution to get meaningful insight. Edge computing can help manage the load distribution, building data storage and processing capabilities on the edge itself. The classic example can be enabling use cases like automated cars, adaptive traffic control systems and content delivery for faster video streaming.

Limitations & freins#

Cost control πŸ€‘#

As Andreessen Horowitz said, the cost of the Cloud matter, with the complexity of data processing and infrastructures.

Keep a close watch on your monthly bills to optimize your costs across the Multi-Cloud services (you are using or planning to use) as Cloud providers are leaders of the industry.

Fortunately, there are two ways to optimize your cost:

  • Scheduling your monitoring β€” For that specific task, you'll need to understand at what time how much IT resources are being consumed, related to what tasks you're telling the computer to do.
  • Size of the resources β€” It is important to keep track of how much compute, memory and storage per virtual machine is being used by your applications and accordingly, before or after the deployment, keep on re-sizing your resources.

Some tools and platforms already exist for these specific reasons, to give visibility and control across your multi-cloud environments, pre-building a set of scenarios for you.

Cloud Governance πŸ”‘#

It is a shared responsibility to protect data on the Cloud and on-premise between organizations and cloud service providers. All major Hyperscalers (AWS, Azure, and Google) offer data encryption (source and in flight) as a part of their managed services.

Organizations must plan for a very robust data protection policy (backup and disaster recovery) to make sure there are enough copies of data available in case of any breach. We recently saw rising funding in Cybersecurity startups, aiming to protect your business risks, online.

  • Privacy-enhacing computation secures the processing of personal data in untrusted environments, which is increasingly critical due to evolving privacy and data protection laws as well as growing consumer concerns. It allows you to still extract data while still meeting compliance requirements
  • Data recovery raises great concerns, when we hear about recent cyberattacks, information blackouts, and framework failures. Most organizations have managed their servers crashing, prompting the loss of important information documents. To guarantee such issues don’t harm the association and its processes, reinforcement and disaster recovery have turned into a trending use instance of the cloud.

Brainboard for 2022 πŸš€#


As a courtesy of reminder, Brainboard is an ecosystem, combing workflows, complex components and multi-Cloud providers, around offering a seamless experience building your Multi-Cloud infrastructures. It is true that designing any infrastructure is a 1-hour task with Brainboard, rather than taking a week to do so, managing multiple parties, a significant number of tools and complex tasks releases, under-pressured by your Product Team.

We are fighting everyday in reducing risks and consumptions-based models for businesses and build a sustainable infrastructure, agile and scalable, ready for any use case. We know that complex AI or Blockchain infrastructures are birthing every day, and we are ready to host any, for the sake of the challenge.

Whether you are using complex components, multiple Cloud providers or workflows for your infrastructure, Brainboard allows you to manage your environments, with a smart all-in-one solution. We believe in offering an encompassed ecosystem for everyone to ease every stage of the development, not limited to deployment capabilities. We constantly improve our capacities to integrate commonly used tools like GitLab, Docker or Kubernetes, prioritizing hyper-automation and human-involvement actions.

Furthermore, we also value data privacy, so hosting your data in-house is important for the future of protecting the value behind your applications.

Cost control is an obvious way to improve optimization of infrastructures and we, later on, will include important insights around that specific need.

As we always like to say, building a simplified complex multi-Cloud blueprint is the logic next-step for our vision of the Cloud Computing industry.

We won't offer a virtual service to design a Cloud infrastructure using an AR set yet πŸ˜‰ (Meta [ex-Facebook]) but we are improving, day-by-day, our solution, load-balancing between reality and virtual world.

Brainboard is an engine for all your Cloud services, and we intend to keep that promise for 2022.

Happy Brainboarding!


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