Apache FlinkMetricflink_jobmanager_job_lastcheckpointduration
The time it took to complete the last checkpointDimensions:None
Available on:
Datadog (1)
Datadog (1)Interface Metrics (1)
Datadog
Dimensions:None
Knowledge Base (17 documents, 0 chunks)
referenceMetrics and dimensions in Managed Service for Apache Flink - Managed Service for Apache Flink2465 wordsscore: 0.95Official AWS documentation for Managed Service for Apache Flink (Amazon MSF) metrics and dimensions. Provides comprehensive reference of application metrics, including CPU, memory, checkpoint, watermark, and backpressure metrics that are reported to Amazon CloudWatch for monitoring Flink applications.
documentationConfigure alert rules - Realtime Compute for Apache Flink - Alibaba Cloud Documentation Center2253 wordsscore: 0.85Alibaba Cloud documentation for configuring alert rules in Realtime Compute for Apache Flink. Covers metric-based and event-based alerting using Cloud Monitor and Managed Service for Prometheus (ARMS), including configuration steps for job monitoring, workflow alerts, and alert rule creation.
troubleshootingFlink JobManager dies due to checkpoint failures - Stack Overflow762 wordsscore: 0.72This Stack Overflow discussion addresses JobManager failures caused by checkpoint exceptions after upgrading from Flink 1.9.0 to 1.11.1. The issue involves FileAlreadyExistsException when reusing fixed job IDs without HA, and discusses checkpoint recovery behavior and the necessity of HA for JobManager failure tolerance.
documentationApache Flink 1.11 Documentation: Monitoring Checkpointing1331 wordsscore: 0.95Official Apache Flink documentation page covering checkpoint monitoring through the web UI. Details the four monitoring tabs (Overview, History, Summary, Configuration) with comprehensive statistics about checkpoint counts, status, timing, data sizes, and alignment buffering.
tutorialHow to Configure Flink Checkpointing2144 wordsscore: 0.75This tutorial provides comprehensive guidance on configuring Apache Flink checkpointing for fault tolerance, covering checkpoint intervals, state backends (HashMap and RocksDB), and configuration options. It includes practical code examples in Java and YAML configuration files for enabling checkpointing, tuning intervals, and selecting appropriate state backends based on state size.
best practicesBest practices for monitoring and alerting - Realtime Compute for Apache Flink - Alibaba Cloud Documentation Center1247 wordsscore: 0.95Comprehensive guide for monitoring and alerting on Apache Flink jobs running on Alibaba Cloud. Covers key metrics for job health, stability, data timeliness, and resource performance with specific alert thresholds and remediation steps.
documentationMonitoring Checkpointing | Apache Flink1023 wordsscore: 0.95Official Apache Flink documentation page detailing how to monitor checkpointing through the web UI. Covers four tabs (Overview, History, Summary, Configuration) that display checkpoint statistics including counts, durations, data sizes, and status information at both job and subtask levels.
troubleshootingCheckpointing is timing out - Managed Service for Apache Flink433 wordsscore: 0.85This AWS documentation page provides troubleshooting guidance for checkpoint timeout issues in Managed Service for Apache Flink. It describes symptoms to monitor, including checkpoint failure metrics and memory-related metrics, and provides causes and solutions for checkpoint failures such as insufficient provisioning, large state sizes, and garbage collection backpressure.
tutorialHow to Build Real-Time Data Pipelines with Kafka and Flink1169 wordsscore: 0.65This tutorial demonstrates how to build real-time data pipelines by integrating Apache Kafka with Apache Flink for stream processing. It covers architecture design, Kafka topic configuration, Python producers, Flink streaming jobs with windowed aggregations, checkpointing for exactly-once semantics, and Kubernetes deployment configurations.
documentationCheckpoints | Apache Flink842 wordsscore: 0.75This page documents Apache Flink's checkpoint mechanism for fault tolerance, explaining how state is persisted during checkpointing. It covers checkpoint storage options (JobManagerCheckpointStorage and FileSystemCheckpointStorage), configuration methods, retained checkpoints, directory structure, and how to resume from checkpoints.
troubleshootingTroubleshoot checkpoint failures in your Amazon Managed Service for Apache Flink application | AWS re:Post859 wordsscore: 0.85This AWS re:Post Knowledge Center article provides troubleshooting guidance for checkpoint failures in Amazon Managed Service for Apache Flink applications. It covers major causes of checkpoint failures including RocksDB performance issues, S3 storage latency, state serialization problems, insufficient KPU provisioning, large state sizes, skewed state distribution, and high cardinality issues.
documentationApache Flink 1.7 Documentation: Monitoring Checkpointing1177 wordsscore: 0.95Official Apache Flink 1.7 documentation page describing the web interface for monitoring checkpoints. Covers checkpoint statistics, history tracking, configuration parameters, and detailed metrics available through the UI including checkpoint counts, durations, state sizes, and alignment buffering.
troubleshootingApache Flink checkpointing stuck - Stack Overflow911 wordsscore: 0.72This Stack Overflow thread addresses Apache Flink checkpointing issues when managing large state (300-400GB ListState) with millions of timers in RocksDB. The discussion covers how timer storms and inefficient state management can cause checkpointing to get stuck or timeout, with solutions including using State TTL, MapState instead of ListState, and timer jitter.
best practicesOperating Flink Is Hard: What does this really mean? And how to go about it?1627 wordsscore: 0.85This blog post provides operational best practices for running Apache Flink in production, emphasizing that Flink jobs should be treated like microservices. It covers capacity planning, performance testing, monitoring strategies, and how different teams (platform engineers vs application developers) should approach observability with different metrics and alert thresholds.
documentationSavepoints and external checkpoints - BBData docs1072 wordsscore: 0.72This page documents savepoints and externalized checkpoints in Apache Flink, explaining their configuration, triggering, and usage for state persistence and job recovery. It covers the requirements, differences between savepoints and externalized checkpoints, configuration parameters, and best practices for resuming jobs from persisted state.
documentationFault Tolerance | Apache Flink1053 wordsscore: 0.72This documentation covers Apache Flink's fault tolerance mechanisms through state snapshots, including state backends (RocksDB and heap-based), checkpoint storage options, and exactly-once processing guarantees. It explains how Flink uses asynchronous barrier snapshotting based on the Chandy-Lamport algorithm to create consistent snapshots for recovery.
documentationOptimizing Flink job restart times for task recovery and scaling operations with Amazon EMR on EKS - Amazon EMR1722 wordsscore: 0.75This AWS documentation page describes optimization techniques for Flink job restart times during task recovery and scaling operations on Amazon EMR on EKS. It covers task-local recovery, EBS volume mounting, incremental checkpointing, and fine-grained recovery mechanisms to reduce recovery time from minutes to seconds.
Related Insights (2)
Checkpoint Failure Cascadecritical
Rising checkpoint failures indicate upstream backpressure, state growth issues, or resource exhaustion that will eventually cause job restarts and data loss.
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JVM GC Death Spiralcritical
High garbage collection pressure on TaskManagers causes processing slowdowns that create backpressure, increased state size, and eventually full GC pauses lasting minutes.
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