Top 10 Challenges to Becoming Cloud Native
The operational paradigm of the cloud is fully utilized by cloud-native apps, which generate business value through auto-provisioning, scalability, and redundancy.
Developers design apps that can grow easily in response to market demand by disassembling monolithic applications into separate but interconnected containers.
Fundamentally, cloud-native computing enables you to build and deploy code anywhere you want, including private, hybrid, and public cloud settings.
According to the Cloud Native Computing Foundation (CNCF), there are approximately 11.2 million cloud-native developers, and the usage of cloud-native architecture is continually expanding.
Image Source: confluent dot io/ design consideration for cloud
Even though cloud-native computing sounds amazing in principle, it isn’t always simple or quick to execute, particularly if your company has old, legacy apps.
Because so many platforms and technologies are competing and overlapping in the cloud native market, it’s easy to become overwhelmed.
You must not only implement cloud-native products that are tailored to your particular needs, but you must also encourage their use through cultural changes. Implementing reforms and changes should be done gradually yet comprehensively.
Here are ten of the issues that businesses encounter most frequently when moving to a cloud-native infrastructure.
What is Cloud-Native?
Before we start the discussion of the challenges associated with using cloud-native infrastructure, let’s have a quick talk on the cloud-native infrastructure.
The concept of creating and executing applications to take advantage of the remote computing capabilities provided by the cloud delivery paradigm is called “cloud-native.”
Cloud Native Apps are created to take advantage of the cloud’s size, scalability, resilience, and flexibility.
According to the Cloud Native Computing Foundation (CNCF), scalable applications can be developed and operated on public, private, and hybrid clouds thanks to cloud-native technology.
This strategy is best illustrated by features like containers (itcompanies dot net, benefits of contanerization), service meshes, microservices, stateless infrastructure, and unambiguous application programming interfaces (APIs).
These properties enable robust, controllable, and visible loosely coupled systems.
They enable engineers to quickly and regularly make significant modifications.
A recent study by Gartner predicts that by 2025, over more than 95% of the latest technological workloads—up from 30% in 2021—will be hosted on cloud-native platforms.
Top Ten Challenges That Businesses Deal with When Moving to a Cloud-Native Infrastructure
1. When Using a Utility Model for Payment, Inefficiencies Become a Big Deal
Teams may be accustomed to utility-style pricing for both physical and virtual servers they have purchased, but this is not the case for cloud-native infrastructure.
Cloud-native design entails extra expenditures, which you’ll really have to control in a utility-style pricing model effectively. The price varies and relates to how much is used.
You have a variety of scaled sunk costs, including physical or virtual computers, with on-premises installations and more conventionally moved designs.
As a result, using serverless functions as a replacement is one upgrade option.
However, if not accurately identified, serverless services alone can cost more in cloud-native systems.
If your operation is scale-out developed, high storage, high concurrency, and lengthy functions can dramatically raise the expenses. With cloud-native infrastructure, it’s essential to spot wasteful cloud resources to prevent unforeseen expenses.
2. You Deal With Temporary Components and Mutable Microservices
You have a predetermined, limited pool of computing resources when using hosted or on-premises servers. On the contrary, cloud-native microservices are mostly on-demand, flexible in terms of number and durability, frequently unstructured, and transient in nature, lasting only as long as they are required.
It can be challenging to pinpoint what ended up going wrong in the recent past if a microservice has evolved or stopped working.
3. The User Doesn’t Know Much about the Underlying System
A major obstacle to switching to cloud-native infrastructure is basically a lack of knowledge and insight. Since you are unaware of the process of dealing with the infrastructure, it creates lots of confusion.
First, it is important to know the source services to learn more about the infrastructure. You require an observability solution that can assist you in identifying the source services.
The observability platform will also help you in determining the issues, if any. The observability solution will even identify the issues if they are with cloud-based infrastructure but not under your administrative supervision.
You may get visibility through the monitoring services offered by cloud suppliers by examining your entire system; this aids in figuring out what is wrong.
4. Security Becomes More Crucial but Also More Challenging
We don’t consider security on a daily basis, but when a significant incident occurs, it becomes evident how crucial it is to maintain it.
When it comes to security, that lack of accessibility, as well as awareness that was mentioned in the prior challenge, becomes much more troublesome. You can overlook certain significant security concerns since it is difficult to observe everything.
The cost of analysis and investigation escalates when there is a large amount of security data to review. You must decide which data on cloud-native infrastructure is valuable.
It’s challenging to impose uniform regulations in systems that use many clouds, hybrid clouds, and a variety of technologies. An improperly constructed cloud infrastructure is vulnerable to assaults.
In addition, you must be able to react swiftly.
Cloud security is just as difficult and complicated as conventional apps. It is essential to be vigilant about potential hazards.
Companies must create strong security procedures by maintaining a secure network for their cloud systems, such as cloud-based IP security cameras (avigilon). This can help safeguard every component of their network against cybercrime as attackers increase their attack surfaces and find new loopholes in the infrastructure.
5. Service Integration Issue
Commonly, cloud-native applications are built from a variety of services. In contrast to monoliths, they are more adaptable and scalable, thanks to their dynamic nature.
However, it also implies that in order for cloud-native workloads to succeed, there are a lot more moving parts that must be brought together in a smooth manner.
As developers create cloud-native applications, they must partially deal with the issue of service integration.
A smart practice is constructing a separate service for each sort of operation inside a workload rather than attempting to make a single service accomplish several things.
They must make doubly sure that each service source is appropriately scaled. Additionally, it’s crucial to refrain from incorporating additional services simply because you can. Verify and ensure that the service furthers a specific purpose upon adding more complexities to your program in the form of a brand-new service.
Successful service integration relies on selecting the appropriate distribution methodologies in addition to the core design of the application itself. The most logical approach to deploy many services and combine those into a unified task is probably using containers. However, serverless functions or non-containerized programs coupled through APIs may be preferable in other situations.
6. Constructing Apps with Cloud-Native Delivery Pipelines
Cloud-native apps operate online. The cloud refers to unchangeable architecture and cloud management procedures, regardless of whether it is running on your firm’s settings as a private, public, on-premises, or hybrid cloud.
However, many application delivery pipelines are still based on traditional on-premises settings that have not been cloud-ified or are inefficient when combined with programs and services that run in containers or on public cloud environments.
This presents difficulties in a number of ways. One is the potential for delays when distributing code from a local or private environment to an on-premises system. Another is the difficulty in simulating production settings when creating and analyzing locally, which might result in unpredictable application behavior after deployment.
One of the most efficient ways to get past these obstacles is to relocate your CI/CD pipeline into a cloud system. This will allow you to take advantage of the cloud’s scalability, infallible infrastructure, and other upsides while simulating the production system and bringing your pipeline as near as possible to your applications.
The code is developed closer to the deployment location in this manner, hastening distribution. Additionally, it becomes simpler to create test environments that are exactly like real-world ones.
Not everyone prefers an entirely cloud-based production system, as some programmers prefer the comfort and efficiency of local IDEs over cloud-based ones.
Nonetheless, attempt to ensure your CI/CD pipelines are operating in a cloud environment to the greatest extent possible.
7. Organizational Change and Teams with Appropriately Skilled Personnel Are Both Necessary: If Not Available, It Becomes an Issue
Businesses and different organizations discover that their teams’ DevOps approach and culture must change to CI/CD pipelines when they make the switch to dealing with cloud-native infrastructure. Teams will need unique skills and abilities as they transform their work culture.
In a cloud-native system, all team members must participate fully when disruptions occur. Cloud architect abilities will require to be developed by teams.
Developing and designing apps based on microservices, containers, and Kubernetes, as well as those that make use of public cloud services, all require specialized knowledge.
The cultural change required for cloud-native architecture readily fits with an observability-focused culture. Everyone, including the operations and research teams, requires observability whenever micro-failures are anticipated and swiftly handled.
Performance indicators like Apdex, average response time, error rates, and throughput are important to both dev and ops engineers.
You can swiftly respond to these failures and unwanted situations via observability. You gain the ability to move more quickly.
8. The Cloud-Native Design Is Intertwined with Reliability Problems
To prevent reliability problems, you must construct the proper approach to leverage cloud platforms and their capabilities, even when using a cloud. It can be difficult and expensive to achieve reliability when certain groups use multiple environments.
You should be able to track your reliability or dependability within a single cloud. Then, you’ll be able to monitor stability and performance data like the page’s poor load time to determine whether or not your strategies are effective.
It is not sufficient to design for reliability; you also have to be able to track reliability and performance from the user interface on the front side to the backend web infrastructure.
There are many distinct forms that reliability can take. Frequently, you may not be aware of your hazards. Therefore, you cannot decide on a massively scalable architecture without continuing to observe.
An observability tool is required to determine where your reliability is profitable.
9. Management and Oversight Problem
The more services that are active within an application, the more challenging it is to oversee and control them. This is valid not only because there are many operations to keep track of.
Additionally, the need to maintain the functionality and stability of an application necessitates observing interactions between services in addition to the systems or services themselves.
Therefore, to effectively track and control operations in a cloud-native system, it is necessary to adopt a strategy that can foresee how errors in one service will affect others and identify the most crucial problems. Dynamic baselining is also criticized since it involves swapping out static criteria with ones that continuously evaluate application environments to identify what is acceptable and what is an aberration.
10. Service Provider Lock-in and Restricted Room for Expansion
You can now experience vendor lock-in if you previously made a strong commitment to a system or technology.
Although, in general, cloud providers’ platforms are packed with features and are easy to use. However, they frequently come with a lock-in penalty.
In the end, cloud-native computing is about enabling you to utilize massively scalable cloud providers while still having the option to take into account multifaceted and hybrid-cloud infrastructures.
According to a Statista study report, the most common cloud-native use case within enterprises worldwide in 2022 will be the re-architecture of proprietary solutions into microservices, with about 19% of those polled suggesting as much.
The participants rated application deployment and testing as the second-most widely used use case.
However, adapting to the cloud is challenging regardless of how you look at it. Cloud-native applications are more complicated and contain many more potential points of failure than conventional application systems.
The difficulties associated with cloud-native computing may be solved, and doing so is essential to achieving the responsiveness, dependability, and scalability that only cloud-native systems can provide.
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