Amazon Analytics Services Monitoring
Amazon analytics services are designed for data processing, querying, visualization, and machine learning integration to handle big data workloads efficiently. Monitoring these services ensures performance, cost control, and reliability for data-intensive workloads like those in IT infrastructure analytics.
Applications Manager can help you monitor:
AWS Glue Crawler monitoring
AWS Glue Crawlers automatically scan your data sources, infer schemas, and populate the AWS Glue Data Catalog, making reliable crawler operation critical for accurate downstream ETL and analytics workflows. Monitoring crawlers helps you catch failed or stalled crawls, catalog inconsistencies, and unusually long runtimes before they delay data availability for reporting and analytics.
Applications Manager tracks the health and performance of your Glue Crawlers with detailed visibility into recent crawl activity and catalog changes. With Applications Manager's AWS Glue Crawler monitor, you can:
- Monitor the last crawl status, start time, and crawl error message, along with failed and stopped run percentages, to quickly spot crawls that failed or were interrupted.
- Track table activity metrics, such as created, updated, and deleted tables, to understand how frequently your Glue Data Catalog is changing.
- Keep an eye on runtime metrics, including last runtime, median runtime, and estimated remaining time for active crawls, to detect performance degradation early.
- Review run state distribution metrics, such as failed, stopped, completed, and total runs, to gauge overall crawler reliability over time.
- Drill down into individual crawl executions, classifiers, and crawler data source targets for granular troubleshooting.
AWS Glue Job monitoring
AWS Glue Jobs run the ETL scripts that extract, transform, and load data across your pipelines, so job failures or slowdowns can directly delay analytics and downstream reporting. Monitoring Glue Jobs helps you identify resource bottlenecks, failed or timed-out runs, and data movement issues before they affect your ETL workflows.
Applications Manager provides executor-level visibility into your Glue Job runs to help you pinpoint performance issues quickly. With Applications Manager's AWS Glue Job monitor, you can:
- Track system load and JVM heap usage across executors and the driver node to identify resource contention affecting job performance.
- Monitor ETL data movement metrics, such as S3 data read/write rates and shuffle data read/write rates across executors, to understand data throughput and inter-executor transfer overhead.
- Keep tabs on task activity, including failed, killed, and completed tasks and stages, along with data and record read rates, to catch processing issues early.
- Review job run state distribution and job run percentages, covering completed, failed, waiting, canceled, error, and timeout runs, to assess overall job reliability.
- Analyze individual job run details, triggers, and job configuration, including worker type, DPU allocation, and retry settings, for deeper troubleshooting and capacity planning.
Amazon MSK cluster monitoring
Amazon MSK clusters require monitoring to ensure high availability, performance, and reliability in streaming data workloads. Proactive monitoring helps you detect issues like high latency, broker failures, or resource exhaustion before they impact your applications. You can address key operational challenges like unexpected scaling limitations, maintenance disruptions, and hidden costs in production environments.
Applications Manager gives visibility into cluster heath, enabling quick identification of potential performance bottlenecks and operational anomalies.
- Track overall cluster availability and operational state with metrics such as cluster state, number of brokers, active controllers, zookeeper session state, etc. Monitor key resource utilization metrics including Kafka Datalogs Disk Utilization, Express Storage Utilization, and ZooKeeper Request Mean Latency to track high performance storage usage, support effective capacity planning, and prevent storage related performance issues.
- Keep tabs on data and partition metrics to assess data integrity and distribution. These metrics include offline partitions, global partitions, and global topics.
- Track configuration attributes including security, storage, network configuration to ensure optimal performance, compliance, and early detection of misconfigurations that could lead to instability or inefficiencies.
Amazon Redshift monitoring
Gain comprehensive visibility into the health and performance of Amazon Redshift clusters and prevent slowdowns, timeouts, and downtime that can disrupt analytics and business operations.
Applications Manager collects a broad set of performance metrics, such as resource utilization (CPU, disk, database connections), network throughput, and storage health, for both leader and compute nodes, enabling proactive detection of issues before they affect users or escalate costs. You can also track detailed query performance data, including query duration, throughput, lifecycle phase times (like planning, waiting, and commit times), and various execution stages. Additionally, you can monitor concurrency scaling metrics to understand how often and how long extra clusters are launched, aiding in optimizing cluster sizing and cost efficiency.
At the cluster and node level, Applications Manager helps identify bottlenecks, uneven workload distribution, and potential resource contention by tracking throughput, inbound/outbound network traffic, and disk activity. Real-time visibility into cluster state, connection health, and network performance ensures reliable operations and quicker troubleshooting.
Learn more about Amazon Redshift monitoring.
Get started with Amazon Analytics Services monitoring in minutes!
Get started with AWS Analytics Services monitoring in minutes using Applications Manager by simply connecting your AWS account and auto-discovering analytics services. Download a 30-day free trial and explore real-time performance, availability, and resource monitoring from a unified dashboard.
Do more with Applications Manager's AWS monitoring capabilities:
