Cloud-Native Applications

Building up Cloud Maturity

Rethinking application lifecycle management, from system architecture through app monitoring, in a manner conducive to cloud characteristics allows you to take full advantage of the cloud. We enable clients to move their systems through the various levels of cloud maturity by adopting application-centric design and automation along with managed services from mature cloud vendors.

Utilizing Cloud Services

Adoption of cloud services is the primary characteristic of any cloud-based system. At the very least, an application may use cloud storage, compute, or monitoring infrastructure. When an application is migrated to the cloud using the lift and shift approach, it makes use of just the basic building blocks. Such systems are at a low level of cloud maturity but enjoy the fundamental benefits of being on the cloud.

While the lift and shift approach may be ideal in certain cases, such as at the outset of your cloud journey, we can take you through even higher levels of cloud maturity. Systems can be configured to utilize managed services for caching, load balancing, etc., or even advanced services such as serverless computing in addition to the rudimentary storage and compute options.

Much of the “undifferentiated heavy lifting” done by your team can be transferred to the cloud vendor through the adoption of managed database services, load balancers, caching mechanisms, data warehouses, or search and automation tools. Managed services will enhance your team’s agility and allow them more time to focus on tasks that add business value.

The highest level of cloud-native maturity is when everything required to run and scale your application is managed by the cloud vendor. Serverless computing service, for instance, lets you run large applications without provisioning, scaling, or managing any servers. Using such managed services can enable some of the most advanced cloud-native architectures.

Basic cloud building blocks - compute, storage, networking, monitoring

Managed services - database, caching, directory services, load balancers, data warehouses, search, automation tools

Advanced services such as serverless and AI/ML services

Adopting Application-Centric Design

On-premises infrastructure is centralized with everything at a single location. In contrast, servers and databases are distributed in the cloud. Mirroring the structure of the cloud while designing and architecting your applications can make them better suited for the cloud platform.

The 12-factor app is a design methodology for building applications such that they can be deployed to modern cloud environments and scaled up without much changes in the architecture, tools, or practices. Such apps will enjoy maximum portability and minimum divergence between environments. Designing your app based on the 12-factor methodology can ensure a higher level of cloud-native maturity.

Many legacy applications have a monolithic architecture with all the components combined into a single unit. To grow in cloud-native maturity, applications need to have a modular structure. Microservices-based applications where each service is fully autonomous and has little or no dependency on other services (loosely coupled) are ideal for cloud computing.

Other considerations for cloud-native architecture include built-in instrumentation, security, parallelization, and resiliency. Applications designed to execute processes in parallel will be better equipped to scale and designing for security allows smoother adoption of cloud security services. Instrumentation as a design consideration can lead to a self-aware application built to detect component failures or latency issues and automatically resolve them (self-healing capacity).

Leveraging Tools for Automation

To take full advantage of cloud offerings, you will need to automate the operational aspects of the application too. This involves developing code for environment setup and configuration.

When a change in the environment becomes necessary, the infrastructure as code (IaC) can be executed to replace the existing infrastructure in full. Such an approach will give you an immutable infrastructure that allows for little or no configuration drift.

In large and complex environments where full replacement of infrastructure is not always feasible, changes can be made at the component level. Using automated scripts will ensure changes are implemented with consistency.

Infrastructure, when written as code, can be handled similar to application code using source control systems. We can configure tools for a fully automated deployment pipeline (CI/CD) that will automate both infrastructure and application code deployments giving you agility and consistency.

At the next level, monitoring of the entire system and usage optimization of resources can be automated. Cloud monitoring services can be configured to detect traffic spikes and fire up additional instances or shut them down to balance the load (autoscaling). Automated compliance audit checks can also be implemented with logging frameworks built to analyze logs and detect anomalies in real time.

At an even higher degree of automation, AI and ML can be used to predict how events could impact the system and take proactive measures to avoid performance or security degradation.

IaC, Immutable infrastructure, CI/CD

Monitoring, compliance, and optimization through automation

AI/ML: Predicting failures, self-healing, self-optimizing