5 key points of data-driven application infrastructure

For years, on-premise application server deployment was the only reliable choice for many enterprises. It was the perfect way to manage resources efficiently, guarantee the safety of personal data, and provide IT teams with enough freedom to implement any customized solution.

Today, cloud services have become the tool of choice for building any data-driven application with the growing demand for uninterrupted availability, on-demand scalability, and much larger processing and storage resources. As a result, many cloud providers offer a wide variety of plug-n-play cloud services: from SQL servers and file storage buckets to containerized environments and monitoring tools—the list goes on.

But there is more to choosing a perfect cloud provider than just liking the technology they offer. Significant differences can be found in the total cost, compliance with industry standards (like storing data within the country's borders), seamless connectivity with your existing infrastructure, and attractive B2B offer available to you.

An IT team can't create a secure data environment without following the advice of major, trusted security organizations. 

OWASP, the most widely recognized project, shares an annual list of top security issues and defines the security risks most known to the industry. Covering all the issues that made their way to the top-10 list will make your application significantly more robust compared to an average player on the market. However, keep in mind that any top-level security threats hold dozens of potential vulnerabilities that must be covered before moving down the list. 

So, there is a lot of work before you address the big issue—industry standards, which will also take effort and require inspections before your application can make it to the market. 

What's more, target security standards should be set and examined before the work on the application begins. Modern security standards cover all the stages of application development and heavily regulate aspects of application logic itself—like the use of cryptographic algorithms and internal access rights. Some measures on the network layer (like firewalls) can be integrated easily with an existing application. But more complex security concepts like an intrusion detection system (IDS) should be part of the application design from day one.

Large volumes of data that have to be stored securely and accessed fast require much more than a simple solution. Just like an application can't run on a single local web server instance, it can't store all of its data within a single database. Instead, you will need to design a datastore system that will include multiple database engines and resource storage systems. 

Here are some points to consider while doing so:

• The importance of data. This factor will guide the choice of proprietary encrypted storage, trusted relational databases with regular backups and replication mechanisms, or lightning-fast cache storage that removes data as soon as it becomes outdated.

• Access speed requirements. You can opt for high-speed NoSQL databases that can handle large amounts of traffic, serving relatively simply-structured data. Alternatively, you can compromise on speed in favor of analytical power over complicated data structures. 

• Data type. With all advancements in database technology, some things like images or executable files are better stored as-is on file servers. Here, you can consider solutions like a content delivery network (CDN) that will duplicate your content to many geographically distributed servers to ensure its flawless delivery to users.

Infrastructure-as-code helps developers store and modify infrastructure as part of a codebase while using familiar programming languages and tools. It eliminates the need for a big DevOps team and allows programmers to make small feature releases constantly. It also enables easy versioning of the infrastructure so that any breaking changes can be rolled back, quickly restoring the service availability.

Containers allow developers to create expandable enclosed environments in great numbers automatically. Moreover, container orchestrating tools can automatically create or destroy active application containers, balancing current user traffic with infrastructure costs. Even if your application is based on serverless microservices architecture, containers can still be used to store plug-n-play test environments or enclose used third-party tools.

The use of modern development technologies and cloud providers makes the infrastructure of data-driven apps more agile and easier to scale and reuse seamlessly. Keeping the best practices for infrastructure reliability and scalability in mind while building it will make the development process transparent and fast. Compromising on reliability will ultimately remove the ability to reuse some infrastructure building blocks. However, if you are unsure that the datastore can handle planned loads, adding more processing resources behind it might not solve the problem.

By not considering scalability from day one, you will see your application becoming unreliable — to the point where the weakest infrastructure link breaks, making the whole system inoperable.

If these points are not thought through before the start of the project, it might result in a total do-over with the use of different tools and significant increases in budgets.

In a broader sense, this point refers to proactively collecting, visualizing, and alerting on data across all of your systems, including your app infrastructure. 

As for the monitoring challenges, there are a few common culprits: 

• The infrastructure ecosystem where the application resides is too big to monitor.

• Your infrastructure monitoring tool lacks advanced reporting capabilities. 

• You're using too many "special case" monitoring tools. 

• There is a lack of communication between teams. 

Poorly monitored infrastructure leads to a series of problems, including an inability to find and fix outages quickly, support engineering, DevOps, and IT teams that work with or rely on the application infrastructure or provide a consistent user experience. 

To prevent this sort of issue, you need to establish the metrics that will tell how well an application performs the work you ask it to do. Also, you should gather sufficient information about the resources the application depends on and how well they manage the workload.

The main signals for applications that serve clients are:

• Latency (request-to-response time)

• Traffic (requests per second)

• Errors (failures to process client requests or access resources)

• Saturation (resources used)

Ideally, you want your monitoring and infrastructure management tools to inform you about performance issues and offer insight into their cascading effects on business goals.

The costs of gathering, storing, accessing, sorting, and analyzing data can pile up. If these costs outweigh the predicted benefits or available resources, consider:

• Eliminating non-essential data collection because the objectives before the project began and after the project is implemented may change

• Reducing the frequency of data collection while also making sure it is sufficiently robust

• Using available data

• Switching to cheaper data collection and processing options.