Cloud technology has transformed the way businesses operate in the digital age. However, cloud services come at a cost, and improving that cost is vital for achieving profitability and financial sustainability.
According to a report by Gartner, worldwide spending on public cloud services is expected to grow 23.1% in 2021 to total $332.3 billion, up from $270 billion in 2020. This means that industries need to adopt more effective cloud cost optimization strategies to avoid overspending and wasting resources.
In this article, we will explore 12 best practices for cloud cost optimization, along with practical use cases of how businesses can save money and improve their cloud performance. Whether you are using AWS, Azure, Google Cloud, or any other cloud provider, these tips will help you get the most out of your cloud investment. Let’s dive in!
1. Continuous Monitoring and Analysis
Regularly tracking cloud expenses is paramount. Services like AWS Cost Explorer or Google Cloud’s Cost Management tools offer detailed insights into your usage and spending patterns. By continuously analyzing your cloud costs, you can identify trends and areas where optimization is needed.
Use Case: A media streaming company observes a spike in data transfer costs during the holiday season. By monitoring and analyzing these costs, they determine that a change in content delivery strategies reduces their expenses while maintaining quality service.
2. Rightsize Your Resources
Rightsizing involves matching your cloud resources to actual usage. Amazon EC2 instances, for instance, offer a variety of instance types. By selecting the right size, you can avoid overpaying for resources you don’t need.
Use Case: A software development company realizes that they’ve been using larger instances than necessary. By downsizing their instances, they reduce their monthly cloud bill by 30% without compromising performance.
3. Utilize Spot Instances
Spot instances are a cost-effective way to run non-critical workloads. For tasks that can tolerate interruptions, like batch processing, spot instances can save you up to 90% compared to on-demand instances.
Use Case: An e-commerce platform uses spot instances for its nightly data analytics jobs. They achieve significant cost savings while completing the work within the desired time frame.
4. Embrace Reserved Instances
Reserved instances provide significant discounts in exchange for a commitment to a one- or three-year term. This is ideal for workloads that remain consistent over time.
Use Case: A SaaS company predicts steady user growth over the next three years. By investing in reserved instances, they reduce their compute costs and allocate resources more efficiently.
5. Implement Auto-Scaling
Auto-scaling dynamically adjusts your resource allocation based on demand. This means you’ll have the right amount of resources during peak times and can save during off-peak hours.
Use Case: An online retailer experiences increased traffic during holiday sales. Auto-scaling ensures they have the necessary resources to handle the load without overpaying for idle resources the rest of the year.
6. Opt for Serverless Architectures
Serverless computing eliminates the need to manage servers, reducing costs associated with infrastructure maintenance. Such as the AWS Lambda and Azure Functions lets you to run code without provisioning or managing servers.
Use Case: A startup creates a mobile app that relies on serverless functions for real-time data processing. With serverless architecture, they reduce operational overhead and infrastructure costs while ensuring seamless user experiences.
7. Monitor Idle Resources
Regularly auditing your cloud resources can help you identify and deactivate idle instances, storage, or databases that are incurring unnecessary costs.
Use Case: An e-learning platform discovers several unused virtual machines. By decommissioning these idle resources, they save thousands of dollars annually.
8. Prioritize Data Transfer Costs
Reducing data transfer costs between regions and availability zones is essential. By optimizing your data transfer, you can significantly cut expenses.
Use Case: An international e-commerce business reduces its data transfer costs by using a content delivery network (CDN) to cache and serve images and videos, resulting in a 40% cost reduction.
9. Employ Cost Allocation Tags
Cost allocation tags enable you to categorize resources by teams, projects, or departments, making it easier to identify cost centers.
Use Case: A large enterprise uses cost allocation tags to allocate cloud costs to different departments. This transparency helps department heads better manage their budgets and optimize their cloud usage.
10. Leverage Cloud Cost Management Tools
Most cloud providers offer cost management tools that provide insights and recommendations as well as help you identify cost-saving opportunities.
Use Case: A technology company uses AWS Cost Explorer to identify underutilized resources and receives recommendations to optimize their EC2 instances, leading to a 15% reduction in their monthly cloud bill.
11. Conduct Regular Cost Reviews
Regular cost reviews help ensure that your cloud costs align with your budget and goals. These reviews can uncover opportunities for further optimization.
Use Case: A financial services firm conducts quarterly cloud cost reviews and identifies that shifting to a different cloud service tier could save them an additional 10% without compromising performance.
12. Foster a Culture of Cost Awareness
Promoting cost awareness within your organization is crucial. Educate your teams on cost optimization best practices to encourage responsible cloud usage.
Use Case: A tech startup holds monthly workshops on cloud cost management. As a result, the development and operations teams become more conscious of costs, leading to a 20% reduction in monthly cloud spending.
Get Ready to Implement These Best Practices with Alignminds!
By implementing these best practices and learning from these real-world use cases, your business can optimize cloud costs without compromising performance or innovation. In the ever-evolving landscape of cloud technology, staying agile and cost-efficient is key to success.
So, get ready to make it happen with Alignminds – a digital transformation company that offers cloud optimization services, among other things! At Alignminds, we can help you with:
Cloud migration: Moving your applications and data from on-premises or other cloud platforms to AWS, Azure, or Google Cloud, using best practices and tools.
Cloud monitoring and maintenance: Monitoring your cloud resources and performance, and provide proactive support and troubleshooting to ensure optimal availability and security.
Cloud transformation: Modernizing your applications and architecture to leverage the benefits of cloud-native technologies, such as microservices, containers, serverless, and AI.
Cloud cost optimization: Analyzing your cloud usage and spending, and provide recommendations and solutions to reduce your cloud costs and improve your cloud efficiency.
One of our success stories is AWS infrastructure optimization for a leading online education platform. We analyzed the traffic and CPU load and usage history, and proposed a cost-effective solution with highly available auto-scaling AWS architecture to accommodate the application loads. We also implemented various AWS services, such as CloudFront, S3, EC2, RDS, ELB, Auto Scaling Groups, Route 53, CloudFormation, etc.
As a result, we reduced the monthly AWS bill by 60%, improved the application performance by 40%, and increased the availability by 99.99%.
To know more about our cloud optimization services, contact us today! Visit our website or email us at info@alignminds.com.
2023 is a time to look at what the future holds for Kubernetes. This container orchestration system has quickly become the de facto standard for managing containerized applications.
Kubernetes.has been evolving rapidly, and 2023 promises to bring many exciting new features, improvements, and challenges. This article will explore some of the most compelling Kubernetes predictions for 2023 and what they mean for businesses and IT leaders worldwide.
Kubernetes has been a game-changer in the world of containerization and cloud computing. As the adoption of Kubernetes continues to rise, IT leaders must stay updated with the latest trends and predictions to make informed decisions for their organizations.
In this article, we will learn what is next for container orchestration and explore seven real predictions for Kubernetes in 2023 that will help IT leaders stay ahead of the curve.
Before that, let us understand more about Kubernetes & the role of Kubernetes in 2023.
Understanding Kubernetes:
Kubernetes is an open-source platform built by Google to automate, deploy, scale, and manage containerized applications. Now maintained by the Cloud Native Computing Foundation (CNCF), it has become the de facto standard for container orchestration, replacing other solutions like Docker Swarm and Mesos.
It provides powerful features for automating deployment, scaling, and management of containerized applications, including self-healing, horizontal scaling, load balancing, and automated rollouts and rollbacks.
With Kubernetes, developers and IT operations teams can easily manage containerized applications at scale, making it a popular choice for modern cloud-native applications.
The Role of Kubernetes in 2023:
Kubernetes operators are becoming increasingly important in managing complex applications in Kubernetes clusters. Operators are software extensions that automate applications and infrastructure management within Kubernetes clusters.
In 2023, the role of Kubernetes operators will become more critical as the complexity of applications running on Kubernetes clusters increases. Kubernetes operators will enable IT leaders to manage complex applications and infrastructure more efficiently and effectively.
The 7 Real Predictions About Kubernetes for Futuristic IT Leaders
1. Kubernetes Will Continue to Dominate the Container Orchestration Landscape
One thing is clear: Kubernetes is not going anywhere! Despite the emergence of new container orchestration solutions, Kubernetes has cemented its place as the go-to platform for managing containerized workloads. This trend is expected to continue in 2023 and beyond as more organizations adopt cloud-native architectures and seek to streamline their development and deployment processes.
2. Kubernetes Will Become More User-Friendly
One of the biggest criticisms of Kubernetes has been its steep learning curve. However, efforts are underway to make Kubernetes more accessible to developers and operators of all skill levels. In 2023, we expect to see further improvements in this area, with new tools and interfaces that make it easier to manage Kubernetes clusters, troubleshoot issues, and automate everyday tasks.
3. Kubernetes Will Expand Its Role Beyond Container Orchestration
Kubernetes was initially designed as a container orchestration platform, but its capabilities have expanded significantly in recent years. In 2023, we expect to see Kubernetes continue to evolve as a platform for managing not just containers but also other types of workloads, such as serverless functions and virtual machines. This will enable organizations to run a broader range of applications on Kubernetes and enjoy the benefits of a unified management platform.
4. Kubernetes Will Improve Support for Stateful Applications
Kubernetes has historically struggled in managing stateful applications, such as databases, that require persistent storage. However, recent improvements in Kubernetes’ StatefulSet feature have made it easier to deploy and manage stateful applications on Kubernetes. In 2023, we expect to see further enhancements in this area, including better data backup and recovery support and tighter integration with cloud storage solutions.
5. Kubernetes Will Become Even More Secure
As Kubernetes adoption has grown, so has the need for robust security measures to protect containerized applications and data. In 2023, we expect to see Kubernetes continue to enhance its security features, with improvements in areas such as identity and access management, network security, and container isolation. This will give organizations greater confidence in running mission-critical workloads on Kubernetes.
6. Kubernetes Will Embrace Multi-Cloud and Hybrid Cloud Environments
With many organizations now using multiple cloud providers and hybrid cloud architectures, Kubernetes is well-positioned to provide a unified management layer across these environments. In 2023, we expect to see Kubernetes continue embracing multi-cloud and hybrid-cloud scenarios with new features and integrations that make managing applications across different environments easier.
7. Kubernetes Will Drive Further Collaboration and Innovation in the Container Ecosystem
Finally, one of the most exciting predictions for Kubernetes in 2023 is that it will continue to foster collaboration and innovation in the broader container ecosystem. Kubernetes has become a key driver of innovation in the container space. We expect this trend to continue in the coming years with new tools, frameworks, and applications built on Kubernetes.
Conclusion:
Kubernetes is set to have another exciting year in 2023, with many new features, improvements, and challenges on the horizon. As Kubernetes continues to mature and expand its capabilities, it will evolve and become more critical in cloud-native computing.
IT leaders must stay updated with the latest trends and predictions to make informed decisions for their organizations.
By understanding these seven real predictions for Kubernetes in 2023, IT leaders can stay ahead of the curve and ensure the success of their organizations. They may also choose to connect with the IT experts in the industry, such as Alignminds.
Book A Free Consultation:
Alignminds helps companies with cloud computing solutions and IT Infrastructure and embrace newer technologies like Kubernetes.
To stay competitive, IT leaders must offer the best Kubernetes experience, which means providing robust, scalable, and reliable Kubernetes services that can meet the demands of even the most complex applications.
Ask Alignminds experts about Kubernetes to help achieve your goals faster and deliver more scalable, reliable, and resilient applications. Whether you are a small startup or a large enterprise, Kubernetes can help you build a better cloud platform that meets your customers’ needs.
So, what are you waiting for? Book a consultation now! Contact Alignminds now!
As per research, the global serverless computing market is expected to grow at a CAGR of 22.2% between 2023 and 2028. Serverless computing has been gaining a lot of importance among developers. Want to know why? In this article, we shall be covering all the interesting facts revolving around serverless computing. Stay with us and read on!
Serverless computing
Serverless computing, also known as serverless architecture, is an execution method of cloud computing. The term ‘serverless’ doesn’t mean that there’s no server used. It means that developers can build and run code without managing servers. Serverless architecture tends to offer backend services on an as-used basis. For instance, if you’re a business that gets backend services from a serverless vendor, you are charged based on your computation. You are not required to pay for a fixed amount of bandwidth or a number of servers. With serverless cloud computing, developers don’t need to pay for idle cloud infrastructure.
All the leading cloud service providers like Amazon Web Services, Microsoft Azure, Google Cloud, and IBM Cloud provide you with a serverless platform.
How does serverless architecture work?
Managing servers is a complex process requiring business teams to look after hardware, maintain security updates, and create backups. But with serverless computing, developers can save themselves from these responsibilities and invest all their efforts in writing the application code.
Now, serverless computing functions on an event-driven basis. This means a function is executed as soon as an event occurs. In a nutshell, a developer only pays when the function is utilized. Serverless architecture works as per the Function-as-a-service(FaaS) model. It enables developers to execute code without the need for infrastructure instances.
Components of serverless computing
Given below are some of the basic components of serverless computing:
FaaS
It is the primary building block of serverless computing which executes the business logic.
API GATEWAY
It tends to deploy and maintain APIs. An API gateway offers an entry-point to clients to send requests to a service in order to retrieve data.
Backend-as-a-service (BaaS)
It is a cloud-based distributed NoSQL database. Some of the key features of BaaS include user administration, cloud storage, and other essential backend services. BaaS removes the need for administrative overhead.
It is a cloud-based distributed NoSQL database. Some of the key features of BaaS include user administration, cloud storage, and other essential backend services. BaaS removes the need for administrative overhead.
Benefits of serverless computing
Serverless computing can provide you with numerous advantages over traditional cloud-based infrastructure. Here are four reasons you should move to a serverless stack:
Quick deployments
With a serverless infrastructure, developers don’t need to upload code to servers or perform backend configuration to release their applications. All code is updated at once or one function at a time. This way, the application is quickly fixed or updated.
Enhanced productivity
Gone are the times when developers had to spend countless hours managing infrastructure. With serverless computing, developers can only focus on writing code and optimizing their front-end application functionality. They can work better on maximizing business logic.
Simplified DevOps cycles
Another benefit of leveraging serverless computing is that it helps developers save time in defining the infrastructure that is needed to test and deploy code builds. This way, DevOps cycles are more streamlined.
Multi-language development
With serverless computing, developers can code in any framework such as Java, Python, JavaScript, and more.
Reduced costs
Serverless computing works on a ‘pay-as-you-go’ basis. This means that developers only need to pay for what they use. The code will only run when backend functions are needed and will scale automatically..
Popular use cases serverless computing
Microservices
Serverless computing supports microservices architecture. Thanks to its cost effective pricing model and automatic scaling, serverless architecture has become a popular choice for building microservices.
Data processing
Serverless computing works well with structured audio, image, video, and text data. It also functions well with PDF processing and video transcoding.
API backends
With the help of a serverless platform, a function can be changed into a HTTP endpoint. An API gateway provides you with enhanced security, OAuth support, and more.
Mobile and web applications
A serverless function takes a request from the front end, retrieves all informational data, and then hands it back to the front end of the application or site.
The serverless era is here!
We hope our article helped you gain a fair understanding of serverless computing. Serverless computing is everything that a developer needs. There is no denying that serverless has created a buzz in the software architecture world. Not only is it cost-effective but also facilitates innovation. So, wait no more! Switch to serverless computing and take the next step toward business transformation.
We would love to see you move towards success. Let us know how we may support you. Contact without delay.
Around the globe, businesses are migrating to the cloud to reduce IT infrastructure costs. Cloud computing helps them to customize computing based on actual requirements and avoid any wasteful spending.
However, as the popularity of the cloud increased, the cost of cloud computing also increased. This happened mainly due to a small group of mega vendors dominating the public cloud markets. Due to monopoly, innovation became stagnated, and prices became no more competitive due to new entrants having no ability to enter the market. Businesses were forced to discover new opportunities for cost saving without compromising on quality.
This unique situation led to the discovery of a new architecture called multicloud. Nowadays, this computing model has become the de facto standard among organizations.
According to a survey conducted by Flexera, 89% of organizations are following a multi-cloud strategy. Only 2% of organizations are still in a single private cloud. When it comes to the case of a single public cloud, the figure stands at 9%. These figures prove how fast the cloud computing market is evolving and how rapidly multicloud is becoming the new face of the industry.
What is multicloud? Definition and meaning
Multicloud is the use of cloud services from multiple cloud service providers like Amazon Web Services (AWS), IBM Cloud, Google Cloud Platform, and Microsoft Azure so that the organization will have more flexibility to optimize performance, control costs and leverage the best cloud technologies of the day.
In a multicloud model, an organization can use two or more private clouds, two or more public clouds or a combination of public, private and edge clouds to run their applications and distribute services. Such cloud computing models make use of open source, cloud-native technologies like Kubernetes that are supported by all public cloud providers. The model will also have a “central console” to monitor and manage workloads across multiple cloud platforms.
Multicloud architecture is mainly used for enterprise application development, compute infrastructure, data warehousing, artificial intelligence, machine learning, cloud storage and disaster recovery.
Multicloud vs Hybrid: Are they the same?
Even though both multicloud and hybrid clouds use more than one cloud platform for deployments, they differ due to the kinds of clouds used in the architecture.
There are mainly two kinds of cloud deployment: public and private.
In the public cloud computing model, computing resources and infrastructure are managed by a third-party vendor and shared with more than one user via the internet. Whereas, in a private cloud computing model, the computing resources and infrastructure is dedicated to only a single organisation/user. Usually, it’s an organization that builds and maintains a private cloud themselves. However, they can also seek help from an external vendor to host a private cloud for them.
The difference between multicloud and hybrid cloud models depends on whether they are using private cloud, public cloud or a combination of both.
A hybrid cloud model makes use of two or more types of clouds. In other words, a computing model that makes use of private and public clouds for deployment is known as a hybrid cloud. In contrast, a multicloud model may utilize a combination of clouds that can be two or more private clouds, two or more public clouds or a combination of private and public clouds.
You need to consider various factors before deciding whether you need a multicloud or hybrid cloud strategy for your business.
Cost
Private clouds are costly to set up and maintain compared to public clouds. This is mainly because there are multiple beneficiaries participating in a public cloud model and the cost is shared among them all making it cheaper. Whereas in the case of the private cloud, all costs are borne by a single organization. So naturally, a multicloud model that utilizes several public clouds will be cheaper than a hybrid cloud model that utilizes private and public clouds.
Reliability
The Multicloud model is comparatively more reliable since the model makes use of multiple clouds to distribute the services. Even during peak times when the demand is high, the application will be up and running without any issues as the workload can be distributed to backup clouds or more resources can be allocated. On the other hand, a sudden rise in demand may overwhelm a hybrid cloud architecture since it will be consisting of at least one private cloud and private clouds are not easy to scale generally.
Security
The security element should be evaluated carefully when deciding between multicloud and hybrid cloud models.
Most of the multicloud and public cloud vendors have more resources at their disposal to fight security intrusion, data theft, privacy breach etc. They frequently release new patches to protect the data of the users.
However, if you have access to a private cloud or on-premises data centre that is best in terms of security and management, a hybrid cloud model will be a better choice for you.
Resources
Most public cloud services are fully controlled by third-party vendors. This is an advantage for businesses that want to maintain a small team and avoid unwanted overhead.
On the other hand, an on-premises data centre requires a team of experts to set up, run, maintain and manage the infrastructure. Even if you approach an external vendor to host a private cloud for you, the price will be higher due to service, support and maintenance charges.
Scalability and dependency
Lack of scalability is one of the major issues haunting on-premises infrastructures. Growth will not be possible without upgrading the technologies on a regular basis. Such requirements demand more investments and maintaining a team of experts to manage the infrastructure is also needed. Migrating from legacy systems to the cloud also demands effort, investments and time.
On the other hand, a multicloud environment makes scaling easier for a business. Moreover, a business does not have to depend on a team or vendor in a multicloud environment as they can move to better alternatives without much hassle.
Performance
Public cloud servers can vastly boost application performance and user experience by integrating new computing methodologies like edge computing.
Other benefits of multicloud
Flexibility
The multicloud model provides businesses with an opportunity to choose cloud services from different vendors. An organization can choose cloud service providers based on a combination of price, performance, location, security, legal compliance etc.
Technology advantage
Multicloud enables businesses to have a technology edge over their competitors. Since a multicloud user is not dependent on a single vendor, the organization can move to a better environment that offers advanced technologies.
Reduced outages
In a multicloud environment, an outage on one cloud will not affect other clouds in the same environment. As a result, the application will run smoothly without any interruptions and the organization can ensure a better user experience.
No more monopoly
With the introduction of multicloud, technology gatekeeping and industry monopoly in the IT sector have come to an end. It was a usual strategy followed by several vendors to charge a premium for their services because they were marketed as an “ecosystem” that is easy to use and well-integrated. This strategy is not effective anymore since businesses now have the option to combine services of different vendors and create their own “cloud ecosystem”.
Even with all these advantages, the multicloud model may not be suitable for all businesses. It is mainly due to the challenges posed by it.
Multicloud: Challenges
Management
Since multicloud utilizes more than one cloud, integrating, monitoring and managing them may appear as a challenge to some businesses. The situation becomes more complex when the different vendors are following different processes, methodologies and technologies. Also, data and technology stacks being scattered across different clouds under different vendors may have their disadvantages too.
Latency
When different services are running on different clouds, there will be frequent interactions between clouds to fulfil user requests. This can introduce latency depending on how closely the services are integrated, the amount of data that needs to be transferred, the location of each cloud and the frequency of the interactions. Utilizations of technologies such as microservices and edge computing etc. can solve this issue to an extent.
Risk
When an application is using many software and hardware, it is offering more targets for a cyber-attack. A single vulnerability in any of these components can lead to the complete shutdown of the application and services and sensitive data may end up in unwanted hands. So, a strict security policy should be formulated before adopting a multicloud model.
Performance
Load balancing can become difficult when there are multiple clouds involved. So, a centralized console to monitor and manage resources across all clouds is very crucial in a multicloud environment.
Multicloud management
To utilize the full benefits of multicloud architecture, all the clouds involved must be integrated closely as if they were part of a single cloud. Therefore, a central console to monitor and manage resources and services across all clouds plays a vital role in a multicloud architecture. With the help of the central console, an organization can
Maintain uniform and consistent security across all clouds.
Ensure a universal application of compliance policies.
Ensure consistency across every stage of the application life cycle (Development, staging, testing, deployment, production etc.)
Monitor events and logs from different service components using a single interface.
Configure consistent response to all events.
Implement version control effectively and efficiently.
Keeping the above points in mind, you can choose a cloud management tool or multicloud management platform that
Helps you monitor and control any cloud resource including IaaS, PaaS, SaaS, data storage, networking or deployment resources.
Offers analytical capabilities with the advantages of Artificial Intelligence (AI) and Machine Learning (ML). AI and ML can be used to streamline operations (E.g., AIOps), add elasticity to resource scaling and perform automatic responses to various events.
Helps you implement consistent and universal security and compliance policies.
Artificial Intelligence and Machine learning can be used in multicloud computing to optimize resource usage and to have better analytics. (Image credit: iqlect.com)
Examples of multicloud management platform
VMware
VMware offers you the vRealize Suite, a central management console, to monitor and control the availability of resources and their utilizations irrespective of what deployment platform you use. vRealize already offers different modules to help you manage resource catalogues, policies, self-service deployment and CI/CD for DevOps organizations. And the number of modules it offers is increasing day by day. For example, in 2018, VMware acquired CloudHealth which can help you with cost management and optimization. It recently acquired SaltStack, an infrastructure automation platform.
VMware stack can run on AWS natively and Azure and GCP via CloudSimple. The VMware Tanzu Kubernetes already works well with AWS. It will start supporting Azure and Oracle cloud very soon.
HyperGrid
HyperGrid is a new kid on the block. It is widely recognized as an “intelligent cloud management platform” due to its full range of capabilities that extend to proactive budget monitoring and reporting, security control, audit readiness, continuous compliance and migration and disaster recovery planning. Gartner considers HyperGrid a “Visionary” in the field. IBM, the US Navy, Synopsys, Henry Schein etc. are a few well-known names in their customer list.
HyperGrid Supports AWS, Microsoft Azure, Google Cloud and VMware.
Scalr
Scalr boasts itself as the only CMP (Cloud Management Platform) designed for enterprise scale. It enables enterprises to incorporate standardization to resource usage and have better cost control. Another advantage of Scalr is that it allows enterprises to choose cloud platforms that meet their actual needs rather than being restricted to using only the features offered by a specific vendor(s). Scalr helps organizations to avoid vendor lock-ins. Recognizing Scalr’s commitment to multicloud philosophy, Gartner named it a leader in the industry.
Samsung, Gannett, Sephora, the FDA, NASA JPL, Xerox, etc. are a few well-known names in their customer list.
Here are a few features that are offered by Scalr
A single central console to monitor cloud usage.
Option to incorporate conditional security and compliance
Role-based access control.
Smooth integration with various IT and DevOps tools.
Customized provisioning portals.
Morpheus
Morpheus aims to integrate CloudOps with DevOps. It offers a variety of multicloud management tools to link development, IT operations and business processes.
Morpheus offers AI-based reporting tools to optimize cloud costs. It also provides role-based access so that the organization can have better governance of the environment. The self-service tools help with faster provisioning and deployment. And in fact, Morpheus claims that its users can set up and run a multicloud environment in less than one hour. It also supports more than 20 cloud platforms.
McDonald’s, BlackRock, AstraZeneca, Penn State etc. are a few well-known names in their customer list.
Conclusion
By Adopting a multicloud model organizations can now have the freedom to use the best possible cloud for each workload. It helps them to avoid unwanted overhead, improve performance, reliability and security and have a technological advantage over their competitors.
Looking for a multicloud solution for your next project? Contact us now!
Gartner defines edge computing as a distributed computing topology where information processing is located close to the edge where things and people produce or consume that information.
The birth of edge computing can be traced back to the 1990s when content distribution networks were created to serve web and video content from edge servers close to users. Later, edge computing evolved into an advanced version that hosts applications and application components such as shopping carts, ad insertion engines, dealer locators and real-time data aggregators.
Edge computing market revenue worldwide from 2019 to 2025(in billion U.S. dollars)
Source: Statista
The number of papers related to edge computing on Google Scholar was only 720 in 2015. However, it has grown to more than 25,000 in 2020. The number of edge patent filings done as of 2020 is 6,418. This is a hundred times more than the number of patents filed related to edge computing in 2015.
While the edge computing market was valued at 139 billion US dollars in 2019, it is expected to reach 274 billion US Dollars in value by 2025.
Apart from these data and figures, if we investigate the real world, the word “edge computing” is becoming familiar across industries, day by day.
So, what’s the deal with edge computing? Why more and more companies are adopting it and becoming an advocate for this technology?
“Edge computing is a networking philosophy focused on bringing computing as close to the source of data as possible in order to reduce latency and bandwidth use. In simpler terms, edge computing means running fewer processes in the cloud and moving those processes to local places, such as on a user’s computer, an IoT device, or an edge server. “
From this definition, it is clear that edge computing is a distributed computing principle applied by companies to reduce delay in information processing and bandwidth usage by moving computing closer to the source of information.
Since the computing is executed as close as possible to the users, there is minimal long-distance communication between a client and the server. As a result, the users will have a faster and more secure experience when using technology-based services and the service providers will have the benefits of providing the best-in-class user experience.
How does edge computing work?
Traditionally, enterprise computing was done by moving data that is produced at the user’s devices via the internet to enterprise servers, then it is stored and worked upon, and the results were sent back to the user’s device. Client-server computing was the most proven and time-tested approach implemented by most organisations.
However, ever since the internet and digital revolution, the volume of data produced by consumers and shared with enterprises skyrocketed. Sending, storing, and computing such a large volume of data at a centre infrastructure became a herculean task. Also, sending and receiving so much data put a toll on the internet. There was frequent congestion, latency issues even downtime that affected the services.
So, the industry came up with an idea of a decentralized system in which the storage and computing are done closer to where the information is produced. Since the computing is done at this closer point, called “the edge”, this approach is known as “edge computing”.
Edge nodes or Edge servers collect and process data locally. Depending on the business model and architecture, sometimes the results of the process are sent to the principal server that is deployed in the cloud.
To better understand how edge computing works, here are a few use cases for you.
Transportation
Self-driven vehicles are replacing manual-driven vehicles at a faster rate. They are widely used for cargo movements and courier services. Such autonomous vehicles function by aggregating a large volume of data related to their location, physical condition, road condition, climate condition, traffic condition, speed and movements of other vehicles close by. It is by gathering and analysing such data in real-time that the vehicle is able to reach its destination without any accident or shortcomings. To facilitates this “auto-piloting”, onboard computing is very much required as a single self-driven vehicle produces anywhere between 5 TB to 20 TB of data in a day.
Network routing
Latency has a significant role in internet traffic. To ensure the quality of the network, the traffic must be routed via the most reliable and low latency path. Edge computing can help with optimizing network routes by regularly measuring traffic conditions across the internet and choosing the best path for each user’s traffic.
Healthcare
Healthcare has technologised rapidly in recent years. There are countless pieces of equipment that make use of the latest technologies to diagnose and monitor the health of a patent. Such types of equipment collect and process large volumes of data, regularly for a longer period of time. With the help of edge computing and machine learning these data can be used for finding abnormalities and delivering proper treatment at the right time.
Retail
The benefit of implementing edge computing in the retail sphere is manyfold. It can be used for surveillance, stock tracking and refilling, real-time sales monitoring, and analysis, aggregating, sales and customer information, loyalty programmes based on sales data, item procurements etc.
Manufacturing
A product must go through many stages before its ready for sending to the market. These stages include product design, prototyping, production, quality checks, packaging, and branding. By implementing edge computing, manufacturers are able to monitor these activities in real-time and at a large scale and it also enables them to reduce resource wastage and find loopholes in the existing process. Together with machine learning, edge computing helps manufacturers collect and analyse data in real-time. Making the right decision at the right time has become easier for them.
Benefits of edge computing
Speed
Since data is produced and processed at the same point, computing became a lot faster. There is no need to send and receive large chunks of data and there is little to no uncertainty of computing demands. Due to this increased responsiveness, edge computing is better than traditional and cloud computing in so many cases such as IoT, autonomous driving, healthcare, public safety, surveillance, augmented reality etc.
The healthcare industry has already recognized the benefit of edge computing.
Reliability
The distributed topology ensures that reliability is not a concern when it comes to edge computing. Because the data is produced and processed at the edge, and multiple edge nodes are used in the system, failure in one node does not affect the remaining ones. Also, since there is a low dependency on the central cloud server, any disruption in the connectivity between the cloud and edge node will not affect the overall performance. In fact, once the connection is restored, the data can be securely synchronized between the nodes and server.
Efficiency
Since computing is executed at the edge, edge computing offers a sophisticated environment that is fit for the usage of advanced analytical tools, artificial intelligence, and machine learning. We have already seen how this can help certain industries like transportation and healthcare.
The opportunity to use powerful analytical tools also helps the system to optimize itself. The system can regularly monitor the user demands and determine where to execute the computing depending on how resource-intensive the task is. For example, if the edge node has the required capacity, it can execute the task and send back the results to the client device saving up bandwidth, resources, and time. If the task requires additional resources, it can be assigned to the central server, where most resource-intensive but rare occurrence tasks are executed.
Scalability
A distributed system is easier to scale than a traditional one. New nodes can be set up to meet the growing demands and any addition or removal of nodes will not affect the system as a whole. Also, each node can be customized according to demands that are specific to the area it serves.
Privacy and security
Edge computing makes use of special encryption mechanisms to protect data that may travel between client and nodes, nodes and nodes and nodes and server. Using a decentralized trust model, the communication between each node is evaluated and whitelisted. Since edge computing emphasises producing, gathering, and processing data at a single point, data is handled in a better way in terms of security and privacy. For example, a node that is situated in a particular geography can be governed by the local law and the condition of local infrastructure and vulnerabilities can also be taken into consideration while setting up the security measures.
Is edge computing and IoT the same?
It is a common misconception that edge computing and IoT are the same. In reality, Internet of Things (IoT) is a use case of edge computing.
IoT makes use of cloud servers for data storage and computing. It means that IoT totally depends on the internet for connectivity. It also means that IoT implementations are centralized and usually intended for specific purposes only.
However, edge computing is decentralized by design, and it can be implemented independently of the internet since data can be produced, collected, and processed at a single point. An edge computing system can also be generic in nature and the data and processes can be heterogeneous.
In short, IoT can be implemented as part of edge computing. However, both are vastly different.
Edge vs cloud vs fog computing
It is common to compare the new technology with existing ones to find out whether it is justifiable to adopt it for your business. The case of edge computing is not exceptional in this matter. Organisations are already used to cloud and fog computing. There should be apparent incentives for them to adopt the new kid in the block. So, let us discuss how these three are different from each other and what they bring to the table.
Edge computing
Edge computing is the deployment of computing and storage resources closer to where the data is produced or consumed. For example, a retail mall with an indoor traffic system can use edge computing to collect and process traffic data in real-time to facilitate its smooth functioning. If it is a chain business, data can be sent to a centralized data centre for human review. However, if the amount of data collected and processed exceeds the computing and storage capacity, the system will fail until the capabilities are improved.
Cloud computing
Cloud computing is the distributed deployment of computational resources and data storage over multiple locations. Since computing is available on-demand, cloud computing is highly scalably and affordable at the same time. Since it is a distributed system, cloud computing offers better storage and retrievability of data and there is least to nil concern about data being lost forever.
However, each cloud server can still be far away from end-users. Data is processing at these far away points and the system depends on the internet to share the data between client and server. In other words, cloud computing is nothing but traditional computing implemented in a distributed architecture that depends on the internet. It consumes bandwidth, can be affected by latency and even overwhelmed by a sudden surge in demands if not configured with the right anticipation.
Fog computing
Fog computing or fogging is an improvised version of edge computing. Sometimes, “the edge” become so large that implementing a strict edge computing system will be detrimental to the actual plan. For example, smart cities are producing a large volume of data every minute. These data are heterogeneous in nature and used for different purposes. However, the objective of the whole implementation could be based on a few principles. Setting up several nodes to cover the whole city will not be practical and it will also affect the objective of the whole system. So, such a system makes use of a fog layer that consists of fog nodes. These fog nodes act as a backend to the edge nodes and add additional computing power to the whole system. Fog computing is the combination of cloud and edge computing and aims to mitigate the weaknesses of both.
Conclusion
Edge computing has opened up so many untapped opportunities and several industries have already started leveraging its advantages. However, its true potential is still unachievable due to the lack of compact devices with enough computing power and software that can handle a limitless number of edge devices. Improvised versions of edge computing such as fog computing may be a step in the right direction.
Are you looking for a renowned technology partner to develop a next-generation edge computing solution? Contact our team of experts for a free consultation.
PaaS (Platform as a Service) market is expected to reach 57.15 billion dollars in 2022. Considering that the market value was 49.41 billion dollars in 2021, it is a CAGR (Compound Annual Growth Rate) of 15.7%. At a CAGR of 13.9%, the market is forecasted to reach 96.24 billion dollars in 2026.
If you are new to the term “PaaS”, PaaS or Platform as a Service is a cloud computing model that offers an environment for businesses to develop, deploy, run, and manage applications over the internet without the need for them to build and maintain the required infrastructure. The infrastructure and the related computer resources are provided by the PaaS provider. So, when we use the term “PaaS market” it denotes the total sales from such cloud-based platform services.
Forecast: PaaS Market Value
There are different types of PaaS. We can generally classify them into web applications, computing platforms, business applications and social applications. Some of the popular PaaS providers include Heroku, Amazon Web Services (AWS) Elastic Beanstalk, Google App Engine and Microsoft Azure.
In 2021, North America was the largest PaaS market followed by Western Europe. Other markets like Asia-Pacific, Eastern Europe, South America, the Middle East, and Africa are also witnessing significant growth in recent years.
Why PaaS: The opportunities it offers
The major reasons why the PaaS market is seeing such growth are manyfold. A PaaS platform can be accessed by multiple users. Businesses can choose computing resources as per their need and scale accordingly when there is a rise in demand. It is easy to run and maintain PaaS platforms as it uses virtualization technology and you do not need extensive system administration knowledge.
Other benefits of PaaS include,
PaaS enables businesses to avoid investing in IT infrastructure and they can invest the budget in their core operations.
PaaS enables businesses to avoid the tedious process of procurement and the need to hire expert personnel for the same.
PaaS enables businesses to save up on office space that otherwise would be needed for storing devices and infrastructure.
Since PaaS is a managed service, businesses can avoid the cost of hiring and maintaining the talent required for building and managing hosting environments and infrastructure.
PaaS enables businesses to reduce their team size. It improves the efficiency as the team will be working only on the core business functions.
Since PaaS offers a way to deploy applications fast and automatically, it reduces complexities and saves up time and money for businesses.
Most of the PaaS providers offer hybrid cloud solutions that are a mixture of private cloud, on-premises computing and public cloud solutions. It enables businesses to innovate, improve efficiency and agility, increase development capabilities and speed and reduce IT costs.
These advantages help businesses and developers in multiple ways.
They can concentrate on developing innovative solutions instead of focusing on external issues.
Developers do not need to start from scratch. They can avoid a lot of repetitive tasks and extensive coding, saving time and money for businesses.
Since PaaS enables developers to solely focus on actual development, the overall development cost comes down. A competitive business can use the saved-up money to better their product by adding more features and implementing creative and user-friendly ideas. They can also use the saved-up budget for market research and better marketing.
In short, PaaS offer businesses an opportunity to develop innovative applications in the most cost-effective and time-effective way. Since PaaS eliminate the need to create and maintain infrastructure and deployment environment, it reduces a lot of complexities and investment.
However, PaaS is not free of disadvantages.
Since PaaS is still an “over the internet” service, it possesses certain risks like privacy and security threats. This is a big concern for corporates since they must protect application data and the privacy of users, especially since there are several regulations in place like General Data Protection Regulation (GDPR) and HIPPA.
PaaS has certain security vulnerabilities that make them a popular choice for cyber-attacks. These vulnerabilities include lax default application configuration, misplaced or lost Linux updates, lost third party patches and holes in secure socket layers (SSL) protocols. Such vulnerabilities can cost businesses money and credibility.
Since PaaS is a managed solution, it takes away control over the environment.
PaaS may have compatibility issues. Certain PaaS supports only specific software architecture and there may be restrictions on the kind of services that can be used on the applications.
Rise of AWS Elastic Beanstalk
Amazon introduced Beanstalk as a solution for system-level development rather than business application development. As a result, Elastic Beanstalk is not a pure PaaS technology. AWS paired Beanstalk with hundreds of cloud services it offers, such as AWS Lambda, to counter the challenges faced by most PaaS technologies.
AWS used its existing stack of services including EC2, S3, Simple Notification Service (SNS), CloudWatch, autoscaling, and Elastic Load Balancers to integrate emerging technologies with Beanstalk. This helped developers to build serverless subsystems directly from the platform and make use of most of the native AWS cloud services and even from outside the ecosystem. Developers can use AWS Elastic Beanstalk to build websites, back ends for both mobile and APIs and for asynchronous work.
Also, Beanstalk integrates well with Amazon Elastic Compute Cloud Container Registry and Docker’s repository. It can use container orchestration tools such as Kubernetes to launch multi- or single-container instances. The platform is compatible with any PHP, Java, Python, Node.js, Ruby, .NET, Docker or Go web applications.
Let’s take a look into the advantages of AWS Elastic Beanstalk and how it tries to overcome the challenges of common PaaS solutions.
The advantages of AWS Elastic Beanstalk
AWS Elastic Beanstalk enables businesses and developers to get access to emerging development opportunities through its advantages.
Faster development and reduce complexities
You can use AWS Management Console, a Git repository, or an IDE (Integrated Development Environment) such as Visual Studio or Eclipse to deploy your code to the platform. When a code is deployed, the platform automatically handles capacity provisioning, load balancing, auto-scaling, and monitoring; thus, the process becomes simple. Since the tasks are automated, it takes only a few minutes maximum for the code to run; so, the deployment duration is also very less.
Easy monitoring
AWS Beanstalk provides a unified user interface for you to monitor the health of your deployed application. The platform tracks more than 40 key metrics and offers you an opportunity to customize the health permission, health checks and health reporting.
You can integrate Beanstalk with Amazon CloudWatch and AWS X-Ray for easy performance monitoring. Using CloudWatch, you can also set up customized thresholds for metrics like CPU utilization, latency etc. and get notified when these metrics exceed the configured thresholds.
Scale on demand
AWS Beanstalk allows you to set up auto-scaling. Once enabled, the platform automatically scales your application based on needs and the configured settings. This feature offers you flexibility in the sense that you can choose any metrics such as CPU utilization to trigger auto-scaling. It also helps you ensure that there is no application downtime, and the cost is directly dependent on resource utilization.
Customize it
Not all businesses have the same requirements. The scope of customization enables a business to leverage every opportunity it has in its hand. Therefore, Elastic Beanstalk is becoming one of the popular choices for businesses across industries.
When using Beanstalk, you can not only choose what AWS resources to make use of for your product, but you can also retain full control of the environment. Beanstalk’s management capabilities make it easier for developers to take control of one or all the resources that are available on the platform.
For example, as a developer, you have the option to choose the type of EC2 instance for your application and what is the optimal amount of RAM or CPU needed for your code to run. You can also customize the default Elastic Beanstalk Amazon Machine Image and configure Beanstalk to use it for your application.
Flexibility and adaptability
Due to feature requirements or better opportunities, a business may choose to use different technologies to develop a product. However, this is not an easy task since combining two or more services may cause compatibility problems.
Fortunately, AWS Elastic Beanstalk tries to help you overcome such challenges. It lets you integrate numerous services that exist in AWS environment, and you can use Docker’s repository or tools such as Kubernetes to develop and launch your application. You can also run multiple services on EC2 and the application you create on Beanstalk will be able to access them efficiently.
Security
The platform automatically keeps itself up to date with new patches and the latest platform versions (minor). The only caveat is that “managed platform updates” must be enabled by you from the configuration tab. Another caveat is that the platform will not perform major platform updates since such updates may include backwards-incompatible changes. But you can perform such updates manually.
However, the true strength of the platform is its “immutable deployment mechanism”. It ensures that the existing environment is safe from any changes caused by the updates by creating a parallel fleet of Amazon EC2 instances that are to be updated with the latest patches. The existing instances are terminated only after the completion of successful installation of updates that are done parallel and independent of the existing ones.
Also, when the updates are being installed, the health of the application will be under scrutinization by the system and in case any conflict occurs, the traffic will be redirected to the unaffected fleet of instances. So, the end-users will not be affected by a faulty update.
Privacy and legal compliance
AWS Elastic Beanstalk follows several criteria including ISO, PCI, SOC 1, SOC 2, SOC 3 and
HIPAA compliance. So, when using Beanstalk for your applications, you do not have to worry about processing financial or health data. You can also be sure that the applications follow the major security and privacy standards.
Elastic Beanstalk architecture
The above advantages are the result of Beanstalk’s unique architecture. So, let us briefly discuss the architecture it uses.
AWS Elastic Beanstalk architecture consists of several major components. They are,
The environment
All the resources needed to run your applications are contained within the environment. So, it is right to say, the environment is the heart of your application. The moment you create an environment Beanstalk automatically provisions all the resources required to run your application. These resources include an elastic load balancer, Auto Scaling group, and one or more Amazon Elastic Compute Cloud (Amazon EC2) instances. The CNAME is considered a part of the environment and it will be pointed to the load balancer. Any request to your domain name will be redirected to the CNAME.
The environment will change depending on the software stack you want to use. It is because each software stack requires a different infrastructure topology, and these topologies are defined by a “container type”. To give an example, an environment with an Apache Tomcat container will be using the Amazon Linux operating system, Apache web server, and Apache Tomcat software.
Load balancer
As the name suggests, the load balancer automatically distributes the incoming requests across multiple Amazon EC2 instances to ensure that the resource utilization is optimum irrespective of whether the traffic is normal, high, or lower. This is done with the help of Elastic Load Balancing URLs and the EC2 auto-scaling.
Amazon EC2 Auto Scaling
Amazon EC2 Auto Scaling (Denoted by Auto Scaling Group in the diagram) is a crucial component without which the environment will fail to handle any variation in traffic. It automatically creates new Amazon EC2 instances when there is an increase in the load on the application. When the load decreases, it terminates any unwanted instances to keep resource utilization at an optimal level. Beanstalk allows its users to customize the minimum and the maximum number of instances the auto scaler should create and handle.
EC2 instances
EC2 instances are compute images that process the actual workload. These can be created, handled, and terminated automatically by the platform. However, Beanstalk allows the users to customize these instances to offer better flexibility. By customizing instances, you can change CPU and memory allocation in case you want more control over the environment.
Host manager
Each EC2 instance will have its own host manager. A host manager is a software component that is responsible for
Deploying an application
Aggregating events and metrics for retrieval
Event generation at the instance level
Monitoring application log file for any critical errors
Monitoring of application server
Installing patches for instance components
Publishing log files to Amazon S3
Any metrics, errors, events, or server status that are available via the Elastic Beanstalk console, APIs, or CLIs are reported by the host manager.
Security group
The security group is what defines the firewall for each instance. In other words, a security group allows or restricts traffic to and from an instance. The default security group can be accessed using port 80 (HTTP). While the default one is created by Elastic Beanstalk, as a user, you can create additional security groups to define the traffic to certain instances or from other sources. The best example could be for your database server.
AWS Beanstalk – PaaS components
How to deploy an application using Elastic Beanstalk?
Here is a brief guide on how to deploy an application to AWS elastic Beanstalk.
Preparation
If you are going to use an external database for your application, you must launch an instance of the database to Amazon RDS first. It is safe to choose “multi-AZ MySQL database instance” in the Amazon RDS console since it enables database failover if the instance fails.
Once the above process is completed you can start working on the access rule. Modify the security group to allow downstream traffic to access only a specific port.
Create an AWS Elastic Beanstalk environment
Access the Elastic Beanstalk Console and create an environment using the default settings. By default, Beanstalk automatically creates an EC2 instance, security groups, load balancer, autoscaling group, Amazon S3 bucket, Amazon CloudWatch alarms, AWS CloudFormation stack and the domain name.
Customization and configuration
You can customize the configuration to grant yourself more control over the environment. This includes configuring the minimum and the maximum number of instances for the auto skating group.
You can also create additional security groups to allow or restrict traffic to specific instances or specific ports. You can use the environment properties to configure connection data to the environment. The properties are available on the management page of the environment you created. Also, confirm that the environment is compatible with the Amazon RDS database instance we created in the first step.
Deployment
Use the “Upload and Deploy” option on the management page to upload your code bundle to the environment. Also, confirm the URL for the application.
Congratulation you have successfully deployed your application to AWS Elastic Beanstalk!
Conclusion
PaaS technologies, with their advantages, offer businesses several opportunities. However, there are challenges too. AWS Elastic Beanstalk, with its user-centric approach, better integration, and flexibility, tries to help businesses overcome these challenges and have better opportunities at hand.
Need help with deploying your application to AWS Elastic Beanstalk? Contact our team of experts now!
Cloud applications are becoming one of the popular options for businesses all over the world. The reason is, it helps them with their cost-cutting strategies.
Since cloud computing works with the help of the internet, the cost of setting up hardware and maintaining the infrastructure can be avoided. Also, the SAAS products have better support and they are easy to use due to their popularity and user base.
What is cloud computing?
Microsoft defines cloud computing as
“Cloud computing is the delivery of computing services—including servers, storage, databases, networking, software, analytics, and intelligence—over the Internet (“the cloud”) to offer faster innovation, flexible resources, and economies of scale.”
The main benefits of cloud computing are
You pay only for cloud services/resources you use
Scalability: As more resources are easily available
Affordability: As you can run the infrastructure more efficiently
As cloud computing became more popular, there was a new trend that became prominent in the industry. The rise of cloud applications.
What are cloud applications?
A cloud application is software that works with the help of data stored in a remote server and uses its resources to process the data and functions. A cloud application has two different systems that work in synchronization. They are client-side and server-side systems. While some processes will take place on the client-side (client’s device/local hardware), the remaining process will be taking place on the server-side which is located remotely and connected with the help of the internet.
One of the main benefits of cloud applications is that they can be accessed from different devices, at any time from anywhere. Also, there are cloud applications that can work without being installed on local devices. Due to such benefits, cloud applications are becoming more popular in the technology industry.
Why should you use cloud applications?
Cost
The main advantage of cloud applications is that they save you money. Most of the cloud applications offer “pay as you go’ plans helping you pay only for the features you use. Also, there is no setup and maintenance cost in the traditional sense.
As cloud applications offer flexibility in terms of features, it is easier for you to upgrade them when a need arises. You can add more features to your existing plan and the investment is reasonable.
Security
Another major benefit of cloud applications is security. Since cloud services are offered by big companies, they can invest dedicated resources in improving the security of data and their services. They have more resources to invest in research and measurements to prevent data theft that may not be possible for a company that chooses in house data storage.
Flexibility
Cloud applications can be accessed from different devices by different users at the same time. You can access the same applications – if they are cloud-based – from a mobile or personal computer anywhere in the world. Due to this, cloud applications are the popular choice for big companies that spread across the globe or companies with a remote workforce.
Team collaboration
If you are a business that needs your team to collaborate on a large number of tasks, cloud applications are the best solutions. As cloud applications handle data instantly, sharing of information between team members becomes fast and secure. Some dedicated cloud applications offer their users the advantage of working on the same task simultaneously from across the globe. As a result, the execution of tasks takes less time.
Quality culture
Cloud applications can be used as a way to implement your company culture and quality control. As everyone in your team can access the same data and information stored in the applications, you can maintain quality standards, consistency in data formats and avoid human errors. It also helps with record-keeping as any updates from a user are automatically recorded by the cloud applications. Monitoring work progress and reviewing tasks will also become easier.
Low risk
As data is stored remotely and across multiple servers, the chance for data loss becomes less in the case of cloud applications. On the other hand, if you had gone with the traditional method of storing the data locally – in your company premises – any accident or natural calamities may lead to the loss of such valuable data. By storing data locally, you will also have the risk of data theft from a malicious insider.
Competitive edge
As mentioned earlier, cloud computing services are offered by big companies or companies that dedicate a good portion of resources in research and development in the latest technologies to cut down the competition for themselves. As they offer cloud computing as a service, it is natural for them to have competitors and the only way for them to stay in the business is to offer their clients – you – the best and latest services possible. As a result, when you opt for cloud applications you have a higher chance that you have the most up to date technology in your hand compared to your competitor who still uses traditional methods and invests their own limited resources on technology research and advancement.
Other benefits of Cloud applications
There is no need to install a cloud application on your device to get it working. Unlike traditional apps, they can work with the help of the internet and without using the resources of the local system. It also offers all features of a desktop app.
The main advantage of using a cloud application is that it uses many cloud servers that are placed across the world. So, the data is faster to retrieve irrespective of your location. Also, the data are more secure as they are remotely stored.
The virtual server helps the user to access the data from the nearest server thus decreasing latency.
Updations and deployment can be done quickly for a cloud app.
As only authorized users can access the data on cloud apps there is less data theft from internal parties.
Cloud applications offer mobility. A user can access the cloud app at any time, from anywhere. Usually, cloud applications support a variety of devices too.
Cloud-based services for app development
Infrastructure as a Service (IaaS): This includes services such as storage, security, and backup. IaaS is an important part of web architecture. Businesses get servers in which they can run their applications without giving the operational costs when choosing this service.
Platform as a Service (PaaS): Provides a platform for application creation. You can deploy your app at a low cost and significantly reduce the amount of coding.
Software as a Service (SaaS): Can be rented on a per month or per user basis. Applications managed by a third-party vendor are delivered through the internet. Can reduce the time spent on processes such as installing, updating etc.
Cloud application development
Now you already know that cloud applications offer several benefits for your business. However, these advantages can be taken away by bad development practices. If a cloud application is developed in the wrong way, it is more likely that it will handicap your business than offering you any advantages.
So to ensure the quality of the cloud application, the cloud application development companies should follow certain principles.
Cloud application development: Dos
Decoupling
One of the purposes of cloud applications is to store data separately, remotely, and safely. By storing the data on your application, you are not only sabotaging the purpose but also making your apps slower as it now has to handle data and operations. By separating data from the app you are making your app function faster as it now has to only take care of the processes it intended to do.
Separate logs
Technology is not immune to errors. Even if the application is built by the best developers, there are chances for bugs due to reasons out of their control. So keeping a log file of things is very important for every application.
However, if you store the logs in the local system, it is less accessible compared to storing them on third-party log aggregators. The use of third-party log aggregators will prevent situations where the logs are lost forever, become partially corrupted, not synchronized, or just simply not accessible.
Futureproofing
One of the reasons why businesses choose cloud applications is that they are easy to scale. However, scaling is not an easy task. If there are restrictions like the ones caused by bad coding, selection of improper platforms, components, or the environment, the application will be difficult or even impossible to scale. So, it is important that future-proofing should be implemented from the conceptualization phase itself.
Optimization
The advantage of cloud applications is that the data is stored remotely and separately. However, if poorly executed this can turn into a disadvantage.
Data is an important component of an application. To work as intended, the application should be able to communicate easily with the server and process the data faster. So it is important that each component of a cloud application is working as intended and the communication between these components is properly optimized.
Security
As the data are stored remotely and separately away from the local system, there is a higher risk of data vulnerability. To overcome this, the developers should adopt the best ways to make the communication between the app and server secure. Also, as cloud servers are a favourite target for hackers and people with malicious intent, you should always choose cloud services providers who follow strict security measures and adopt the latest technologies at a fast pace.
Go generic
Use a common standard for your codes, platforms, and topology. This will ensure that the app you built will fit in most cloud environments. It will also help you with the scalability of your applications as mostly the process will be automated and certain standards need to be followed.
Vulnerability checks
Periodically checks for vulnerabilities. Since Cloud applications work with the help of the internet there is a higher risk of data breaches and security exploit.
Consultation
Cloud technology is a fast-growing industry. New technologies are emerging day by day and the services are becoming complex. However, the client may not be aware of the complexity of cloud technologies. So, always try to educate them on the benefits of the cloud, what features will benefit them, what are the limitations and how the cost can be calculated.
Cloud application development: Don’t s
Security and privacy
Never neglect data security and privacy. Two of the major concerns when it comes to cloud applications are how secure the application is and whether it values user privacy. Follow strict policies on security and privacy and always adopt the latest trends in these fields.
Downtime
Server outages can be common. However, it must be avoided when it comes to cloud applications as without server connectivity the application will not work. For most businesses, it will affect their day-to-day functions and revenue.
Complexities
You won’t be seeing yourself moving to the cloud anytime sooner. However, that does not eliminate the possibility of you adopting cloud as the requirement changes in the future. As mentioned earlier, you should always keep this possibility in mind and avoid any complexity in the system which will hinder the process.
Don’t test your luck
There are several companies offering almost the same cloud services. But that does not mean that all of them offer the same quality of services. Instead of trusting your instinct you should carefully evaluate your options, study what their services offer, check their customer feedback and review their service level agreement (SLA). Switching between various cloud providers may not be easy and it will cost you a lot of resources and expertise.
Don’t force
Never force all your existing applications to migrate to the cloud. It is common that big corporations have hundreds of applications in their arsenal. However, not all of them will be suitable to migrate to the cloud. A few may not be worth migrating when evaluating the cost and benefits. So, prioritize the applications based on the value when it comes to cloud migration.
Don’t underfund
Never try to save money on cloud migration and the process by underfunding. You should first analyze whether it is beneficial for your business to move to the cloud. If yes, make sure that the process is well-governed, monitored, and implemented. That way you can save more money in the long term and avoid any pitfalls due to quality issues.
Documentation
Never forget to document everything. It will not only help you with reevaluating the process if any pitfall occurs but also help your team with future development. Without documentation, your team will not have any clarity on the limitations of the application and the environment and it will be difficult for them to envisage a roadmap for further development of the application.
Cost
Never forget to start the process with a cost analysis. Approach a good application development company that is an expert in cloud-related services. They can help you with evaluating the cost most accurately as there may be additional or indirect costs that you may miss out on. For example, as a business, you may not know the right cloud architecture for your application or you will not know the additional cost associated with optimizing the application prior to moving it to the cloud. A cloud application development company can easily identify them.
Hiring cloud application development company
Before hiring a cloud application development company, consider some of these points:
Define your goals prior to approaching a cloud application development company. Having a perfect understanding of your goals helps the cloud application developer to plan and execute the project easier.
Analyze if your application is suitable for migrating to a cloud. There might be a need for a complete rewriting of the application.
Select your deployment model-whether it is a private cloud or a public cloud. Private clouds are more costly. Public clouds are less costly but there is a higher risk of security.
Build custom cloud management platforms to keep everything in checks such as the security and application performance.
Prior to deployment, test the cloud app for potential security risks. Testing should also be done to ensure optimal performance.
Before hiring a cloud application development company, always research their credibility. Choose one which is following global standards for data processing and handling.
Make sure that the cloud platforms have containers. Containers are used to divide the applications into components which help in easy deployment.
Conclusion
Moving to the cloud has its own benefits. However, these benefits come with their own complexities. While cloud applications are becoming more popular and they are replacing traditional applications across multiple verticals, businesses need the assistance of an expert in the field to reap the actual benefits of the cloud. AlignMinds has more than a decade of experience in developing best-in-class applications in mobility and cloud platforms. If you are searching for a technology partner for your next project, contact us now.
