Questions and Answers
Which of the following is NOT a feature of Prometheus?
Based on the information provided, which of the following statements accurately reflects the relationship between Amazon CloudWatch and Prometheus?
What is the primary purpose of the Cloud Native Computing Foundation?
What is the main purpose of the mon-put-data
command in Amazon CloudWatch's command line interface?
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Based on the information provided, which of the following metrics is NOT typically monitored by Amazon CloudWatch?
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What is the maximum duration for which CloudWatch stores data with 1-minute granularity?
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Based on the text, what is the primary difference between basic monitoring and detailed monitoring in Amazon CloudWatch?
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What is the primary advantage of using a time series database for storing monitoring metrics?
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Which of the following is NOT mentioned as a method to access Amazon CloudWatch?
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What is the primary role of an exporter in Prometheus?
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How does Prometheus handle alerts?
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Which of these is a key benefit of using Grafana with Prometheus?
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Which of the following is a characteristic of log files, as described in the text?
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How does Prometheus achieve scalability?
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What is the significance of the 'for' clause in a Prometheus alert rule?
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Which of these is NOT a characteristic of Prometheus?
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How is a PostgreSQL exporter typically deployed?
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What is the purpose of the 'expr' clause in a Prometheus alert rule?
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What is the primary purpose of "Log Normalization" in log analysis best practices?
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Which of the following is NOT a benefit of properly structured logs?
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What is the key difference between log streams and log groups in AWS CloudWatch Logs?
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What is the role of "Artificial Ignorance" in log analysis best practices?
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How does CloudWatch Logs Insight enable real-time processing of logs?
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Which of the following is NOT a characteristic of the distributed tracing approach described as "Google Dapper"?
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How does CloudWatch Logs facilitate log analysis and visualization?
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What is the primary purpose of capturing the interaction of different services in "Distributed Tracing"?
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What is the main difference between traditional log analysis and CloudWatch Logs Insight?
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What is a key feature of Logstash in relation to data?
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Which functionality is NOT provided by X-Pack?
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What type of data does Filebeat primarily collect?
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What purpose does the Aggregator Framework serve within the Elastic Stack?
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Which of the following is a function of Beats in the Elastic Stack?
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Which aspect of the Elastic Stack does NOT contribute to logging beyond debugging?
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Which of the following describes a use of geo-location lookups in Logstash?
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What is a primary role of the SQL interface in the Elastic Stack?
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What is the main purpose of parsing in Logstash?
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Which of these statements is TRUE about the backward compatibility of Protobuf?
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Which of these statements is FALSE about Protobuf?
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What is the main advantage of using Protobuf over ASCII representation for logs?
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Which of these is NOT a benefit of using structured logs?
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Which of these statements best describes the use of structured logs?
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Why might ASCII representation for logs be considered inefficient?
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What is a major advantage of Protobuf over other binary formats for logs?
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Which of these characteristics of Protobuf makes it suitable for logging?
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Which of these best describes the purpose of Protobuf?
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What is the primary function of the Aggregator Framework in the Elastic Stack?
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What type of data does Filebeat primarily collect?
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What is a key feature of Logstash in relation to data?
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What is a key benefit of using X-Pack with the Elastic Stack?
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What is the primary purpose of Beats in the Elastic Stack?
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What is a key feature of Kibana?
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What is the main purpose of adaptive sampling in the context of Dapper?
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What is the main advantage of using asynchronous writes in Dapper?
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What is the purpose of coalescing events in Dapper?
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What is the main feature of the Dapper Depot API?
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What is the purpose of indexed access in the Dapper Depot API?
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What is the main advantage of using Open Telemetry (OTel) over other distributed tracing solutions?
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What is the main purpose of runtime verification in the context of distributed tracing?
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What is the main benefit of using policy-based isolation in distributed tracing?
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What does Elasticsearch primarily organize data into?
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Which of the following best describes Logstash's primary function?
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What is a primary feature of Kibana?
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What aspect of the Elastic Stack does X-Pack primarily enhance?
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What type of data do Beats primarily collect?
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What characteristic of Elasticsearch allows it to scale effectively?
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Study Notes
Monitoring and Logging
- Metrics monitored by Amazon CloudWatch:
- CPU utilization, data transfer, and disk usage for EC2 instances
- Read/write latency for EBS volumes
- Request counts and latency for load balancer
- Number of messages sent for Simple Queueing Service (SQS) queues
- Freely available memory and storage for RDS DB instances
- Custom application and system metrics
- Data provided by CloudWatch:
- Frequency: every second to 5 minutes depending on the data and account
- Data with < 1 minute granularity stored for three hours
- Data with 1 minute granularity stored for two weeks
- Data with 1 hour granularity stored for 15 months
- Actions available in CloudWatch:
- View graphs and statistics
- Set alarms
- Access to CloudWatch:
- Management Console web interface
- Command-line interface
- Libraries for Java, Script languages, Windows.Net
- Web Service API
Custom Metrics and Alarms
- Defining custom metrics:
- Use the command line interface (mon-put-data) to specify data points
- Can specify multiple aggregated data points (sum, minimum, maximum, SampleCount)
- Getting access statistics:
- Use the command line interface (mon-get-stats) to retrieve statistics
Pricing and Limits
- Pricing:
- Basic monitoring is free (standard metrics every 5 minutes)
- Detailed monitoring of EC2 instances every minute
- Each alarm, each custom metric, and CloudWatch API calls incur costs
- Free Tier:
- 10 Detailed Monitoring Metrics (at 1-minute frequency)
- 1 Million API requests (not applicable to GetMetricData and GetMetricWidgetImage)
- 3 Dashboards for up to 50 metrics per month
- 10 Alarm metrics (not applicable to high-resolution alarms)
- 5GB Data (ingestion, archive storage, and data scanned by Logs Insights queries)
Prometheus
- Features:
- Metric collection in the form of time series
- Storage by a time series database
- Query language for accessing the time series
- Alerting
- Visualization
- Alerting:
- Separated into Prometheus server and Alertmanager
- Rules determine an alert (e.g., HighRequestLatency)
- Alertmanager manages alerts, including silencing, inhibition, grouping, and sending notifications
Visualization and Scalability
- Visualization with Grafana:
- Open-source platform for visualization
- Prometheus is one of the possible data sources
- Connect through IP address and port
- Create your own dashboard
- Scalability:
- Hierarchical federation of servers
Logs
- Definition:
- A log is a sequence of immutable records of discrete events
- Generated by applications, system level, infrastructure, and devices
- Logging levels:
- Configuration allows drilling down
- Difficulty in analyzing logs
- Representation:
- ASCII (easily readable but inefficient with respect to space and time)
- Binary (more efficient, e.g., protobuf from Google)
Logstash and Kibana
- Logstash:
- Supports parsing for predefined patterns (grok patterns)
- Transforms and filters
- Derives structure
- Anonymizes personal data
- Geo-location lookups
- Kibana:
- Open-source platform for visualization
- X-Pack provides extensions to ELK:
- Authentication and authorization
- Monitoring ELK
- Alerting
- Report generation of Kibana contents
- Machine learning (e.g., anomaly detection and forecasting)
- SQL interface for Elastic Search
Beats and Application of Log Processing
- Beats:
- Agents to collect data
- Filebeat for logs
- Metricbeat for metrics
- Heartbeat for health
- Application of Log Processing:
- Logging has other uses besides debugging and performance monitoring
- Properly structured logs help with:
- Incident root cause analysis
- Anomaly detection
- Fault prediction and predictive maintenance
- Detecting and responding to Data Breaches and Other Security Incidents
- Ensuring Compliance with Security Policies, Regulations & Audits
- Best practices for log analysis:
- Pattern Detection and Recognition
- Log Normalization
- Classification and Tagging
- Correlation Analysis
- Artificial Ignorance
AWS CloudWatch Logs
- Allows storing and analyzing logs from Amazon Services and applications
- Log group:
- Clusters several log streams from multiple sources
- Metrics can be extracted from log statements automatically and inserted into CloudWatch metrics
- Retention period can be controlled
- Analysis via CloudWatch Logs Insight:
- Special query language for analysis with support for log entry fields from AWS service logs and JSON-based application logs
- Support for visualization of query results
- Real-time processing via:
- Streaming to Kinesis analytics service or Lambda
- Streaming to your Amazon OpenSearch Service cluster supporting OpenSearch and Elasticsearch
ELK Stack for Log Processing
- ELK stack consists of Elasticsearch, Logstash, and Kibana
- It's open source and free, suitable for logs and metrics
- Elastic Stack is an extension of ELK, adding Beats and X-Pack
Elasticsearch
- Distributed data store, search, and analytics engine based on Apache Lucene
- NoSQL database, organized in indexes
- Each index is a collection of documents (JSON objects), with a schema-free structure
- Automatically extends schema as new documents are added
- Distributed, scales horizontally using multiple servers (nodes) for availability and fault tolerance
- Indexes are stored in shards (primary and replicas) on nodes, forming a cluster
Logstash
- Supports parsing for predefined patterns (grok patterns)
- Performs transforms and filters
- Derives structure from data
- Anonymizes personal data
- Supports geo-location lookups
- Has various filter plugins available
X-Pack
- Extensions to ELK, providing:
- Authentication and authorization
- Monitoring ELK
- Alerting
- Report generation of Kibana contents
- Machine learning (anomaly detection and forecasting)
- SQL interface for Elasticsearch
Beats
- Agents for collecting data
- Includes Filebeat for logs, Metricbeat for metrics, and Heartbeat for health
- Provides integrations for data injection from major systems
Kibana
- No detailed information provided
Managing Overheads
- Trace generation and collection overheads
- Amount of resources required to store and analyze trace data
- Coalescing events reduces overheads
- Asynchronous writes reduce application tracing overhead
Adaptive Sampling
- Sampling rate adjusts based on application throughput
- Reduces overall size and meets Bigtable throughput limits
- Trace ID determines data collection
Dapper Tools
- Dapper Depot API provides access to traces via trace ID, bulk access, and indexed access
- Indexed access uses a single index, combining service name and host name
Open Source Alternative
- Open Telemetry (OTel) is a merger of Open Tracing and Open Census
- Originally developed by Google from 2001-2008, now open source and maintained by Google
- Uses protocol buffers (protobuf) for data structure definition and serialization
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Description
This quiz covers the metrics monitored by Amazon CloudWatch, including EC2 instances, EBS volumes, load balancers, SQS queues, RDS DB instances, and custom application and system metrics.