Developing cloud-based applications needs a modern mindset along with the implementation of newer rules. When the cloud is used effectively, it can help both small and large enterprises with a wide range of activities. Consider the following factors to create a scalable cloud application.
Reflecting on the Topology
One of the leading reasons behind the use of cloud systems is that it helps businesses scale their applications at will. Often, virtual applications are implemented to attain this type of scaling.
Instead of limiting yourself to a certain topology, you should consider how to protect your cloud applications from the dynamic scaling impact. If you can design a generic application, you can prevent your application from struggling with negative effects during the cloud migration. In case your application is using a singleton state, developing a backup through a shared repository can assist you before the cloud migration.
Pondering Over Design
Designing the appropriate scalable cloud architecture which also aligns well for business risk requires the right combination of security policies and design principles. For a cloud system, you should have the tools for designing, implementing, and refining your policies for enforcement, and controls in a centralized approach.
These tools allow developers to equip the network layer with security through solutions like host-level firewalls, VPNs, access management, and security group. For the operating system layer, they can take advantage of strict privilege separation, encryption storage, and hardened system. While dealing with the application layer, they can benefit from carefully enforced rules and the latest updates. The idea is to implement these solutions in conjunction for the design and development approach, instead of thinking it as being part of operational maintenance.
In the cloud, when you deploy services, it gives you an edge to plan your network and security solutions from scratch.
Sharding and Segmenting
You have to ensure that you have properly separated concerns regarding your components. For instance, while working with an RDBMS, a common question is that where should the developer place the DB? According to a conventional approach, the DB server has to a large metallic structure with 16TB RAM and a 64-CPU box.
However, a large and singular DB server for hosting is significantly less powerful in comparison to multiple small DB servers where each of them hosts one schema. This means that if you have a 16 CPU, 16 GB server, then you are better off with 2 CPU, 2GB PostgreSQL servers to achieve greater performance. Similarly, you also have the choice to vertically scale all your instances by adding one schema for each server. In this way, you can have additional RAM, CPUs, and can also perform migration for better storage to use that schema.
This recommendation is equally effective for in-house IT teams. For instance, if all the organization’s department wants to use a portal—let’s say it is built on Drupal—then all departments have to manage documents themselves. Therefore, the use of a stand-alone server is an effective option. All your instances can be maintained with a similar strategy; they will be connected to a primary authentication server while scaling will be performed independently.
Choosing Enterprise Integration Patterns
While designing cloud applications, choosing the right design patterns is necessary. Enterprise integration patterns are a good fit for service-oriented architectures. You can use enterprise integration patterns which have gained relevance for enterprise-level systems. It helps to scale cloud systems on demand while incorporating an extensive list of third-party tools.
The use of development which is based on patterns helps developers and architects to code applications which are convenient to connect, describe, and maintain through utilizing recurrent elements.
In cloud systems, patterns are particularly used for routing messages. Sometimes in service-oriented architectures, a common pattern known as message translator is required where the adoption of shared best practices is effective.
Similarly, there are options like Apache Camel which developers use to get their hands on the enterprise integration framework. It allows them to avoid writing glue code. Instead, they can focus on coding business logic, thanks to the reusable integration patterns of Camel.
At times, a strong wave of traffic comes at once where systems are simply struggling to manage the workload. If a service is non-operational in these times, then it can be quite tricky to handle a large number of messages which must be processed. These are times when the inbound traffic is more than the limits of the system and it is not possible to create a response for all requests.
You may think about the shutdown as a solution but there are better options. If you can enforce QoS (quality of service) to produce and consume your messages, it is possible to achieve diminished availability rather than going completely unavailable.
To stop services from getting overloaded, you can decrease the message number which is being managed; specify a time-to-live for them. By doing this, messages which are older and not relevant can expire and thus discard after a time limit. You can also try restricting the message number which is interpreted simultaneously through the use of concurrent message consumption; restrict each service to handle no more than 10 messages at a single time.
For scalable cloud applications, the maintenance of a state is always tough. Persistence is another name for maintenance of state. Persistence is to store data in a location that is central, due to which it is always hard to scale in such instances. Instead of using multiple transactional or stateful endpoints for your cloud application, you can ensure that your application possesses a RESTful capability; however, make sure that it is not restricted by HTTP.
If you must use state and you cannot ignore state for your cloud applications, then you can govern your state through the use of the above-mentioned enterprise integration patterns. For instance, read about the claim check pattern.