Greetings, fellow learners! Today unfolds another chapter in my AWS DevOps certification journey, and I'm thrilled to share the knowledge gained on Day 8 through StΓ©phane Maarek's Udemy course.
π‘ Course Progress - Day 8: Exploring CloudWatch, Amazon Lookout, CloudWatch Logs, Alarms, and More!
As we navigate through AWS CloudWatch and related services, let's dive into the diverse topics covered and gain valuable insights for effective monitoring and analytics in the cloud.
π Key Learnings
π What are CloudWatch Metrics?
Amazon CloudWatch is a monitoring service for AWS resources and the applications you run on them. CloudWatch provides data and actionable insights to monitor applications, respond to system-wide performance changes, optimize resource utilization, and get a unified view of operational health. CloudWatch Metrics are the fundamental concept of CloudWatch. They are time-ordered sets of data points that represent the values of a metric over time. Metrics are used to monitor various resources such as EC2 instances, RDS DB instances, and custom metrics.
π CloudWatch Custom Metrics
CloudWatch Custom Metrics are metrics that you define and send to CloudWatch. You can use custom metrics to collect and analyze your own application-specific data. You can publish custom metrics from any application or service that sends data to CloudWatch.
π CloudWatch Anomaly Detection
Amazon CloudWatch Anomaly Detection is a feature that enables you to monitor your metrics for unusual behavior. It uses machine learning algorithms to continuously analyze your metrics and detect anomalies. When an anomaly is detected, CloudWatch sends an alert to notify you of the issue.
π Amazon Lookout for Metrics
Amazon Lookout for Metrics is a machine learning service that detects anomalies in your metrics. It uses machine learning to automatically identify anomalies in your metrics and provide you with insights into the root cause of the issue.
π CloudWatch Logs
Amazon CloudWatch Logs is a managed service that makes it easy to centralize logs from all your systems, applications, and AWS services in one place. You can use CloudWatch Logs to monitor, store, and access your log files from Amazon EC2 instances, AWS CloudTrail, and other AWS services.
π CloudWatch Logs Live Tail
CloudWatch Logs Live Tail is a feature that enables you to view real-time log data from your CloudWatch Logs in a web browser. You can use Live Tail to monitor your logs and troubleshoot issues in real-time.
π CloudWatch Logs Metric Filter
CloudWatch Logs Metric Filter is a feature that enables you to extract metric data from your log data. You can use Metric Filters to search for specific terms, phrases, or values in your log data and create metrics based on that data.
π CloudWatch Agent and CloudWatch Log Agent
CloudWatch Agent and CloudWatch Log Agent are two agents that you can use to collect and send log data to CloudWatch. CloudWatch Agent is used to collect system-level metrics and logs from Amazon EC2 instances and on-premises servers. CloudWatch Log Agent is used to collect and send log data from Amazon EC2 instances and on-premises servers.
π CloudWatch Alarms
CloudWatch Alarms enable you to monitor metrics over a specified time period and perform one or more actions based on the value of the metric relative to a threshold over time. You can use CloudWatch Alarms to monitor any metric that CloudWatch supports.
π CloudWatch Synthetics
Amazon CloudWatch Synthetics is a service that enables you to monitor your endpoints and APIs. You can use CloudWatch Synthetics to create canaries, which are scripts that run on a schedule to simulate user interactions with your endpoints and APIs.
π Amazon Athena
Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run.
β¨ The Journey Continues: As Day 8 wraps up, I'm excited about the depth of understanding gained and the practical skills acquired. Stay tuned for more updates as my AWS DevOps journey continues to unfold!