Backend Systems

2 posts

datadog3 min readCurated summary

Steganography at scale: Embedding share URLs in Datadog widget screenshots

Datadog is building a way for screenshots to preserve the context normally available through share links. The system invisibly embeds a compact widget identifier into screenshot pixels, while storing the full widget definition in Redis. This approach aims to combine screenshots’ convenience with share links’ ability to restore queries, time ranges, and dashboard state, at massive scale. ## From Share Links to Context-Aware Screenshots - Copying a Datadog widget creates a backend record and places a unique share URL on the clipboard. - Pasting the URL into a dashboard or notebook restores the widget. - Slack and Teams integrations can render a live preview linking back to Graph Explorer. - Screenshots remain popular because they are quick, intuitive, and visually consistent. - However, screenshots normally lose: - The time range - Underlying queries - Visualization type - Dashboard state - Template variables and other configuration ## Storing a Compact Snapshot Reference - A complete widget definition can be about 2 kB, including queries, display settings, legends, titles, time ranges, dimensions, and deep links. - Encoding all of that directly into an image would be impractical. - Instead, Datadog stores the full definition in Redis and embeds only a randomly generated snapshot ID in the screenshot. - Snapshot records are retained for one hour because screenshots are typically pasted within seconds or minutes. - The frontend generates IDs optimistically so watermarks appear immediately, before the backend cache operation completes. - Redis keys include the organization ID, preventing collisions between different customers. - An 8-byte identifier provides roughly 2⁶⁴ possible values; under the stated traffic assumptions, the estimated collision risk is about one in 37 million. ## Encoding Data in Widget Borders - Every dashboard widget has a uniform, 1-pixel border, making it a reliable place to add metadata without visualization-specific code. - An initial design used individual pixels with two colors to represent bits, but encoding 64 bits would require at least 64 pixels and could become visible. - The chosen approach stores multiple bits in each pixel’s RGB channels. - Each color channel is offset from the base border color by up to seven values, allowing up to nine bits per pixel. - Two sentinel pixels, encoded with maximum RGB offsets, mark the beginning and end of the watermark. - Because the encoded pixels remain close to the border’s original color, the watermark is intended to remain imperceptible while remaining recoverable by software. ## Scaling and Collision Considerations - Datadog renders more than one billion widgets per day, with peaks of roughly 35,000 widgets per second. - The watermark design therefore has to minimize payload size while supporting high throughput. - Shorter identifiers are easier to hide but increase collision risk, requiring organization-scoped keys and carefully chosen identifier sizes. Datadog’s design uses screenshots as lightweight carriers for references rather than embedding complete widget data. By combining subtle border-based pixel encoding with short-lived Redis snapshots, screenshots can potentially regain the contextual and interactive benefits of share links without changing their appearance.

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datadog3 min readCurated summary

Engineering spotlight: Marie-Laure Bardonnet

Marie-Laure Bardonnet’s Datadog career illustrates how engineers can grow through both technical and management paths. After working on Dashboards and Notebooks, she moved into distributed backend systems, eventually leading Datadog’s Logs engineering organization. Her approach emphasizes engineering-informed leadership, deliberate career planning, mentorship, and embracing unfamiliar challenges. ## From Web Engineering to Logs Leadership - Bardonnet joined Datadog full-time in 2017 after interning there. - She began on the Paris-based Dashboards team, where she helped: - Launch the Notebooks product. - Build the backend for a responsive Dashboard layout. - Encouraged by her manager, she transitioned into backend engineering and joined the Logs team. - Logs engineering involved real-time ingestion, processing, enrichment, storage, and querying of millions of log payloads daily. - As Datadog’s products developed shared technical requirements, Logs engineers collaborated closely with a centralized Platform team. - After one year as an individual contributor, Bardonnet became a team lead and later advanced to Engineering Manager II, overseeing both backend and frontend Logs teams. ## Balancing Product Delivery and Technical Health - Her role combines strategic planning, technical decision-making, people development, and recruiting. - At the start of each quarter, teams create OKRs that guide product and technical roadmaps. - Managers balance product priorities with: - Reliability and scalability. - Technical debt reduction. - Cross-team dependencies. - Bardonnet reviews RFCs, incident postmortems, and product documentation to help teams make sound decisions. - She supports both individual contributors and managers by identifying projects that build expertise and leadership skills. - She also participates in weekly hiring committees to recommend candidates and maintain consistent leveling. ## Structuring Teams for Future Growth - As organizations expand, Bardonnet focuses on restructuring teams to improve execution and create better growth opportunities. - Two questions guide this process: - What problems will the organization need to solve about a year from now? - How can everyone progress toward their next career step? - Logs leadership works with Product Management on a three-horizons plan to align future investments with customer needs. - Team design also considers whether each person has appropriately scoped work, meaningful challenges, and sufficient mentorship. ## Building a Self-Directed Career Path - Career planning begins by separating current responsibilities from the work someone ultimately wants to do. - Engineers should reflect on: - What work brings them satisfaction. - What they do well. - What they want to learn. - What legacy they want to leave. - Career goals should be reviewed continuously, organized across different planning horizons, and discussed with leaders. - A strong career path balances personal interests, strengths, learning opportunities, team needs, organizational priorities, and feedback. - Career direction is self-driven and may change over time, but managers and organizational leaders can help identify opportunities and create a suitable path. ## Growth Through Uncertainty - Datadog’s expanding platform and variety of engineering teams mean that career paths differ widely between employees. - Progression may be nonlinear and can require taking risks or accepting unfamiliar challenges. - Growth comes from leaving one’s comfort zone and learning through difficult problems. - Peer feedback helps employees assess whether they are progressing and feel supported. - Regardless of role or trajectory, employees contribute to Datadog’s culture by modeling high standards for quality and delivery. Bardonnet’s experience suggests that career growth is most effective when employees take ownership of their direction while seeking feedback, mentorship, and challenging opportunities from their organization.

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