Resilient Systems: Lessons for Startup Engineers
Master Software Reliability Engineering for startups. Learn to build resilient systems with observability, incident management, scaling, and best practices
Every engineer should know how to build resilient systems. I learned this In the several fast-paced startup environments I worked at, where rapid iterations, shifting priorities, and limited resources are the day-to-day norm.
In startups, Growth and learning opportunities are huge, but this comes at the cost of having to wear multiple hats. Launching new features and growing the product are essential, but what determines the success or failure of a feature is system resilience. Without it, features will be a customer’s pain point rather than an added value. This can cost users, reputation, and even cripple the business.
In this article, We will explore what every engineer needs to know about Software Reliability Engineering (SRE).
Resilience Starts with the Engineer
Resilience is the ability of a system to recover from failure, and it’s a responsibility shared by every engineer, no matter their role or company size. Every decision, from design to deployment, impacts system reliability. Engineers must build systems that can handle failures gracefully.
Imagine facing a sudden traffic surge due to a marketing campaign. A third-party API integration begins to timeout, causing some functionality to fail. This leads to wasted marketing efforts, a poor user experience, and I am pretty sure it will cause an increase in bounce rates and a decrease in retention for first time customers.
If caching or a backup integration were implemented, we could have avoided these issues. This highlights the importance of designing for failure and how it ensures system resilience in the face of unexpected challenges.With resilience in mind, the next step is ensuring we have full visibility into the health of our systems.
Observability is all you need
Having comprehensive visibility into your system’s health is critical for early issue detection and prevention. Without proper monitoring, it’s easy to miss performance problems that can lead to downtime, and lost revenue. The sooner you can identify issues, the faster you can handle them before they escalate into bigger failures that affect the business.
In my experience, focusing on a few core metrics like response times, error rates, and uptime provides a clear, actionable view of system performance. By measuring these metrics, you get the visibility needed to understand how your system is performing and where to focus your attention.
Tools for Observability:
Log Management and Analysis OpenSearch and ELK Stack (Elasticsearch, Logstash, Kibana) help track and analyze system events, enabling deep insights into system behavior.
Performance Monitoring: Datadog, New Relic, and Prometheus provide comprehensive performance monitoring, tracking infrastructure health, application performance, and user interactions.
Visualization and Dashboards: Grafana offers real-time dashboards for visualizing system health, often used with Prometheus.
Edge and Deployment Monitoring:Cloudflare ensures optimal performance during high traffic, and Argo offers real-time visibility into deployment pipelines.
Incident Management and Alerting: PagerDuty provides real-time alerts and escalations, helping teams act swiftly during incidents.
These tools offers you the end-to-end visibility needed to have a faster issue resolution and a more reliable system. But we can’t prevent incidents, eventually one will catch us off guard.
Prepare to crash
Incidents will happen, it is just a matter of when, therefore incident management is important for maintaining system reliability.
One way we can prepare is by setting up a runbook in advance. A runbook is a guide that includes common issues, resolution steps, escalation procedures, and how to go back to normal operations.It helps ensure consistency, decreases mean time to recovery, and enables teams to handle incidents effectively and minimize downtime.
One other we can use to prepare is conducting regular “fire drills,” inspired by Netflix’s Chaos Engineering, where issues are introduced as a test to identify gaps and improve response capabilities.
Scaling Early and Often
Scaling should be considered from the start. Expecting growth, and peak traffic helps you build systems that scale as demands increase.
Stress-test your systems to uncover performance bottlenecks before real traffic hits, ensuring you optimize ahead of time. Design for resilience by focusing on core features and providing fallback options to minimize user impact during failures.
Lastly, be effective by avoiding overscaling and make sure to match resources to actual demand.
Building Resilience One Engineer at a Time
Every engineer has a role in making the system resilient. By preparing for failure, monitoring the system, handling incidents effectively, and learning from mistakes, we can ensure long-term growth and reliability.