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Building Resilient Applications

Building Resilient Applications

If you have a product today, you need an application to grow your business. Either a web app, mobile app, or desktop app. Applications are the backbone of many businesses, driving interactions, transactions, and information access. However, even the most advanced applications can experience disruptions, making application resilience essential. This article will cover the best strategies for building resilient applications and explore how to fish out and address potential weak points.

As mentioned earlier, application resilience is the ability of software to sustain functionality and minimize the impact of downtime when disruptions occur. A resilient application can withstand hardware crashes, disruption, bugs, and cyberattacks and recover quickly with minimal impact. It is a very important consideration in building modern applications. There are several recovery techniques to get an application back up and running after experiencing downtime.

Some key concepts facilitate an application’s ability to minimize downtime; here are a few of them:

Fault Tolerance is the ability of a system to function during failures or malfunctions. Strategies like redundancy and failover procedures ensure that other system components can take up the load to reduce downtime.

  • High Availability (HA): High availability aims to reduce downtime using geographically dispersed data centers, load balancing, and clustering. High-availability systems work by spreading workloads and providing redundancy across several servers to continue functioning even when individual components fail.
  • Disaster Recovery (DR): While Fault Tolerance and High Availability focus on unexpected disruption, Disaster recovery plans are essential for more consequential events like cyberattacks. Disaster Recovery plans include data backups, system restoration procedures, and failover to secondary systems to ensure a prompt return to regular operations.

The Unpredictable Nature of Downtime

Although hardware malfunctions are not very common in recent years, they pose a threat and may result in unexpected failures, leading to application downtime. An application could experience disruption from different causes. Besides the hardware problems, an application can also experience downtime due to network congestion, outages, or security breaches, which can prevent users from accessing the application or disrupt communication between application components.

Strategies for Building Resilient Applications

Building resilient applications requires a layered approach. Some strategies ensure the application will continue to operate with minimal effect, even if a component falters. Here are some of them:

Designing for Redundancy

Redundancy is having backups for the essential components of your application, such as extra servers, network connections, etc. When one component fails, the other components can keep the application running.

Implementing Redundancy

There are several ways to implement redundancy, one of which is Load balancing, which distributes incoming requests across multiple servers. This prevents any single server from becoming overloaded and potentially crashing. If one server experiences an issue, the others can pick up the slack, ensuring users don’t experience any disruption. Another technique is database replication. Imagine having a mirror image of your production database. This replica database is constantly updated with the original database, ensuring minimal data loss. If the original database encounters an outage, the replica can take over seamlessly, minimizing downtime.

Kicking in When Needed

Redundancy gives us the backup plan, but we also need to be able to switch over those backups automatically. Increased availability: Automated failover systems continuously monitor the health of essential components and can react much sooner to a component failure. If they detect that any of their components is slower, the system fails over immediately to other hardware. This leads to less downtime and makes for a seamless transition experience on the user’s end. As perfect as automated failover is, having defined operational procedures for manual intervention is equally wise. These processes serve as a blueprint for directing the discovery and rectification of faults, including manually reverting to backup systems if necessary.

Monitoring and Alerting

Redundancy is one thing, but alertness is at all times. The safety net that redundancy and failover are being because the resilience fails to maintain its secret spring. This is where monitoring and alerting help. Instead of these outages, you should proactively monitor your application’s and infrastructure’s health to catch a suboptimal performance before it transforms into an outage. This involves monitoring several key metrics, such as server health and resource utilization (CPU and memory), database performance, and application error rates.

Effective monitoring involves different tools and technologies. Prometheus is an excellent open-source platform that does wonders when measuring and storing metrics data. Grafana comes in next, visualizing this data and offering informative dashboards to track the health of your application live.

Regular Backups and Data Integrity

Even the best-laid plans can be derailed by unexpected events. Regular Backups: Like a safety deposit box for all things digital, backups give you that extra security layer in case everything goes wrong. There are many backup options to do this. Full backups represent a complete snapshot of your data, including the full dataset. This could be the full file (full backup) or just changes since a previous last time copy of it was made. It’s incremental. This minimizes storage but demands both the incremental and most recent full for recovery. The frequency of backups depends on your data’s criticality and tolerance for data loss. For highly sensitive data, daily backups might be necessary. Less critical data might be backed up weekly or even monthly.

Checking Backups

A backup is worthless if it can’t be restored. Repeated verification of your backup data and testing how to restore it is essential. This allows you to test your restoration methods in a disaster recovery scenario and avoid potential issues before they become crises.

Automated Testing and Continuous Integration/Continuous Deployment (CI/CD)

We can update the code periodically because it is natural in software development, but this force sometimes causes bugs that are impossible to see and identify until we go into production. We can hedge this risk using automated testing and CI/CD pipelines. These tests are essentially a set of automated quality checks on your code, and this can be broadly called Automated Testing. Unit tests, which make sure components of your application are correct at a singular function level Integration tests - these ensure how part A interacts with Part B and find out if there could be an issue where two parts are connecting End-to-End testing mimics user interactions in our app to verify that everything is working as it should. Essentially, by adding these levels of testing to your development process, you can catch bugs and prevent them from hitting production issues. This proactive strategy bakes quality into your application from the beginning.

CI/CD helps by automating a whole bunch of tasks (from submitting code to deploying) that would otherwise need intervention and manual input from human beings. It is just the interconnected steps comprised of these pipelines. When new functionality is introduced, automated code building and testing tests it against existing services to ensure that changes haven’t interfered with previous releases. The version control system enables code changes and continuous integration and combines them to not require manual intervention for repeated updates. According to your configuration, continuous deployment might also deploy new integrated code into a testing/production environment. This means we make quicker delivery possible and minimize regression probability in every manual deployment.

Design for Failure

The concept of “design for failure” might seem counterintuitive. However, it has proven an effective strategy for building resilient applications. It assumes that failure can and will occur and works to build your application around it with as little downtime or data loss as possible. Chaos engineering involves experimenting on a distributed system exposed to extreme conditions to build confidence about its capability. This allows you to see how your app responds to failure so you can discover its weaknesses and harden your systems against them preemptively. This proactive approach helps you prepare for and mitigate issues long before they emerge in a production environment.

Another design-to-failure mechanism is the use of resilient architecture patterns. With these patterns, you get a pre-codified methodology to deal with disruptions, allowing you to incorporate a layer of protection at the architectural stage. The circuit breaker, for instance, stops retrying a service endlessly in response to repeated failures. Once the connection has passed a certain number of failures, it “breaks,” and no further connections are attempted for an interval. After the reset timeout, we can partially open the circuit to a given number of retries to test if it is safe for traffic. It also protects the dependent services from being overloaded by a failing service.

Disaster Recovery Planning: Preparing for the Worst

Although proactive measures are vital, a well-defined disaster recovery plan is necessary for responding to major disasters. A disaster recovery plan outlines what your team will do to recover from a major incident resulting in downtime or data loss, restoring normal operations as swiftly as possible. Creating a DR plan requires defining key components: the Recovery Time Objective (RTO), which defines the acceptable downtime after a disaster before critical business processes are restored, and setting the target timeframe for getting your application back online. The Recovery Point Objective (RPO) specifies the acceptable downtime after a disaster before critical business processes are back up and running, serving as your target time to restore application access. These components provide clear guidelines for recovery efforts and help prioritize actions during a crisis.

Case Studies: Resilience in Action

Take a look at some examples where resilient architecture was handy in the real world. We will touch upon some success and horror stories on that note, highlighting what each of them learned in the quest.

Success Stories: When Resilience Pays Off

  • Netflix: A textbook example of resilience, Netflix has adopted chaos engineering with Chaos Monkey. They simulate failures and outages to find the problems before they have a chance to take down their millions of users. Because they are designed to be microservices with bulkheaded isolation to prevent the single-service-failure-brings-down-the-whole-platform syndrome. This approach has been delivered with zero downtime, guaranteeing extremely high availability for millions of users. Amazon: Many folks we talked to wanted Amazon Scale and Availability, as supported by what they called Cloud Resilience. Amazon uses multiple regions and data centers to ensure that whenever one region goes down, the other can continue. Amazon also automates its deployments through CI/CD pipelines to reduce the human error factor and speed up restoration time for issues as a priority.

Lessons Learned: The Cost of Downtime

  • The Great AWS Outage of 2012: In this cautionary story, a cascading series of failures within Amazon’s S3 storage service caused popular web applications across the Internet to fall offline. This incident showed how crucial it is to test infrastructure changes properly and have resilient recovery plans for unexpected events.
  • Equifax Data Breach: Data Breach: His data breach was responsible for millions of customers exposing their sensitive financial information. While the breach was not due to a lack of resilience in the app, it highlights that strong security practices are one element of holistically building reliable and secure systems.

Conclusion

Resilient applications are no longer an option; rather, they are a must-do when building applications. Following the practices outlined in this post, you can create applications that work well and will continue to thrive. Remember, resilience is a journey, not a destination. By continuously monitoring your applications, conducting regular drills, and adapting your approach based on experience, you can improve your application’s ability to handle the unexpected.

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