November 2017 Summaries

James Kirk, Datadog's director of IT governance, risk management, and compliance, highlights the company's dedication to security and privacy as a top business priority, underscored by the recent release of their SOC 2 Type II report. This report, following the earlier SOC 2 Type I report, demonstrates Datadog's commitment to transparency and safeguarding customer data amid increasing global attention to privacy issues and regulatory changes such as the GDPR. The company's partnership with Coalfire Systems for an independent audit reflects their ongoing efforts to adhere to Trust Services Principles and Criteria. Datadog employs a multi-layer security design and continually updates its practices to meet current and future industry standards, underscoring their mission to provide a secure environment for customer data.

Query value widgets in Datadog now support custom background images and animated GIFs based on metric values, providing visual context to users. This feature was developed during an internal hackathon at Datadog. To set custom image backgrounds for query value graphs, users need to set conditional thresholds in the graph editor and then select Custom Image in the Show With menu, pasting a link to a hosted image or animated GIF. This update allows users to liven up their dashboards with fun, endlessly customizable visual context for their metrics.

To add visual context to query value widgets in Datadog, users can now set custom background images using static or animated GIFs. This feature allows for instant and customizable visualization of metrics, enabling users to quickly identify trends and anomalies. Users can paste a link to a hosted image or GIF into the graph editor, selecting from a variety of options to customize their widget's appearance. With this new feature, Datadog aims to provide an engaging and interactive experience for its customers, enhancing the overall dashboard experience.

Redis is a popular in-memory key/value data store used across industries and use cases such as databases, message queues, and memory caches. Monitoring Redis can help detect resource issues with the database itself or problems arising elsewhere in supporting infrastructure. Key performance metrics include latency, instantaneous_ops_per_sec, hit rate, used_memory, mem_fragmentation_ratio, evicted_keys, blocked_clients, connected_clients, connected_slaves, master_last_io_seconds_ago, keyspace, rdb_last_save_time, and rdb_changes_since_last_save. Error metrics include rejected_connections, keyspace_misses, and master_link_down_since_seconds. Monitoring these metrics can provide good visibility into the health and performance of Redis servers.

The text discusses the problem of unstable metrics causing frequent alerts and introduces recovery thresholds in Datadog to address this issue. Recovery thresholds work on the principle of hysteresis, similar to how a thermostat regulates temperature. They set different values for when an alert triggers and when it resolves, ensuring that an alert only enters the "recovered" state once a metric has passed the recovery threshold. This helps reduce noise and distraction from flapping monitors and increases confidence in issue resolution. Recovery thresholds can be set up during monitor creation via the UI or API, with separate thresholds for recovery from alert and warning states.

In order to prevent unnecessary alerts and distractions from unstable metrics, Datadog has introduced recovery thresholds. These thresholds work by setting a different value for when an alert triggers and when it resolves, using the principle of hysteresis. When creating a monitor via the UI or API, users can add recovery thresholds to their alert conditions, which apply to threshold alerts, change alerts, and anomaly detection. By doing so, users can increase confidence that an issue has truly been resolved once an alert recovers.