Tech organizations face many challenges: system failures, service downtimes, security attacks, and outdated technology infrastructure are prime examples. This article will explore these issues and look at how DevOps consulting, proper setup, and performance optimization can mitigate their effects.

Infrastructure

Robust architecture design

Your applications’ performance profiles should be the foundation of your system architecture design strategy. From there, build it taking account of the following:

• Obtain the maximum amount of information on your current workload as possible.
• Decide if your systems can deal with the heavy production demands while meeting SLAs
• The system design must follow best practices for reliability and fault tolerance.
• If using a cloud service, ensure the range of services meets your operational requirements in every respect.
• Automate and regularly test failure management processes to ensure their effectiveness and reliability.

Latest technology stack

In this digital age, staying ahead of the technology curve is crucial. To keep up with the times, it is essential to embrace new advancements as soon as they are available to enhance your technological capabilities.

Automated processes

Automation accelerates development, improves code quality, simplifies infrastructure management, and optimizes business operations.

Typically, besides an IT infrastructure audit, this type of automation covers the following:

• DevOps Infrastructure as Code
• Autoscaling
• Automated monitoring
• DevOps CI/CD (Continuous Integration and Continuous Delivery)

Security hardening

Your company’s security effectiveness is tied to the measures used to achieve it. To keep your data, systems, and assets secure, your strategy must protect against potential and actual attacks. This should consist of identity and access management, infrastructure protection, detective controls, and data protection.

Application

Code quality

Low-quality code leads to issues resulting in rollbacks and production problems. To measure the quality of released software, DevOps or DevOps as a service utilizes the Change Failure Rate metric. This DORA metric measures the code’s resilience to malfunctions. It captures the percentage of code changes that result in rollbacks or failures, with a lower average indicating fewer code faults. This allows a DevOps company, by using this metric, to reduce bugs and improve code quality.

Readiness for the cloud

Since most software is now delivered as a service, it must adhere to the best cloud architecture design standards. Above all, ensure that it:

• is compatible with modern cloud platforms, and
• can be easily containerized.

To ensure your application is cloud ready, evaluate it against our 12-Factor App principles.

Delivery of code and deployment

Different software deployment strategies are often used by different teams, services, and businesses. To increase deployment reliability and minimize potential impacts, it’s important to establish best practices for software delivery. To achieve this, consider implementing the following:

• CI/CD: Software development methodologies involve systematic and automated processes for building, testing, and releasing code with new patches submitted to the codebase.
• Reduced iteration cycles: Working with smaller changes will make your code more readable and easier to test and troubleshoot.
• Deployment approach: Select the method that aligns best with your application’s needs. Combine strategies based on the specific requirements of the service, its performance profile, and potential business impact.
• Automated rollbacks: Automating all process steps helps minimize the impact of scenarios like failed deployments by allowing for rollbacks. The result? A smoother release process.

Observability

Awareness of the signals systems emit can aid in preventing incidents or reducing their impact.

Metrics

The two key metrics types to monitor are:

• Infrastructure-specific: pertaining to the system’s operational level, these can include detailed information like database utilization, server resource usage, deployment failure rate, etc.
• Application-specific: these offer insights about a specific service. They help evaluate the service’s business logic, such as application availability (SLA), query and database time, error rate, and more.

Tracing

Collects data from inside services, combining it with known system information. The data it gives helps developers identify slow calls, prolonged operations, service failures, and their locations.

Log monitoring

Records events such as web service access logs and error states. This differs from monitoring metrics which are restricted to recording performance data at predetermined intervals.

Final thoughts

This article discussed reasons infrastructure, applications, or deployment often fail. It also presented some proven techniques for improving performance and reliability. We offer DevOps consulting services that will help you assess the readiness of your systems for production.

DevOps development company https://shalb.com/ provides DevOps as managed service, SRE, and System Architecture Services with 24/7 support for global software teams. We utilize Kubernetes management, Serverless, Terraform, IaC, and cloud cost optimization to design dependable systems.