Business success today depends on the reliability of cloud infrastructure. Any downtime damages the brand reputation, causes revenue loss, and leads to permanent erosion of customers.

Maintaining customer trust and optimising business operations depends on a resilient cloud architecture. A resilient cloud operates reliably even in the face of any stress or disruption.

Here are the best practices to build resilient cloud architectures for modern enterprises.

Embrace Cloud Native Architecture with Microservices

Conventional applications are monolithic. These applications have a single codebase and deploy as a single unit, on a single server. The components remain tightly coupled and interdependent.  A  good example is a monolithic e-commerce website. The user interface, catalogue, cart, and payment processing in a single codebase makes changes hard.

In today’s uncertain and fast-paced business environment, such monolithic applications retard progress. It becomes difficult to scale or update individual components. And a failure in one component takes down the entire application. Often, the only recourse is to scale the whole application or redeploy the entire monolith.  

Cloud-native architectures, built on microservices and containers, make applications scalable, flexible, and resilient.

Microservices break down applications into smaller, independent components. These components are often loosely coupled. Changes in one component do not require changes in other components,  except in cases of shared databases or libraries. The integration depends on events that trigger scripted actions.

Containers offer a lightweight and portable environment for running microservices. It enables consistent deployment across multiple servers and even different providers.

Microservices allow easy code changes. Changes or updates to any independent microservices do not affect the other parts of the application.  Likewise, scaling only the required part consumes resources. 

Microservices also enable independent fault isolation to localise the impact of failed components. For instance, each microservice can have different data stores, such as object storage or backend databases. Issues in any of these backend data stores limit the failure of the specific microservices.

A monolithic architecture may still suit smaller applications with limited complexity and scalability. Such an architecture is simpler to develop and deploy. But for most mainstream applications, a microservices approach is the way to go.

Adopt Serverless Computing

Along with microservices and containers, serverless computing makes the cloud architecture more resilient.

Traditional networks have static hardware sizing and manual configurations for scalability. This causes hardware underutilisation of hardware during low volumes. And during peak volumes, performance issues surface. Oversizing becomes the norm.

Serverless computing automates provisioning, management and scaling.  The service provider configures the platform to scale resources based on real-time demand. The platform supports highly elastic applications. It becomes resilient to handle traffic spikes without performance degradation or outages.  

Most providers also offer built-in retry mechanisms to cope with transient errors. The application executes successfully, overcoming temporary issues.  Likewise, security patching and updates also take place in auto-pilot.

Design for Failure

In today’s complex environment, too many variables remain outside the control of the enterprise or the cloud service provider. Natural disasters, cyberattacks, hardware failures, power outages, and human errors have become common. It is not possible to foresee and prevent all such scenarios. Business resilience depends on the ability to recover from major downtimes, be it due to a or any other cause, in double-quick time.

A design-for-failure approach integrates fault tolerance into the cloud architecture design. The approach assumes failures will happen. It implements redundancy at every level to mitigate the impact of such failures. The main approaches to design for failure are:

• Fault domain. A logical grouping of hardware and infrastructure minimises the risk of correlated failures. Instances and resources get distributed across multiple physical servers within a data centre. Each domain gets its dedicated power and networking infrastructure and remains isolated. If one fault domain experiences a failure or outage, other domains operate as usual.
• Graceful degradation. Many cloud networks are complex, with intricate dependencies and distributed systems. In such an environment, a complete and seamless failover is challenging, if at all possible. In such situations, graceful degradation is more viable. Here, the system continues to operate with reduced functionality. Core services or essential functions remain available even during failures. For instance, an e-commerce website might disable personalised recommendations. A social media platform might disable image uploads.

Ensure Load Balancing

Load Balancing distributes the infrastructure across multiple availability zones (AZ) and regions. Configuring DNS routing rules sends traffic to such infrastructure spread over multiple regions.

Load balancing works through several techniques. 

• Geographic distribution of resources protects from localised outages and ensures any-time availability. Automated failover mechanisms switch to the replica components.
• Session persistence ensures all requests from a single user during a specific period go to the same server. This prevents degradation of the customer experience.
• SSL termination decrypts HTTPS traffic at the load balancer instead of the backend server. The burden on backend servers reduces allowing the system to cope better with high traffic volumes.
• Health checks monitor the health of instances and direct traffic only to healthy and responsive backend servers. It removes traffic to non-functional instances, to pre-empt downtime.

A load balancer also makes it easy to implement autoscaling.

Enable Seamless Integrations

Any enterprise cloud network would require the integration of diverse applications. But custom peer-to-peer integrations become costly and difficult to maintain. Developing the integration is hard enough. Ongoing maintenance, updates, and debugging become a big headache, and downtime becomes common. As the network expands, scalability becomes an issue,

Cloud-based Integration platform-as-a-service offers a centralised environment to connect diverse applications. The data flow also gets streamlined. These platforms automate the end-to-end process, and scale resources as needed.

Platforms such as Infor ION offer seamless integrations regardless of the deployment.

Prioritise Security

In today’s era of heightened attack security-related disruptions are a big menace. Hardcoding security in the design makes the architecture resilient.

The best security approach is multi-layered and co-opt:

• Zero Trust, which always authenticates the user or device and monitors the traffic for any abnormality.
• The principle of least privilege. Every component operates with the minimum necessary permissions. Identity and access management (IAM) roles and policies enforce this principle.
• Defence in depth, or a multi-layered approach. Multiple protection layers, such as firewalls and encryption ensure protection even if one layer fails. 

Regular review and policy updates have become indispensable in today’s ever-changing landscape. 

Implement Observability

Comprehensive monitoring and observability offer insights into system health and performance. Monitoring the workload components unearths anomalies and enables nipping issues in the bud.

Techniques such as logging, metrics, and tracing detect anomalies and potential issues. Configuring alerts and notifications allows system admins to respond to incidents, fast.

For effective monitoring, collect logs into a central logging system. Also, keep track of baseline measurements, such as the standard response time to a customer request. Measure anomalies based on the deviation from such baselines.

Test Regularly

Sustaining resilient cloud architecture requires periodic, thorough testing.

Performance testing and disaster recovery drills make the architecture capable of withstanding disruptions. 

Another good way to test network resilience is chaos engineering. Controlled disruptions check the ability of the system to withstand real-world stress. Examples include adding load on disk volumes or injecting timeouts when the application connects to a database. 

Automate Backup and Recovery

Automated backup and recovery capabilities protect against data loss and corruption. One time-tested best practice is a point-in-time recovery strategy. Increment backup allows seamless recovery from accidental deletions, data corruption or malicious attacks.  

Automated, self-healing workloads detect failure and recover from it all by itself. For instance, it replaces failed components, restarts services, or switches to another AZ or region. But automated recovery may not always work, especially during major failures.  A failover plan becomes essential for large networks.

Choose the Right Cloud Provider

There are several cloud service infrastructure providers. The obvious consideration is to partner with a provider who aligns with the specific business needs. One robust, yet cost-effective option, cutting across industries, is Infor. Infor leverages innovation and uses AI to deliver cloud resiliency and top performance. The power and responsiveness of Infor’s system architecture help businesses become competitive.