There are various factors which cause downtime. 1. Increased loads (Genuine) 2. Time consuming services which are blocking the subsequent requests 3. Intentional DDos attacks from since service/IP 4. Single service/IP continuously hitting the service due to a Bug How to address 1. Provision the scaled Infra if Auto scaling is not place 2. Avoid sequential processing of computational tasks unless they need real time transactional capability 3. Apply forking/workers for utilizing the server capacity efficiently 4. Apply rate limits for avoiding DDos attacks

It is highly likely that downtime occurs due to unforeseen increase in the traffic load. But there are times when a very small part of traffic can lead to disruptions because of long running processes. To solve these situations it is best to deploy the web solution with following checkpoints - Ensure a load balancer is present between service consumers and providers - Offload longer running processes into their own dedicated threads - Check if a task is repetitive and can be done via queues, and then use the ideal services for it - Use an intermediate cache server for functions and data. - Try optimising Database connections with a pool - Database setup with multiple read write replicas is a bonus for performance and reducing downtime

I just try to have code that we can change. This means that whenever a data flow is problematic we can dive in and fix it quickly. If you can’t write code to fix problems in a day then you’ve got bigger problems. The more vendor stuff you have of course, the harder it is. But it’s still possible. Ultimately this is more about having a capable and trusting team than any one specific architecture thing.

Following things will help - Use load balancers to distribute traffic and ensure availability. - Use alerts systems like go alert by setting up monitering like grafana. - Have disaster recovery plan. - Auto Scaling. - Use CDN for loading static content to reduce load on servers. - Have Unit and Automation testing in place. - Perform load testing and stress testing to handle unexpected loads. Above stratigies will reduce the risk of downtime and improve your application's resilience.

Downtime occurs due to external threat or internal system failures. To avoid we can take below steps: • Better design (considering stability, resilience, security, self-healing systems, performance, etc) and development. • end to end testing (Load, performance, system, integration, db, vulnerability, etc) • secured infra (WAF, DDoS, rate limit etc) • Continuous monitoring with threshold notification. • Regular audit on systems and infra. • RCA with action in case of downtime. In our AI era there are AI models providing better downtime safeguarding systems with predictive maintenance, Anomaly detection and AI-powered monitoring (need to explore this area)

Depending on the type of integration, the impact it would have on the app, and length of the downtime, things that might work: - Update the application to work at a limited capacity (some level of degradation). That way, users with "jobs to be done" that don't need the integration still succeed. - Having a "fallback" service where we route traffic while the integration is down. - Add a broker (queue / stream / bus) to hold traffic to the integration while it's down. Once the integration is back online, processing continues, state converges, and everyone is happy again. - Serving stale content while the integration is down. - For planned downtime, something as simple as a notification/announcement and a static page can do the trick.

We can consider multiple options. However, usually it is advisable to choose correct one based on your problem. Few below are some solutions. 1. Multiple servers(nodes), load balancing, rate limiting, stop calling service which are failing. 2.failover mechanisms, health monitoring. 3. Check if any DOS attack. 4. Performance optimisation of application, optimise services which consume more cpu and mem causing unavailability. 5. Security and performance test of application in staging environment with prod size data. 6. Regular data backups, so if required can spin new environment quickly.

To keep our web app running smoothly, we add extra servers (redundancy) so if one fails, another can take over. Circuit breakers stop failing services temporarily, and retry logic lets the app try again if a request fails. Monitoring tools show us our app’s health, and alerts notify us of any issues. With graceful degradation, users can still do basic tasks if a feature fails. Feature toggles let us turn off problematic parts easily, while regular backups and a disaster recovery plan help us recover quickly. Load testing shows how much traffic our app can handle, and chaos engineering prepares us for unexpected problems, ensuring our app stays reliable.

To keep your web apps running smoothly and avoid downtime, focus on these key strategies: - Real-time Monitoring & Predictive Analysis: Use monitoring and log analysis to catch early warning signs and address issues proactively. - Load Balancing & Auto-scaling: Scale resources and balance traffic to handle peak loads efficiently. - Retry Logic: Implement retry mechanisms with backoff strategies for handling temporary errors. - Circuit Breakers: Isolate failing services to prevent cascading failures. - Caching Management: Reduce database strain with caching, while avoiding stale data. - Comprehensive Testing: Regular load and resilience testing ensures your app’s reliability.