High availability is a key requirement for many systems, especially those that handle critical or time-sensitive tasks. It means that your system can withstand failures and continue to operate with minimal downtime or data loss. But how do you design a system that achieves high availability? Here are some general principles and strategies that you can apply to your system design.
The first step is to identify the possible failure scenarios that your system might face, such as hardware failures, network failures, software bugs, malicious attacks, or natural disasters. You should also estimate the probability and impact of each scenario, and prioritize the ones that pose the most risk to your system. For example, you might consider how often a server might crash, how long it would take to recover, and how much data or revenue you would lose in the process.
To have highly available system you may need to setup multiple instances of your application. And adopt dynamic autoscaling to support sudden traffic or load so that your existing infra is not overwhelmed and become unavailable.
I fully agree with first step. Additionally you should have single pane monitoring across all systems with detailed views of each device, easily track down the source of performance issues and preempt future service disruptions. Maybe implement and use AI to do real time analysis which can notify you before problem occur.
One of the most common ways to achieve high availability is to use redundancy and replication. Redundancy means having multiple components or resources that can perform the same function, so that if one fails, another can take over. Replication means having multiple copies of the same data or state, so that if one is corrupted or lost, another can be used. For example, you can have multiple servers in different regions that can handle requests, and multiple databases that store the same data.
Another way to achieve high availability is to implement failover and load balancing mechanisms. Failover means switching to a backup component or resource when the primary one fails, while load balancing means distributing the workload among multiple components or resources to optimize performance and availability. For example, you can use a load balancer to route requests to the most available server, and use a heartbeat mechanism to detect failures and trigger failover.
The 3-site replication with a HyperSwap configuration solution consists of three independent geographically dispersed systems. Of this, two systems would have a HyperSwap configured within themselves. - Regulatory compliance, it maintains three copies of production data. - High availability during maintenance, it ensures the availability of two copies of data during site maintenance - System load balancing, it distributes the replication source between two near sites.
Scalability and elasticity are also important for high availability, as they allow your system to handle changes in demand and capacity. Scalability means that your system can handle more load by adding more resources, while elasticity means that your system can adjust the resources dynamically based on the load. For example, you can use horizontal scaling to add more servers or databases when the load increases, and use vertical scaling to increase the size or performance of each server or database when needed.
Fault-tolerant and resilient architectures are those that can tolerate failures and recover quickly, without compromising the functionality or quality of the system. There are different types of fault-tolerant and resilient architectures, such as microservices, serverless, or event-driven architectures, that have different advantages and trade-offs. For example, microservices are small and independent units of functionality that can be deployed and scaled independently, while serverless are functions that run on demand and only pay for the resources used.
Transitioning from a monolithic system to microservices saved our system from failing badly .. Glitches occurred, but our core system remained intact, enabling us to scale seamlessly and meet customer needs. API Gateway: Directs traffic, masks failures, and can even provide fallback responses when a service is down. Service Discovery: Services easily find each other, even as they are moved or scaled, keeping communication smooth. Circuit Breaker: Cuts off struggling services to prevent cascading failures and give them a chance to recover. Monitoring: Detailed metrics on each service let you spot issues early, often preventing them from becoming major outages.
The last step is to test and monitor your system regularly, to ensure that it meets the high availability requirements and to identify and fix any issues that might arise. You should use different types of testing, such as unit testing, integration testing, performance testing, or chaos testing, to verify the functionality, reliability, and resilience of your system. You should also use different types of monitoring, such as availability monitoring, performance monitoring, or error monitoring, to measure and track the health and performance of your system.
Monitoring is the most ignored yet one of the most important aspects of any system. With monitoring you will come to know the real runtime issues related to your application which you can handle in time to avoid complete failure.