Is a location service that allows applications to know when a user has crossed a specific location and then triggers an automated action?

Amazon CloudWatch dashboards enable you to create reusable graphs and visualize your cloud resources and applications in a unified view. You can graph metrics and logs data side by side in a single dashboard to quickly get the context and move from diagnosing the problem to understanding the root cause. For example, you can visualize key metrics, such as CPU utilization and memory, and compare them to capacity. You can also correlate the log pattern of a specific metric and set alarms to alert you to performance and operational issues. This gives you system-wide visibility into operational health and the ability to quickly troubleshoot issues, reducing MTTR.

With Amazon CloudWatch composite alarms, you can combine multiple alarms and reduce alarm noise. If an issue affects several resources in an application, you will receive a single alarm notification for the entire application instead of one for each affected resource. This helps you focus on finding the root cause of operational issues to reduce application downtime. You can provide an overall state for a grouping of resources, such as an application, AWS Region, or Availability Zone.

Amazon CloudWatch alarms allow you to set a threshold on metrics and trigger an action. You can create high-resolution alarms, set a percentile as the statistic, and either specify an action or ignore as appropriate. For example, you can create alarms on Amazon EC2 metrics, set notifications, and take one or more actions to detect and shut down unused or underutilized instances. Real-time alarming on metrics and events enables you to minimize downtime and potential business impact.

Applications and infrastructure resources generate large amounts of operational and monitoring data in the form of logs and metrics. In addition to letting you access and visualize these datasets in a single platform, Amazon CloudWatch also makes it easy to correlate them. This helps you quickly move from diagnosing the problem to understanding the root cause. For example, you can correlate a log pattern, such as an error to a specific metric, and set alarms to alert you to performance and operational issues.

Amazon CloudWatch Application Insights provides automated setup of observability for your enterprise applications so you can get visibility into their health. It helps you identify and set up key metrics and logs across your application resources and technology stack, such as database, web (IIS) and application servers, operating system, load balancers, and queues. It constantly monitors this telemetry data to detect and correlate anomalies and errors to notify you of any problems in your application. To aid in troubleshooting, it creates automated dashboards for the detected problems with correlated metric anomalies and log errors, along with additional insights to point you to their potential root cause. This enables you to take quick remedial actions to ensure that your applications are healthy and end users are not impacted.

Container Insights provides automatic dashboards in the CloudWatch console. These dashboards summarize the compute performance, errors, and alarms by cluster, pod/task, and service. For Amazon EKS and k8s, dashboards are also available for nodes/EC2 instances and namespaces. Each dashboard summarizes the list of running pods/tasks or containers by CPU and memory for the selected time window. You can dive deeper into application logs, AWS X-Ray traces, and performance events contextually, based on time window and selected pod/task or container.

Lambda Insights provides automatic dashboards in the CloudWatch console. These dashboards summarize the compute performance and errors. Each dashboard includes the list of metrics for the selected time window and allows you to dive deeper contextually (based on time window and selected function) into application logs, AWS X-Ray traces, and performance events.

Amazon CloudWatch Anomaly Detection applies machine-learning (ML) algorithms to continuously analyze metric data and identify anomalous behavior. It allows you to create alarms that auto-adjust thresholds based on natural metric patterns, such as time of day, day of week, seasonality, or changing trends. You can also visualize metrics with anomaly detection bands on dashboards. This enables you to monitor, isolate, and troubleshoot unexpected changes in your metrics.

You can use Amazon CloudWatch ServiceLens to visualize and analyze the health, performance, and availability of your applications in a single place. It ties together CloudWatch metrics and logs as well as traces from AWS X-Ray to give you a complete view of your applications and their dependencies. Quickly pinpoint performance bottlenecks, isolate root causes of application issues, and determine the impact on users. CloudWatch ServiceLens lets you gain visibility into your applications in three main areas: infrastructure monitoring (using metrics and logs to understand the resources supporting your applications), transaction monitoring (using traces to understand dependencies between your resources), and end-user monitoring (using canaries to monitor your endpoints and notify you when the end-user experience has degraded). CloudWatch ServiceLens provides a Service Map that visualizes the contextual linking of all your resources, along with an intuitive interface so you can dive deep into correlated monitoring data.

Amazon CloudWatch Synthetics allows you to monitor application endpoints more easily. It runs tests on your endpoints 24/7 and alerts you if they don’t behave as expected. These tests can be customized to check for availability, latency, transactions, broken or dead links, step-by-step task completions, page load errors, load latencies for UI assets, complex wizard flows, or checkout flows in your applications. You can also use CloudWatch Synthetics to isolate alarming application endpoints and map them back to underlying infrastructure issues to reduce MTTR. With this new feature, CloudWatch now collects canary traffic, which can continually verify your customer experience even when there is no customer traffic on your applications, enabling you to discover issues before your customers do. CloudWatch Synthetics supports monitoring your REST APIs, URLs, and website content, checking for unauthorized changes from phishing, code injection, and cross-site scripting.

Amazon CloudWatch RUM gives you visibility into your applications’ client-side performance and reduces MTTR. It allows you to collect client-side data on web application performance in near real time to identify and debug issues. CloudWatch RUM complements the CloudWatch Synthetics data to give you more visibility into your end-user experience. You can visualize anomalies in performance and use the relevant debugging data (such as error messages, stack traces, and user sessions) to fix performance issues (such as JavaScript errors, crashes, and latencies). You can gain insight into the range of end-user impacts, including number of users, geolocations, and browsers. CloudWatch RUM aggregates data on your users' journey through your application, which can help you determine which features to launch and bug fixes to prioritize.

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