Hello everyone. Welcome to the Con 42 Site Reliability Engineering 2025 conference. My name is Ravata, and today I'm going to talk about the alert and monitoring and the strategies for identifying and resolving performance bottlenecks. So let's just get started. System failures can have severe real world consequences. Impacting finances, safety, and critical infrastructure in finance. Trading glitches like the 20 20 12 Night capital group trading algorithm failure resulted in a loss of 440,000,045 minutes while banking outages disrupt transactions. Another example is the Amazon Web Services outage in 2021, which caused major losses across multiple businesses while banking outages, disrupt transactions, and customer access. Healthcare, failure in medical devices or hospital regard systems can delay treatments and risk lives. Transportation failures such as aviation software crashes or self-driving car malfunctions led to. Delays accidents and safety concerns. Power grid failures like the 2003 North American blackout affect millions while cyber attacks on infrastructures such as the colonial pipeline attack, disrupt supply chain, and fuel availability. Data breaches. Like the 2017 Equifax hack exposes sensitive information leading to financial fraud and theft. Even defense and system space systems failure can compromise national security affecting military operations and GPS navigations system. Downtime in major tech platforms can hurt businesses and impact global communication. Faulty AI decision making in areas like fraud detection, hiring, and credit approvals can lead to unfair biases and legal challenges. These risks highlight the need for a robust engineering rigorous testing, cybersecurity measures and resilience system designs to prevent the catastrophic failures and ensure reliability in critical services. System failures can severely disrupt business operations by halting critical services, delaying production, and causing financial losses. For example, software outages can prevent employees from accessing key data or applications leading to inefficiency and missed deadlines. In customer facing systems, failures can result in poor user experience, loss sales, and damage reputation. Payment processing issues can hold transactions affecting revenues. Supply chain disruptions due to system errors can delay production, delivery and create inventory shortages. Additionally, data breaches or cybersecurity attacks can compromise sensitive information leading to legal liabilities and loss of customer trust. Ensuring system reliability is crucial for maintaining smooth and continuous business operations. Monitoring is essential for maintaining uptime and system health. By providing realtime insights into system performance, it helps detect issues early, such as slowdowns errors or security breaches before they can even escalate into a major. Problems. With proactive monitoring, teams can quickly address potential failures, minimizing downtime, and reducing the impact on users and operations. It also allows for continuous optimization, ensuring systems run efficiency and securely by tracking key metrics like server load, response times, and error rates. Monitoring helps maintain a stable environment, ensuring consistent C service delivery, and preventing disruptions. Alerting plays a critical role in ensuring rapid issue resolution by notifying team about potential problems as soon as they arise. It provides realtime alerts based on predefined thresholds, enabling immediate action before issues impact users or system performances. By prioritizing alerts according to severity, teams can focus on critical issues first, reducing downtime and minimizing business disruptions. Prompt alerts also ensures that the right team members are informed, enabling faster collaboration, and quicker resolutions in fast paced environment. Effective alerting helps maintain system health, improves response times and ensures continuous service availability. Monitoring is the ongoing process of tracking system health to ensure optimal performance and stability. It involves continuously observing key system metrics, such as server load, response times, and error rates to identify potential issues before they escalate by maintaining constant visibility. Monitoring helps detect anomalies, performance bottlenecks, and security threats early. Allowing teams to take proactive measures. This continuous oversight ensures system remains reliable, efficient, and secure. Minimizing downtime and supply. Supporting smooth business operations monitoring is essential for maintaining a healthy high performance IT environment. Key components of monitoring include data collection, analysis, and visualization. Data collection involves gathering logs. Sorry. Log metrics and events from servers, applications, and infrastructure to capture system behaviors. Analysis is the process of detecting patent trends and potential issues. By examining this data for anomalies or irregularities, visualization helps in interpret system performance through dashboards and reports, providing clear insights into the system health. Together. These components enable proactive management and ensure quick identification and resolution of problems leading to improved uptime and efficiency. Infrastructure monitoring focuses on tracking the health of the underlying hardware, such as CPU usage and disc utilization. This helps ensure that the system resources are not overburdened preventing slowdowns or crashes. Application performance monitoring. Also called as a PM, measures the performance of application by monitoring response times and database queries, allowing system to identify bottlenecks and optimize performance. Network monitoring focuses on latency. Packet loss and connectivity issues, ensuring smooth and communication between systems and minimizing disruptions. Lastly, securing monitoring involves tools for anomaly detection and intrusion detection systems, which helps identify unusual activity or potential security breaches. These four areas together provide a comprehensive approach to maintaining system health, optimizing performance, and ensuring security. Effective monitoring helps identify performance bottlenecks early, allowing steam to detect slowdowns, high resource usage or inefficiencies before they impact operations. This enables proactive problem resolution, which ensures our addressed before they escalate into major failures. Reducing downtime and minimizing business disruptions by continuously tracking key system metrics. Monitoring help ensure system stability and smooth user experience preventing unexpected crashes or performance issues. A well monitored system runs efficiently, maintains reliability, and keeps users satisfied. Ultimately supporting seamless business operations and long-term success. So components of alerting. Alerting its process of notifying teams when an issue arises, ensuring that potential problems are addressed before they are impacted. Users, it allows it. It works by triggering real time alerts based on predefined thresholds, such as high CPU usage, slow response times, or security threats. Alerting prevents unnoticed system failures by continuously monitoring critical components and immediate flagging anomalies, reducing the risk of prolonged downtime. It plays a crucial role in ensuring quick response time to incidents, enabling teams to act swiftly, resolve issues efficiently, and maintaining system stability. Effective alerting minimizes disruptions, protects users experience, and helps maintain business continuity. Alerting consists of key components, triggers notification channel and escalation policies. Triggers are the conditions that active alerts such as high CPU usage, server downtime, or security breaches, these predefined threshold ensures that teams are notified the moment an alert. Arises issue arises. Notification channels determine how alerts are delivered, including email, SMS Slack or PagerDuty, ensuring that the right people are informed instantly as soon as the issue is started occurring. Escalation policies ensures that if an alert is not acknowledged, it is forwarded to the next level, guaranteeing a response. Together these components create an efficient alert ring system that helps teams react quickly, prevent unnoticed failures, and maintain system stability. To build an effective alert system, it's important to set clear alert thresholds so teams are notified only when issue truly need attention. Ensuring alerts and actions are helps prevent unnecessary noise by providing relevant details and clear steps for resolution. Prioritizing alerts is crucial to avoid alert fatigue, ensuring that critical issues are addressed first while lower priority alerts don't overwhelm teams. Finally, using automation to resolve common issues helps reduce manual interventions by automatically handling repetitive problems, improve response times, and maintaining system stability. A well-structured alerting should keep operations as smooth and teams efficient. An effective alerting system can cause serious challenges. Too many alerts can overwhelm teams leading to alert fatigue. Where critical issues may be ignored, false positives and false negatives create confusion. False positive triggers, unnecessary responses while false negative causes real issues to go unnoticed. Delaying action, lack of context in alerts. Makes it difficult to diagnose problem quickly as alerts without relevant details. Force teams to spend extra time investigating. Finally, delayed responses can turn minor issues into major outages, impacting system uptime and user experiences. A well tuned alerts strategy ensures timely, accurate, and actionable notifications. To improve alerting effectiveness, it's essential to tune alert thresholds, carefully balancing sensitivity to avoid both excessive noise and missed issues implementing. Structured on-call rotations ensures that alerts are handled effectively, preventing burnouts, and ensuring 24 by seven coverage. Leveraging ai, ML based anomaly detection helps identify unusual patterns and reduce false positives, making alerting smarter and more precise. Lastly, ensuring logs and metrics provide enough enough context allows teams to quickly diagnose and resolve issues without unnecessary delays. Optimized alerting system enhances the response times, reduce fatigues and maintains system reliability. An effective alerting process follows a structured approach. Step one would be monitoring system health and collecting data to track key performance metrics in real time. Analyze logs and metrics. Detect two. Detect anomalies and identify potential issues before they actually escalate. Third would be a step up alerts based on the critical thresholds, ensuring teams are notified only when action is needed. Step four would be automate responses for faster recovery, reducing manual interventions, and minimizing downtime. Step five would be continuously refining alert rules to improve efficiency, reducing false alarms, and ensuring alert remains relevant. The structured approach helps maintain system stability and ensures the rapid issue resolution. There are various tools available for monitoring and alerting. Ramus and Grafana are popular open source solutions. That provide powerful monitoring and visualization capabilities. Datadog and New Relic are commercial observability platforms, offering real-time insights, application performance monitoring, and an advanced analysis for cloud environments providers offer built-in solutions like AWS CloudWatch. Azure Monitor and Google Cloud operations, which integrates seamlessly with cloud services to track performances, detect issues, and trigger alerts. Choosing the right tool depends on system requirement, scalability needs, and budget, ensuring. Efficient monitoring and proactive issue resolutions. When choosing monitoring tool. Consider your team's expertise, budget in budget, integration needs and specific monitoring requirements. The right tool ensures seamless tracking, quick alerts, and efficient issue resolution. Effective incident management and alerting, rely on the right tools. Page of duty and ops chiney are powerful incident management platforms that help team handle alert automation workflows and escalate critical issues to the right personal, ensuring quick resolution. Slack, VictorOps and Microsoft Teams enhanced collaboration with built-in alerting, allowing teams to receive notifications, discuss issues in real time, and coordinate responses efficiently. Additionally built in cloud alerting solutions like AWS CloudWatch Alarms, Azure Monitor Alerts, and Google Cloud Operation Alerts provide native monitoring and automated notifications within cloud environments, helping teams detect and address issues before they escalate together. These tools enables fast response times, streamlined communication, and improved system reliability. Imagine a scenario where an e-commerce platform experiences a sudden surge in traffic during a holiday sale, but due to a poor monitoring system, the system fails to detect the high CPU usage and database overload. As a result, pages low started loading slowly, transaction fails, and customer abandon their cards leading to lost revenue and customer dissatisfaction. The issue remains unnoticed for hours, significantly impacting the business operations and sales. After implementing proper monitoring and alerting the company set up a real-time performance, tracking automated alerts and AI driven anomaly detection. Now when traffic spikes alert, notify the teams immediately allowing them to scale resources and optimize database queries before user experience issues. As a result, downtime is reduced by 60%. Response time improved by 40%, and customer satisfaction scores increases. This example highlights the critical role of monitoring and alerting in preventing failures, ensuring system stability, and maintaining business success. To build an effective monitoring and alerting strategy, it's essential to follow the best practices. First, define key performance indicators that matters most to your system, such as uptime, response time, error rates, and re resources utilizations. These metrics help track system health and detect potential issues early. Second, choose the right monitoring and alerting tool that aligns with your infrastructure, whether open source solutions like ERs and Grafana or commercial platforms like Datadog and newly finally continuously irate and improve by analyzing system behavior, refining alert. Thresholds and leveraging automation to enhance efficiency. A well optimized approach ensures reliability, minimizes downtime, and improves overall system performance. Real-time dashboards provide a centralized view of system health by displaying key metrics such as CPU usage, memory consumption, network activity, and application response times. These dashboards offer instant visibility into performance trends, helping teams detect and address issues before they escalate. For example, a server monitoring dashboard might track CPU load and disc usage. While an application performance dashboard could display response times and error rates. Security dashboards can also provide insights into login attempt and potential threats. Real time insights enable proactive issue resolution by alerting teams to anonymize anomalies as they occur instead of reacting to system failures after they impacted the users. Teams can identify pattern, predict potential failures, and take preventive actions, ensuring stability, reducing downtime, and improving user experience. They allow customization to display the most relevant KPIs for different teams, such as latency error rates, throughput for engineering or user. Engagement metrics metricses for product teams. Monitoring dashboards, consolidate data from multiple sources like logs, APMs, infra metrics, metricses into a single view, enabling faster diagnosis, streamlined communication, and informed decision making across stack holders. The image shows a monitoring dashboard in Azure. From Azure Monitoring Services this is for a CH one real retail app AI application. It presents real time insights into system performance across four key areas, usage, reliability, responsiveness, and browser performance. Usage displays, unique session and user currently 6.5 a users showing trends over the past 24 hours. You can change this time window and see it for 12 hours, 48 hours, seven days, or any specified time window reliability highlights the field request with 16.63 K and server exceptions helping identify system issues. Responsiveness tracks server response times, which is 1.2 seconds as an average. And CP utilization is 15.15. Ensuring system efficiency. Browser performance monitor, average page load times 73 milliseconds network and 5 37 milliseconds. Client and browser errors. This dashboard helps teams quickly access system health, performance trends, and potential failures, enabling proactive troubleshooting. The future of monitoring and alerting is evolving with our advanced technologies. AI powered anomaly detection is transforming how systems identify issues. Using machine learning to detect unusual pattern and reduce false positives, predictive men, maintenance, and automated issues as solution, allow teams to proactively address potential failures before they occur. Minimize downtime and improving reliability. Enhanced integration across cloud and on-prem systems ensure seamless monitoring in hybrid environments, providing a unified view of system performance. Additionally, there is an increased focus on security monitoring with AI driven threats, detection, and real-time alert, helping organization protect against cyber threats. These advancements are making monitoring more intelligent, proactive, and efficient. Key takeaways. Effective monitoring and alerting are essential for maintaining system stability. Monitoring provides valuable insights by continuously tracking performance, helping teams detect and prevent potential failures before they actually escalate. Alerting ensures a quick response by notifying the right team in real time, minimizing the impact of issues and reducing downtime by implementing best practices such as settling clear thresholds, using automations and refining alert rules, organizations can significantly enhance system reliability. A well-structured monitoring and alerting strategy led to better performance, improved user experience, and seamless business operations. As applications, scale and architecture evolve, monitoring strategies should be revisited to ensure continued effectiveness. Regular audits, feedbacks, loops, and AI driven insights can improve detection, accuracy, and reduce false positives. Example, if a company shifts from a monolithic to a microservices, architecture monitoring tools must evolve to track interservice communication and dependencies. Thank you all for your time and attention today. I appreciate the opportunity to ensure to opportunity to share and in share my insights on monitoring and alerting. I would love to hear your questions or thoughts. Feel free to ask or share your experiences. If you would like to connect or discuss further, you can reach me out at my email or at LinkedIn, which is mentioned in this slide. I look forward to continue this conversation outside of this conference as well. Thank you.