How do you ensure reliability and resilience of your systems under high load and stress?

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Reliability and resilience are crucial aspects of any scalable system, especially when it faces high load and stress. How can you design, test, and monitor your systems to ensure they can handle unexpected spikes, failures, and disruptions without compromising performance or availability? In this article, you will learn some practical tips and best practices to achieve reliability and resilience in your systems.

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1 Define your reliability goals

Before you start building or improving your system, you need to define your reliability goals and metrics. Reliability goals are the expectations and requirements of your users and stakeholders for how your system should perform and behave under normal and abnormal conditions. Reliability metrics are the quantitative measures that reflect how well your system meets those goals. For example, you might use metrics such as availability, latency, throughput, error rate, or service level indicators (SLIs) to track your reliability. You should also define service level objectives (SLOs) and service level agreements (SLAs) to specify the acceptable thresholds and consequences for your reliability metrics.

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Miguel Villamil

CEO de Aceleradora A1M I ?? Si tienes una agencia, te ayudo a superar los 83.333€ al mes con +35% rentabilidad gracias a liberarte de las tareas del día a día I ?? Escala tu agencia trabajando menos horas
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Al definir los objetivos de confiabilidad, es esencial alinearlos con las expectativas del usuario y las necesidades del negocio, asegurando que cada métrica tenga un impacto directo en la satisfacción del cliente. Además, establecer SLOs realistas y revisarlos periódicamente permite adaptarse a cambios en la demanda y mantener la resiliencia.

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Jack B.

MS DCSE Candidate @ SMU Lyle | Ex-LinkedIn | Software Engineer | Novelist
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When it comes to defining reliability goals, it's essential to remember that they shouldn't be set in a vacuum. Instead, adopt a user-centric perspective by getting to know your users and partners—understanding their expectations and what they can handle is key. To strike the perfect balance, start by chatting with your users and partners to grasp their reliability, availability, and latency tolerance. This knowledge will help you find the sweet spot in setting thresholds, ensuring you don't make overly costly engineering decisions or delay time to market, while still meeting user needs.

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2 Design for scalability and fault tolerance

Scalability and fault tolerance are two key aspects of reliability and resilience. To design a scalable system, you should use horizontal scaling instead of vertical scaling, distribute traffic and workload using load balancing and routing techniques, break down your system into microservices or serverless architectures, use caching and queueing mechanisms, and employ asynchronous and event-driven patterns. To design a fault-tolerant system, you should use redundancy and replication techniques, failover and backup mechanisms, circuit breaker and retry patterns, health checks and heartbeat signals, as well as logging and tracing tools.

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Moses B. Landon

Senior Executive Healthcare, Operations, Client, Revenue + Strategy | Scaling organizations to exceed revenue and operational KPIs while serving people and communities.
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Designing for scalability and fault tolerance is an ongoing process. Regularly review and refine your architecture to adapt to changing requirements and evolving technologies. Break down your system into smaller, independent functions or microservices. Each function should have a specific responsibility and operate independently. Decoupling allows for easier scaling and fault isolation. Failures in one function won’t affect the entire system. Detect anomalies, bottlenecks, and failures early to take corrective actions. Conduct controlled experiments (chaos testing) to simulate failures and observe system behavior. This helps uncover vulnerabilities and improve fault tolerance.

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Miguel Villamil

CEO de Aceleradora A1M I ?? Si tienes una agencia, te ayudo a superar los 83.333€ al mes con +35% rentabilidad gracias a liberarte de las tareas del día a día I ?? Escala tu agencia trabajando menos horas
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Al dise?ar para la escalabilidad y la tolerancia a fallos, es fundamental implementar pruebas de "chaos engineering" para identificar puntos débiles y validar la efectividad de los mecanismos de recuperación. Integrar herramientas de observabilidad avanzada permite una detección proactiva de problemas y optimiza la respuesta ante fallos. Además, aplicar un enfoque de "fallback" garantiza continuidad de servicio en situaciones críticas.

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Ye W.

Head of Technology at APC Postal Logistics
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For most sophisticated data resiliency requirements, even dispersed geography itself with single a public cloud vendor is not a rigorous enough option. It's often recommended to diversify to have multi-cloud presences on the internet to ensure maximum resiliency. The reason is that, having an instance of infrastructure deployed at a completely isolated data center from a different public cloud vendor would drastically reduce the chance of downtime because two different public cloud vendors rarely experience downtime at the same time, while two different regions of a single public cloud vendor is at a much higher likelihood (even though it's still rare).

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3 Test your system under load and stress

Once you have designed your system for scalability and fault tolerance, you need to test it under load and stress to verify its reliability and resilience. Load testing and stress testing are two types of performance testing that simulate realistic or extreme scenarios of user demand, traffic volume, or resource consumption on your system, and measure its response and behavior. Load testing aims to determine the maximum capacity and throughput of your system, and to identify any performance bottlenecks or issues. Stress testing aims to determine the breaking point and recovery time of your system, and to identify any reliability or resilience gaps or risks. You should use load testing and stress testing tools and frameworks, such as JMeter, Gatling, Locust, or Artillery, to generate and execute your test cases, and to collect and analyze your test results.

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Nitin Mahajan
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When it comes to testing under load and stress, consider adding chaos engineering to test system design for reliability before real failures happen. Mimic real-world events like server crashes, hard drives malfunction, bad network connections, etc. Validate if the operational solutions, fallbacks, and resilience systems kick in to meet desired SLOs & SLAs.

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Miguel Villamil

CEO de Aceleradora A1M I ?? Si tienes una agencia, te ayudo a superar los 83.333€ al mes con +35% rentabilidad gracias a liberarte de las tareas del día a día I ?? Escala tu agencia trabajando menos horas
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Es esencial complementar las pruebas de carga y estrés con escenarios de prueba de "spike testing" para simular aumentos repentinos en el tráfico y observar cómo el sistema maneja picos inesperados. Utilizar datos de producción o patrones de uso reales en estas pruebas puede ofrecer una visión más precisa del comportamiento del sistema. Además, automatizar las pruebas periódicas garantiza que el sistema mantenga su confiabilidad a medida que evoluciona.

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4 Monitor your system in production

After testing your system under load and stress, you need to monitor it in production to ensure its reliability and resilience. Monitoring involves collecting, measuring, and visualizing data and metrics that reflect the health and performance of your system, as well as alerting the relevant stakeholders or teams when any anomalies or issues occur. This process helps you validate your reliability goals and metrics, detect and diagnose errors, identify and optimize performance or resource inefficiencies, understand user behavior, and anticipate demand patterns. To do this, use monitoring tools such as Prometheus, Grafana, Datadog, or New Relic to collect and visualize your data and metrics, and set up alerting rules and policies.

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Miguel Villamil

CEO de Aceleradora A1M I ?? Si tienes una agencia, te ayudo a superar los 83.333€ al mes con +35% rentabilidad gracias a liberarte de las tareas del día a día I ?? Escala tu agencia trabajando menos horas
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Una supervisión eficaz en producción debe incluir no solo alertas en tiempo real, sino también capacidades de análisis predictivo para anticipar problemas antes de que ocurran. La correlación de métricas de rendimiento con los logs de aplicaciones permite un diagnóstico más rápido y preciso. Además, implementar prácticas de observabilidad holística, como "tracing" distribuido, mejora la comprensión del comportamiento del sistema bajo cargas variables.

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5 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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Miguel Villamil

CEO de Aceleradora A1M I ?? Si tienes una agencia, te ayudo a superar los 83.333€ al mes con +35% rentabilidad gracias a liberarte de las tareas del día a día I ?? Escala tu agencia trabajando menos horas
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Un enfoque clave para mejorar la resiliencia es integrar simulaciones de "chaos engineering" en entornos de producción controlados, lo que permite identificar fallos antes de que ocurran en condiciones reales. También es útil fomentar una cultura de aprendizaje continuo y retrospectivas regulares para adaptar rápidamente las estrategias. Además, la colaboración interdepartamental es esencial para alinear objetivos y mejorar la resiliencia a nivel organizacional.

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How do you ensure reliability and resilience of your systems under high load and stress?

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1 Define your reliability goals

2 Design for scalability and fault tolerance

3 Test your system under load and stress

4 Monitor your system in production

5 Here’s what else to consider

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