Cloud Native Engineering - Anti-patterns

Introduction

Most companies today are widely adopting digital infrastructure and cloud workspaces, as they guarantee fast workflows, impressive returns, and better business management. By 2028, cloud computing will shift from being a technology disruptor to becoming a necessary component for maintaining business competitiveness, according to Gartner. It is not only expected that more than 50% of enterprises will utilize cloud platforms to accelerate their business initiatives, but by 2028, most organizations will be leveraging the cloud as a business necessity.

Common Anti-Patterns

This section discusses several common cloud-native anti-patterns and provides suggestions for avoiding them.

• Monolithic Thinking in a Microservices World
  Cloud-native applications are primarily characterized by loosely coupled, independent, and modular components, often referred to as microservices, which enable faster development, deployment, testing, and scaling for each element. However, at times, some cloud-native applications still adopt monolithic architecture, where all functionality is bundled into a single, large, and complex application. This makes it harder to update, maintain, scale, and troubleshoot the application, as well as to leverage the benefits of cloud services and tools.
  To avoid this anti-pattern, it is essential to break down the application into smaller, cohesive, and manageable units that can communicate through well-defined interfaces and protocols.
• Treating Cloud-Native as "Lift and Shift"
  Another common cloud-native anti-pattern, known as lift-and-shift migration, involves migrating an existing application to the cloud without modifying its original design, configuration, or code. Although it seems like a quick and easy way to move to the cloud, it can result in suboptimal performance, compatibility issues, wasted resources, and higher costs. Lift-and-shift migration does not leverage the cloud-native features and capabilities, such as elasticity, automation, observability, and security.
  To avoid this anti-pattern, one should analyze the application first and then identify the areas that need to be modified, optimized, or refactored to fit the cloud-native model. One must also utilize cloud-native services and tools that can enhance the application's functionality and efficiency.
• Overprovisioning resources
  Provisioning resources on demand and paying only for what is used is one of the key benefits of cloud computing. However, a problem arises when some cloud-native applications overprovision resources, either by allocating more than necessary or by failing to release them when they are no longer required, resulting in unnecessary costs, waste, and inefficiency. Overprovisioning resources can also affect the performance and availability of the application, as well as the environment and sustainability of the cloud.
  To avoid this anti-pattern, monitoring and measuring an application's resource consumption and utilization become crucial. One must utilize cloud-native techniques, such as autoscaling, load balancing, serverless computing, and containers, to dynamically adjust resources according to the application's needs and demands.
• Improper Use of Auto-scaling
  Without proper configuration, auto-scaling that manages all traffic surges can lead to significant issues. Relying too heavily on reactive rather than predictive scaling, and lacking complete horizontal or vertical scaling policies, applications may experience performance degradation during traffic spikes and incur higher infrastructure costs due to over-provisioning.
  To avoid this, it's essential to implement scaling with custom metrics (such as CPU, memory, and application-level metrics), utilize Cluster Autoscaler for node-level scaling, and combine autoscaling with traffic control techniques like rate limiting.
• Insufficient Automation Capability
  Deploying microservices without proper automation can lead to significant challenges, including slow-release cycles, increased errors, and difficulties in scaling due to manual processes becoming bottlenecks.
  To avoid these issues, implementing a robust CI/CD pipeline with automated testing, build, and deployment processes, and leveraging Infrastructure as Code (IaC) is essential. This approach streamlines the workflow, reduces errors, and enhances scalability
• Ignoring Observability and Monitoring
  One of the key challenges of cloud native applications is that they are distributed, dynamic, and complex, making it harder to monitor, debug, and troubleshoot. A common cloud native anti-pattern is ignoring observability, resulting in poor quality, reliability, and user experience. Observability is defined as the ability to understand the internal state and behavior of an application by collecting and analyzing data from various sources, such as logs, metrics, traces, events, and alerts.
  To avoid this anti-pattern, implementing observability as a first-class citizen in application design and development is the sole viable option. One must also utilize cloud-native tools and platforms that can help collect, aggregate, and visualize observability data.
• Neglecting security
  One of the key risks associated with cloud-native applications is that they are significantly more vulnerable to threats and vulnerabilities compared to traditional applications. Neglecting security is a common cloud native anti-pattern that can compromise an application's integrity, confidentiality, and availability. Security is not something that can be added later or delegated to someone else. It is something that one must consider and embed throughout the application's lifecycle, from design to deployment and operation.
  To avoid this anti-pattern, it is recommended to adopt a security-by-design and security-by-default approach. To protect the application from malicious attacks or unauthorized access, one must employ cloud-native best practices and standards, including encryption, authentication, authorization, auditing, and compliance.

Conclusion

One can avoid cloud-native antipatterns by careful planning, adopting best practices in architecture, and utilizing the proper tooling. By designing loose coupling, security, observability, and scalability, organizations can fully leverage the benefits of cloud-native environments while avoiding common pitfalls.

Coforge Advantage

Coforge has the experience to assist you if you are considering cloud-native application development. With a combined workforce of over 4,000 professionals from product engineering and cloud practices on board, we have the necessary expertise to apply cloud-native best practices and deliver modern applications for your business. Coforge has an extensive portfolio of cloud projects in different industries, including banking, Insurance, travel, healthcare, and more. We collaborate with the leading global cloud providers and have a Preferred Partnership with Microsoft Azure, AWS, and the Google Cloud Platform.