The landscape of technology is rapidly shifting, with cloud infrastructure and platform services revolutionizing the way businesses operate. Self-hosted solutions are gradually giving way to the cost-effective and streamlined approach offered by the cloud.
With automated processes, robust backups, and pre-installed tools, cloud environments can provide unparalleled convenience for users. Moreover, they require less effort to maintain stability compared to traditional, locally deployed servers.
Over the years, the CyberVision team has accumulated extensive cloud development and migration expertise, which we are ready to share with you in our article. Let’s explore the main types of cloud services, highlight popular cloud service providers, and discuss the key roles in a cloud solution-building team.
What is a cloud service?
In the world of technology, cloud services have emerged as game-changers. But what exactly are cloud services?
According to Gartner, cloud services are highly automated and standardized packages where built-in platform services fully manage the majority of infrastructure resources, such as computing power, connections, and file storage.
The best cloud services are scalable and easy to expand with a pay-as-you-go model. They allow businesses to effortlessly scale their operations as needed, providing cost-effectiveness and agility. Moreover, leading cloud services offer the convenience of managed databases and applications, empowering users to choose from a wide array of pre-installed tools tailored to their specific requirements.
Operating through intuitive custom user interfaces, cloud services provide authorization options that cater to both single-tenant and multi-tenant environments. This flexibility ensures seamless integration into existing infrastructures. Additionally, real-time analytics capabilities enhance decision-making by providing valuable insights into system performance and usage patterns.
The benefits of cloud services
Cloud development services: Main types
New application development
In the application delivery pipeline, engineers first define requirements. After selecting tools and technologies, they set up the solution environment and design the application. Deploying to the cloud and implementing application logic is one of the toughest parts, which requires detailed testing and debugging.
Once the application is up and running, the next crucial step often involves integrating new external services or functions into the application ecosystem. This integration expands the application’s capabilities and enhances its overall functionality. Continuous monitoring and optimization play a vital role in ensuring the long-term success of the application, allowing for efficient performance and scalability.
Below, you can see popular cloud services for application production.
- APIs and microservices - Build modular and scalable applications that can be easily integrated and extended.
- CI/CD / backup apps - Streamline the development process, ensure seamless updates, and provide reliable data backup.
- E-commerce / web applications - Facilitate secure transactions, robust content management, and scalable infrastructure.
- Content / streaming apps - Support content delivery, streaming, and efficient management of the media assets.
- Communication applications - Enable real-time messaging, video conferencing, and collaborative functionalities.
- Data analytics, AI, and ML apps - Build intelligent applications powered by data analytics, artificial intelligence, and machine learning.
- IoT applications - Operate secure data storage, device management, and real-time analytics.
- Mobile app backend building - Provide scalable backend infrastructure and services for the mobile app.
Cloud migration
In today’s digital landscape, companies have the flexibility to seamlessly migrate their applications and data to the cloud while ensuring uninterrupted operations and processes. As part of this migration process, they can choose to transfer PostgreSQL/MySQL databases with zero downtime, ensuring the continuous availability of critical services and applications. Moreover, data transfer between legacy databases and cloud storage may also be necessary to facilitate a smooth transition.
Cloud migration services offer more than just cost estimation and guidance. They encompass a range of steps, such as automating data movement into BigQuery, modernizing outdated databases, and integrating diverse database types. By leveraging these services, organizations can eliminate the challenges associated with shifting workloads and unlock the scalability they require.
Data analytics implementation
It’s no secret that intelligent data collection and analysis is a rapid pathway to business growth, albeit a complex one. Harnessing the power of advanced data analytics requires a multidimensional perspective and intuitive insights from a data expert who can identify patterns and transform them into actionable trends.
To implement analytics successfully and extract valuable insights from data, a secure and robust data processing and storage infrastructure is crucial. This entails creating projects, implementing various tracking codes, consolidating data into containers or databases, establishing effective processing techniques (as a significant portion of the data may be irrelevant), and exploring insightful reports.
Data privacy and protection of private data are paramount considerations in data analytics implementation. It is vital to ensure compliance with data governance policies and privacy regulations in your location and the locations of your customers.
Data management for multiple apps or services
Fully managed database solutions and services offer centralized data management for multiple apps and services. Embracing unified and robust cloud solutions enables businesses to securely grow their operations while benefiting from cost-effectiveness, as managing data on bare metal infrastructure can be overwhelming for beginners.
Cloud solution providers often facilitate the migration of application data from traditional databases to cloud-native counterparts that can seamlessly scale to accommodate evolving needs. Data management is a critical component of any cloud project, empowering organizations to drive innovation for their clients through a wide range of options, including open-source technologies.
AI/ML pipelines integration
Incorporating AI/ML pipelines into applications to enhance user experiences may seem like a marketing buzz, but it can truly revolutionize the way we interact with technology. Whether it’s enabling chatbots, text analysis, or working with various types of media, AI/ML applications have the potential to be game-changers for user experience.
When embarking on an ML/AI project, you have two options: utilize ready-made tools through subscription services or build your own models using open-source toolkits. Modern cross-platform networks simplify the development of ML and AI applications that can run seamlessly across multiple platforms. However, it’s important to note that such applications require substantial computational resources to ensure optimal performance.
For companies that have already integrated AI/ML into their operational processes, cloud services offer valuable assistance in managing these applications at scale or even transitioning them to on-premise environments.
Cloud services workflow
To effectively utilize and manage cloud resources, it is crucial to understand the workflow involved. Here are the key steps.
Deploying to new instances
The process typically begins by selecting the appropriate instance type or size based on the required computing resources, including CPU, memory, storage, and networking capabilities. These choices can be adjusted to align with your budget. Additionally, cloud providers offer a range of services that simplify the deployment of complex software solutions.
For example, many providers allow you to deploy a well-configured Kubernetes cluster with different setups that can cover various use cases in a matter of minutes without extensive support from DevOps.
Similarly, cloud providers offer built-in support for popular databases like Postgres, MongoDB, MariaDB, and others, which enable seamless scaling of these databases in minutes.
Migrating
If you want to migrate your data from the old cloud to a new one, this is a lengthy process that, as a rule, can be automated only in a minimal way. You will need to transfer data, reconfigure applications, and adjust network settings. Additionally, the DB format should fit both structured and unstructured data.
In some cases, cloud service providers offer migration tools, such as import/export or application migration frameworks. However, it’s important to note that while compute and application instances can generally be migrated relatively easily, there may be instances where certain services are tied to a specific cloud provider. Such cases may require custom solutions or prove challenging to migrate.
Therefore, each step of the migration process should be carefully executed to minimize disruptions to ongoing business operations.
Connecting additional cloud services
Engineers seeking to integrate additional services or resources into an existing cloud computing environment must configure and test access and security settings, including two-factor authentication. This can be a challenge as compatibility issues with services from different cloud providers sometimes emerge.
Once the necessary settings are configured and resources are allocated, the new service can be connected and rigorously tested for both connectivity and functionality.
Main cloud computing service models
In the realm of cloud computing, there are three main service models that cater to different needs and use cases. Each model offers a unique set of advantages and capabilities.
IaaS (Infrastructure as a Service)
IaaS focuses on providing infrastructure components, allowing businesses to build and manage their own virtualized environments.
- Testing environments
- Website / app hosting
- Data Backup / recovery
- Big Data / analytics
- High-performance computing (HPC)
- Hybrid cloud environment creation
PaaS (Platform as a Service)
PaaS emphasizes the provision of tools and services for application development and management.
- App development/deployment
- Website/app development
- CI/CD
- IoT Solutions
- Big Data processing
- CMS (Content management systems)
- Backend for mobile services
SaaS (Software-as-a-Service)
SaaS offers ready-made software solutions that cater directly to end users.
- CRM solutions
- ERP systems (Enterprise resource planning)
- Visualization, collaboration, and productivity tools
- HR management tools
- Email/communication services
- Financial/Invoicing systems
- LMS (Learning management systems)
How to choose a cloud service provider?
Now that we have explored the different cloud service models, let’s discuss how to choose the right cloud service provider for your specific needs. With numerous options available on the market, selecting the right provider can be a daunting task.
In the next section, we will introduce our selection of top cloud service providers, and give our insights to help you choose the right one for your cloud project.
Top 6 cloud service providers worthy of your attention
- AWS
- Digital Ocean
- Azure
- Oracle
- Hetzner
- Bare metal (your own physical server)
AWS
AWS is a cloud service provider suitable for seasoned businesses, offering fast performance and impressive uptime. It provides a comprehensive range of services and features, such as S3 for object storage, Route 53 for DNS management, and CloudFront for content delivery. However, the extensive variety of services and the amount of data they handle require careful consideration, making AWS a less ideal option for beginners.
AWS has a proven track record with robust infrastructure and a global data center presence, ensuring high availability and low latency. It offers flexible computing options with powerful virtual machines, containers, and serverless computing. The flexibility of AWS allows businesses to scale resources up or down based on demand and easily integrate with other services.
AWS provides quick cluster creation with pre-configured values and offers many automated steps in deployment. It also offers a robust and comprehensive set of security controls, features, and services to help customers meet their security requirements and maintain compliance.
Pricing in AWS can be complex, as it offers various pricing models, but it also provides cost optimization tools and a free usage tier for new customers.
Digital Ocean
Digital Ocean provides a user-friendly experience with easy cluster creation, including convenient Kubernetes presets and automatic backup options. It caters to both beginners and advanced users, allowing manual setup for those seeking automation and performance optimization.
Digital Ocean provides scalability and flexibility through flexible droplet configurations and the ability to resize resources as needed.
Digital Ocean offers transparent pricing plans based on resource usage. Data residency options may be limited as they have fewer data center locations compared to larger providers, but availability is generally reliable.
Azure
Azure is a cloud service provider that offers a comprehensive set of service offerings and features, including strong support for open-source technologies. It offers great scalability and flexibility, allowing businesses to dynamically scale resources and integrate with other Azure services. With a broad range of data center locations worldwide, Azure provides options for data residency and ensures availability in various regions.
Azure provides free QuickStart templates and SDKs, which make it much simpler for engineers to create applications. Another benefit is that this cloud provider provides innovative services like AI, ML, IoT, RPA, or cognitive services, although these may come at a higher cost.
If you have already used other Microsoft tools – for example, Power BI – then Azure may be the best choice in your case. It offers flexible pricing models, including pay-as-you-go, reserved instances, and hybrid options.
Oracle
Oracle is regarded as a solid and battle-proven cloud provider for large enterprises. It offers a range of service offerings and features tailored to enterprise needs, including database services, analytics, and AI capabilities.
Oracle’s platform is known for its complexity, which may require a steep learning curve and deep technical expertise to fully utilize its capabilities. As a result, it is not recommended for beginners, who may find it challenging to navigate and manage.
Oracle Cloud provides a reliable infrastructure with robust servers and network capabilities. It ensures high availability and low latency to meet the demanding requirements of enterprise workloads.
Oracle’s pricing structure may be complex, with different licensing models and options. Data residency options are available through their global data centers.
Hetzner
Hetzner provides optimized and affordable pricing with a range of service offerings and features, including APIs and ARM64 architecture support. Also, they have 20 TB of bandwidth included on each server.
Hetzner offers reliable computing options with virtual private servers, dedicated servers, and cloud storage. Security and compliance measures are in place, including data encryption and monitoring. You can easily upgrade or downgrade resources with flexible plans.
Data residency options may be limited to their data center locations. Availability is generally reliable, and Hetzner includes generous bandwidth allowances with their servers.
Bare metal
Bare metal is a sophisticated cloud solution that requires time and effort to set up but provides benefits for experts who desire full control over automation and features. Bare metal enables custom configuration for big data migration and real-time analytics, potentially reducing costs depending on the complexity of your solution.
Security and compliance can be tailored to specific requirements with complete control over security measures. Scalability and flexibility may be limited compared to virtualized environments, but bare metal is suitable for applications with specific resource requirements.
Cloud computing experts: Cloud engineers, developers, architects
When assembling your team, it is crucial to define your project goals, budget, and timeline. Start by considering your budget to determine realistic timelines and when they can be achieved. If your timeline is pressing, you may need to adjust your budget accordingly.
It’s important to recognize that the combined output of two junior specialists may not be equivalent to that of a senior cloud developer or engineer. Likewise, it may not be practical to hire a top-notch cloud architect for maintenance or cost optimization on a small project without potential for scalability.
Hiring the right type of specialist for your project requirements is also important. Below you can find a comparative table showcasing three types of cloud specialists and the various tasks they perform.
Cloud solution building: The team
When it comes to cloud expertise, it’s essential to acknowledge the individuals who bring it to life. The engineering team plays a crucial role, whether they are part of the client’s internal team or an external team within an IT services company. But which option is better?
In this section, we will compare the advantages and disadvantages of internal and external cloud engineering teams. It’s important to note that the effectiveness and outcome of a project ultimately depends on the developers’ individual expertise. The following table serves as a guide and does not directly reflect a project’s efficiency or final result.
| Internal cloud engineering teams | External cloud engineering teams | |
|---|---|---|
| Expertise | Know more about the organization’s systems, processes, and domain-specific requirements. Can produce better tailored solutions to the company’s goals and requirements | Can have specialized skills and expertise, such as working with specific kinds of tools, possessing certain industry experience, new database or cloud migration expertise, or dealing with projects of higher complexity |
| Security concerns | Intellectual property fully belongs to the company. More secure in terms of data safety | The protection of a proprietary company’s information becomes crucial. More advanced agreements are needed |
| Skills | Skill gaps | The team have multifaceted skills: you pay, you choose |
| Organization | May have some organizational bias | Not a part of the company, so their engagement in the workflow isn’t transparent. |
| Perspective | Limited problem-solving | Higher diversity of perspectives |
| Resources | Time/effort constraints | Time/effort constraints depend directly on budget and can be scaled more easily |
| Dependency | Already an integral part | Organization may then depend on these experts for delivering updates or more features |
| Tools | Known, proven set of tools | May have access to new, more effective tools, technologies, or methodologies which allows for more innovation |
| Communication | Smooth | More challenging, but with more diversity and cultural differences |
| Cost-effectiveness | Mostly for long-term, large projects | Savings on recruitment, training, infrastructure, and other overhead costs |
| Best for | Delivering predictable, tailored solutions that align well with the team goals | Solving complex problems or implementing cutting-edge solutions |
Choosing the right team for your cloud project depends on its type and goals. If you’re concerned about lack of control with fully remote external teams or hiring a large internal team for a single feature, there’s a third option: extended teams.
Extended teams combine internal knowledge with the specialized skills of external cloud experts, resulting in a highly effective setup. With a broader range of expertise, these teams excel at comprehensive problem-solving and solution development.
Acting as a part of a client’s team, they actually integrate into the workflow and make a perfect match for startups and medium-sized projects.
Summary
The cloud services market has long since passed the initial stages. Now, companies are looking for ways to optimize costs without cutting down on the user experience. All ranges of cloud services, from migration to AI models, are also being enhanced. Low-code / no-code frameworks are further reducing the complexity of product building for startups.
But there’s a catch. Whether you’re a solid cloud architect with an impressive exercise or a junior developer just taking the first steps into the product, you’re already accustomed to some tools or frameworks. The human mind is usually trying to save energy, which is why learning something new is challenging.
In the near future, more complex DevOps / cloud computing automation models are predicted to arrive, but the aim will always be to optimize and shorten the path to revenue.
Essentially, energy and cost optimization are what all of these cloud services are doing, and we’re excited to see what happens in the future! So stay tuned!
