Importance of Reliability in Distributed Systems: Datadog Outage Case Study

#Datadog, a monitoring and analytics platform for IT infrastructure, experienced an outage due to the failure of a single node in their distributed data pipeline system. Customers experienced gaps in historical data, elevated latency, and error rates. The issue was resolved by replacing the failed node and backfilling data. The incident emphasized the importance of reliable and fault-tolerant distributed systems and the need for rigorous monitoring and testing to identify potential weaknesses. Future actions include reviewing the system architecture, establishing redundancy in critical components, and regular testing of resilience.

Brief Overview of Datadog:

Datadog is a monitoring and analytics platform that provides visibility into the performance of IT infrastructure, applications, and logs.

Customer Experience during the Outage:

During the outage, customers experienced gaps in their historical data for certain products. They also faced elevated latency and error rates on the web application for metric queries and APM.

Actual Issue:

The actual issue was that the data pipeline that feeds into Datadog's data ingestion systems experienced an outage, leading to a disruption in data processing and delivery.

Root Cause:

The root cause of the issue was the failure of a single node in a distributed data pipeline system. The failure resulted in the node being unable to process data, leading to a backlog of unprocessed data that overwhelmed the rest of the pipeline, causing a cascading failure across the system.

How was the issue fixed?

The issue was fixed by identifying the failed node and replacing it with a new one. The new node was able to process data, which helped to clear the backlog and restore the system's normal operation.

High-Level Timeline of Events:

• On March 8, 2023, the data pipeline that feeds into Datadog's data ingestion systems experienced an outage.
• Customers experienced gaps in their historical data for certain products and elevated latency and error rates on the web application for metric queries and APM.
• The root cause of the issue was identified to be the failure of a single node in a distributed data pipeline system.
• The failed node was replaced with a new one, and the new node was able to process data, clearing the backlog and restoring the system's normal operation.
• Backfilling of data was completed for different products such as Real User Monitoring, Database Monitoring, Network Performance Monitoring, Network Device Monitoring, and Log Management.
• Monitoring of the recovery was done, and all Datadog systems were receiving, querying, and evaluating monitors on live data as normal.
• Customers still experienced gaps in historical data for parts of the last 24 hours.
• Backfilling of data was continued for certain products, and updates were provided every 2 - 3 hours until the backfill effort was completed, and the incident was fully resolved.

Lessons Learned:

The incident highlighted the importance of distributed systems' reliability and fault-tolerance. It also demonstrated the need for monitoring and alerting on the data pipeline's performance and the ability to quickly identify and replace failed nodes.

Potential PoR Actions:

• Review the current distributed systems architecture and ensure it is designed with reliability and fault-tolerance in mind.
• Establish more rigorous monitoring and alerting on the data pipeline's performance to detect issues early and take corrective action quickly.
• Implement redundancy in critical components of the data pipeline to prevent a single point of failure.
• Establish a process for regular review and testing of the data pipeline's resilience to identify and address potential weaknesses before they become a problem.
• Conduct post-incident reviews to identify further areas of improvement and ensure that lessons learned are incorporated into future incident response plans.

Note: The information presented in this article is based on publicly available sources and does not guarantee its completeness or correctness.