System failures, the time needed to restore services, security concerns, and an obsolete technology stack are among the most prevalent problems that technology organizations encounter, according to our clients. In this article, we'll examine each of these elements, considering the impact setup and optimization have on them.

IT infrastructure audit

Properly designed architecture

The golden rule when designing system architecture is to start with the performance profiles of your apps.

To formulate an appropriate strategy, your team should focus on the following:

  1. Obtaining the maximum amount of information on your current workload as possible.
  2. Do your systems have the capacity to maintain production workloads and align with SLA?
  3. When designing your systems, adhere to fault-tolerance and reliability best practices.
  4. Confirm that the range of services fully satisfies your operational requirements if using a cloud.
  5. How trustworthy is your system? To ensure that your failure management processes remain effective, automate and test them frequently.
Stack modernity

Nowadays, having cutting-edge technology is essential as things become increasingly digital. Therefore, enhance your technological capabilities by utilizing the latest developments immediately after they become available.

Process automation. Not only does this speed up development, but it also boosts the quality of your code, makes managing the infrastructure easier, and streamlines business operations.

Infrastructure automation typically covers the following:

  1. DevOps Infrastructure as Code (IaC)
  2. DevOpsCI/CD for Continuous Integration and Continuous Delivery (CI/CD)
  3. Autoscaling
  4. Automated monitoring
Security

Your company's security is only as good as the measures used to achieve it. Your strategy should include robust measures for protecting data, systems, and assets against potential threats and actual attacks. Consider factors such as identity and access management, infrastructure protection, detective controls, and data protection.

Application

Quality of code

Poor-quality code is likely to lead to problems that result in rollbacks and production issues. That is why we, as a DevOps development company, employ the Change Failure Rate to gauge the quality of released software. Change Failure Rate is a DORA metric that shows how resilient code is to failures.

The percentage of code changes resulting in rollbacks or production failures is captured by the Change Failure Rate: the lower its average, the fewer faults the code contains.

Cloud readiness

Most software is now provided as a service, so the right cloud architecture design is essential. This primarily pertains to an application's design, namely how well-suited it is for deployment on modern cloud platforms and whether it can be easily containerized. 

We recommend you perform a cloud cost optimization to evaluate your application in accordance with the 12 Factor App principles to ensure it is cloud ready.

Deployments and code delivery

Different teams, businesses, DevOps companies and services use different software deployment strategies. Your deployments will become more dependable and help minimize any potential effects if you lay the groundwork for better software delivery. Therefore, consider putting these procedures into practice:

  1. CI/CD: Software development methodologies are continuous, using automated mechanisms to build, test, and deploy code as part of performance optimization every time a new patch is submitted to a codebase.
  2. Shorter iteration cycles: Your code will be more readable and easier to test and troubleshoot when working with smaller changes.
  3. Deployment strategy: Choose the approach that best suits your application. Mix strategies based on the service-specific requirements, its performance profile, and potential commercial impacts on your business.
  4. Automated rollbacks: Automating all steps means the impact of scenarios such as a failed deployment can be minimized by rollbacks, which in turn will ensure the release process is as smooth as possible.

Observability

Awareness of the signals systems send out can go a long way toward preventing incidents from occurring or minimizing their impact.

Metrics

The following two types of metrics should be monitored:

  1. Infrastructure-specific: these relate to the operational layer of the system, and can include information like server resource usage, database utilization, or fail rate of deployments.
  2. Application-specific: these provide data on a given service. They are used to assess the business logic of the service, such as application availability (SLA), error rate, database, and query time.
Tracing

This tool permits data collection directly from within services and combines that with what is already known about the system. It provides the data programmers need to identify sluggish calls, long-running operations, service malfunctions, and their locations.

Logs

Log monitoring occasionally records occasional and crucial events: web service access logs, error conditions, etc. This contrasts with monitoring metrics that simply record performance data at regular intervals.

Conclusion

This article has outlined the key reasons why your infrastructure, application, or deployment could fail. It suggests some tried-and-tested methods for tuning things for enhanced reliability, security hardening and performance. Why not try our DevOps consulting services real-time infrastructure audit to see how prepared your systems are for production? 

Using this website https://shalb.com/ you can find for your project SRE, container management services, and System Architect Services with round-the-clock support. We use Kubernetes management, Serverless, Terraform, and the Infrastructure as Code methodology to create and maintain reliable cloud native systems.