Application instances generating raw log files
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Amazon CloudWatch Logs
Collects, stores, queries, and routes application and AWS service logs
Why learn Amazon CloudWatch Logs?
Teams use Amazon CloudWatch Logs to adopt centralized cloud logging without building the complete underlying platform themselves.
The problem it solves
Collects, searches, retains, and routes platform and application logs
Where it came from
Amazon CloudWatch Logs is Amazon Web Services's offering for centralized cloud logging. Its closest catalog counterparts are Azure Log Analytics and Google Cloud Logging; they address the same broad need but are not feature-for-feature identical.
Build your understanding
Work through these exercises in order. Try the task before opening a reference.
- Explain the main responsibility of Amazon CloudWatch Logs.
- Choose a workload that fits Amazon CloudWatch Logs.
- Identify one operational tradeoff of Amazon CloudWatch Logs.
- Compare Amazon CloudWatch Logs with Azure Log Analytics.
- Compare Amazon CloudWatch Logs with Google Cloud Logging.
Documentation and sources
- AWS cloud services catalog (aws.amazon.com)
Connect the ideas
Alternatives
Real World Example
Log Aggregation for Distributed Microservices
A retail logistics company operating a fleet of distributed microservices across multiple compute environments.
The business problem
The engineering team struggles to correlate errors across fragmented service logs, leading to extended mean-time-to-resolution during intermittent order processing failures.
How this topic solves it
By centralizing application logs into Amazon CloudWatch Logs, the team gains a unified interface to query and analyze log streams, allowing for cross-service pattern matching and centralized retention management.
- Install the CloudWatch agent on compute instances to capture local application log files.
- Configure log groups to define retention policies for compliance and data lifecycle management.
- Define log streams within log groups to organize data by specific service instances or containers.
- Utilize CloudWatch Logs Insights to execute queries across multiple log groups for rapid error identification.
- Set up subscription filters to route specific error patterns to downstream notification services.
This diagram illustrates the flow of log data from distributed services to the centralized analysis interface.
Local daemon collecting and pushing logs
Centralized storage and indexing service
Interface for analysis and pattern matching
- Microservices → writes to local file → CloudWatch Agent
- CloudWatch Agent → pushes log events → CloudWatch Logs
- CloudWatch Logs → queries stored data → Insights Query
Expected business outcome
Engineers achieve a holistic view of the request lifecycle, enabling faster identification of root causes without manual log file aggregation.
Limitations and checks
CloudWatch Logs imposes a maximum limit on the size of individual log events; if an application generates exceptionally large stack traces, the log ingestion may be truncated, which can be checked by monitoring the IngestionError metric.