The pace we are moving at requires the software industry to change. In particular, we need to modernize our architectures and move to a more cloud native model.
It is challenging and requires many moving parts to work together to allow businesses to scale at pace.
Moving from the traditional on-premise data center to the cloud takes work. The journey is full of pitfalls, and you’ll need to know essential details about cloud-native infrastructure to make your way through it successfully.
What Are the Top 6 Challenges of Cloud Native Infrastructure?
Cloud-native infrastructure is a hot topic right now. It’s a new way of thinking about how we build, deploy, and run our applications that promise to make life easier for developers by giving them more control over the infrastructure that powers their applications.
But cloud-native infrastructure isn’t easy to implement, and it requires a lot of changes to how we think about software development and operations, which means it has its own set of challenges.
Here are some common challenges with cloud-native infrastructure and how you can overcome them:
1. Security
The first challenge is security. Cloud-native environments are less secure than traditional ones because they use open-source tools and components. This means they can be vulnerable to third-party attacks or insider threats.
Your cloud-native environment’s security will depend on how well you use the tools that your cloud provider gives you. If you don’t know how to use them properly, you may create a bigger problem than what you started with.
Hackers find it easier to get to sensitive data and information stored on cloud platforms because they can quickly deploy apps. Security should be a top priority when developing your cloud strategy, whether for cloud security cameras or a cloud-based data server.
2. Monitoring & Managing Resources
The second challenge is monitoring and managing resources effectively. A major issue is making the shift to microservices.
With a microservices architecture, it becomes difficult to monitor each service because so many of them are running at once on the same physical server.
Also, it’s hard to manage resources efficiently without knowing what is happening inside each container at any given time.
Microservices are a style of software architecture in which an application is broken down into small, independently deployable services, each of which has a single responsibility.
This makes it easier for developers to work independently on different parts of an application at once, allowing them to scale up or down as needed.
3. Testing For Availability and Performance
To ensure that your applications are ready for production, you must test them thoroughly in a staging or test environment.
You also need to test your infrastructure before deploying it into production. This includes testing for availability and performance to ensure that your site will work properly with your new infrastructure.
Unfortunately, there’s no easy way to test for availability and performance with cloud-native infrastructure. You can’t just copy the code from one environment to another because there isn’t a single point of failure.
All components are distributed across multiple regions and zones, meaning each component must be tested independently.
4. Performance & Scalability
Performance is an important consideration when designing your application architecture on any platform, including cloud-native infrastructure, because it directly impacts the end-user experience.
High availability, scalability, and resilience come into play here, too, so organizations need tools that support all three at once without disrupting users or operations during maintenance.
It is challenging to run an application on multiple containers to perform as well as a single instance of the application because each container has its resources.
The more containers you run, the more difficult it becomes to optimize performance across them. This can also lead to problems with scaling when your application needs more resources than what is available in a single container.
5. Data & Application Portability
The cloud is a great place to store data and run applications, but it’s not the only place.
You might have a lot of data on-premises or in a private or hybrid cloud that you need to integrate with your public cloud services. And you might want to move applications between public clouds.
While this is possible, it can be challenging and cost-effective. Data portability can be difficult because the data format may be proprietary and not easily converted into other formats.
And while there are tools that help with application portability, they’re not always easy to use — and they require support from both vendors and users.
6. Observability
Cloud-native environments are built with containers, microservices, and serverless functions that run on top of virtual machines or bare metal servers.
This creates a challenge for observability because each component is designed to be independent of one another — not necessarily designed with observability in mind.
For example, containers can be stateless and ephemeral; therefore, monitoring them requires understanding what’s inside each container at any given time. Cloud-native infrastructure is not easy to monitor and troubleshoot.
The dynamic nature of containers and serverless architectures makes it difficult to collect metrics and logs from applications running on them.
Companies have to set up a separate monitoring system for each application, which becomes expensive when you have hundreds or thousands of applications running in your environment.
Which Solutions Can Help Overcome the Challenges?
Cloud-native infrastructure is based on the concept of “software-defined everything.” It’s an approach to building and managing IT systems that deliver agility, cost savings, and operational efficiencies.
The concept includes microservices, containerization, serverless computing, and DevOps automation.
Cloud-native infrastructure enables organizations to build and manage applications as a single entity rather than as separate components. It allows them to deliver applications faster while maintaining control over their resources.
1. Security
Security in the cloud can be managed through encryption and access controls, but this must be done at both the application and infrastructure levels.
Encryption can help protect data in transit as well as at rest. While encryption doesn’t necessarily prevent an attack, it will make a breach more challenging to exploit and make stolen information more difficult to decode.
Access control helps ensure that only authorized users can access sensitive information or applications.
For example, you may want to restrict access to sensitive data only to those users who need it for their jobs — limiting access beyond this group would help lower your risk profile and make attacks less likely to succeed.
2. Monitoring & Managing Resources
Monitoring tools such as Middleware, Prometheus, and Grafana can help give you insight into your cloud-native environment.
These tools facilitate the creation of dashboards that provide visibility into application performance metrics such as CPU utilization, memory consumption, and disk I/O rates.
You can also use them to monitor other aspects of your infrastructure, like container health or network utilization.
A virtual machine can be managed using traditional tools such as VMware vCenter Server and vRealize Operations Manager.
But when multiple VMs are combined into one container, it becomes more challenging to use these tools. You need solutions that can monitor the health of your containers, including Docker and Kubernetes.
3. Testing For Availability and Performance
Automated testing can be done at every stage of development. Automated testing allows developers to run tests as part of their workflow to detect any issues early in the development process.
This saves time and money since it enables teams to fix issues before code is deployed into production environments where customers are impacted directly by outages or slowdowns in performance.
Because cloud-native applications are designed to scale horizontally, it’s crucial that they can scale up and down automatically as needed.
This means that any test should be able to simulate load on the application’s API layer or microservices layer without manually scaling the number of instances involved.
This can be done using tools such as Gatling and LoaderBot, which allow you to simulate high volumes of requests simultaneously.
4. Performance & Scalability
Use tools like Middleware, Kubernetes cAdvisor, or Prometheus for monitoring and alerting so you can spot bottlenecks before they become too serious.
You can also use distributed tracing tools like Jaeger or Zipkin to track down where requests are failing so you can optimize them at their source rather than looking for solutions further up the chain after they’ve already failed once or twice.
There are several ways to overcome this challenge:
Load balancing: Load balancing ensures that the load is distributed equally across multiple instances of an application so that no single instance becomes a bottleneck. It also provides that others can pick up the slack if one fails.
Auto Scaling: Auto scaling ensures you have sufficient resources to run your application efficiently.
When there’s high demand for your application, auto-scaling will automatically add more instances when needed; when demand decreases (e.g., after business hours), auto-scaling will shut down unused instances to save money and improve efficiency.
5. Data & Application Portability
A good solution is using an open-source tool such as OpenStack’s Heat Orchestration Template (HOT) engine, which can orchestrate workloads across different environments.
Fortunately, there are solutions available to address this problem. One example is CockroachDB which claims to be “Google Spanner meets SQL” but is open source and fully distributed.
This challenge can be solved by leveraging Cloud Native Infrastructure (CNI). CNI provides a standard set of APIs for application developers to write applications that can run on any public cloud with minimal or no modifications.
6. Observability
Use a monitoring tool that provides end-to-end visibility across all layers of your application stack.
It automatically discovers all your applications, collects metrics about them, monitors performance, and alerts you if anything goes wrong so that you can take action early on.
You can often use a tool that collects metrics from your applications and stores them in a time-series database (TSDB). This allows you to query your data using a query language. You can then visualize the results.
Wrapping Up
Cloud-native infrastructure is a growing trend that companies are adopting across the board, but with any new concept or technology, there will be challenges. You’ll need to change your existing processes and tools to overcome the obstacles and reap the benefits.
While there is no silver bullet to solving these problems, getting started with techniques like service modeling and design can help your organization take advantage of the cloud.
