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DASH Livestream Replays

DASH Livestream Replays

Keynote

On-demand

New Launches

Bits for SRE

Bits Detection

Bits Detection is your always-on production monitoring system that autonomously identifies what’s unhealthy and when it matters as your systems change. Using real-time telemetry, historical baselines, service topology, ownership, and source code context, Bits continuously monitors critical areas of production and surfaces impactful alerts. Fully integrated into the Datadog platform, Bits helps teams keep monitoring aligned with fast-moving systems without manually defining every condition up front.

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Bits for SRE

Bits Memories

Bits gets more useful the more it knows about your environment. With Memories, Bits learns the operational context your team builds up over time: the hard-won lessons live telemetry alone can't surface. It can then apply that knowledge whenever it's relevant, adding a deeper layer of context across all of its work.

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Bits for SRE

Bits Remediation

Bits Remediation: Bits doesn't stop at detecting issues and finding the root cause. It helps you resolve them. Bits can act on its findings across your services and infrastructure by calling APIs, running fully configured scripts, and opening code fixes as pull requests, all within the guardrails your team defines.

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Bits for SRE

Bits Infrastructure Operations

Bits Infrastructure Operations acts as your autonomous platform engineer that detects, investigates, and remediates common infrastructure issues, such as OOMKilled pods, expiring TLS certificates, and Lambda concurrency limits, before they escalate into incidents. Bits acts safely within the new Bits Guardrails you define: autonomously resolving issues when permitted, surfacing the rest for review and user approval with full context, and learning from every approved change to expand what it can resolve on its own.

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Infrastructure Monitoring

Network Monitoring

Datadog's end-to-end Network Monitoring suite gives every engineer the visibility they need to detect and resolve issues across the full stack. Datadog correlates network, application, and infrastructure telemetry in real time, pinpointing the exact source of latency, congestion, or configuration-related issues hop-by-hop. Teams remediate issues directly within the platform and roll back on-premises devices to their last known good configuration with a single click. With Bits AI, anyone can pinpoint the root cause of complex network behavior in plain language—no networking expertise required.

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Database Monitoring

Bits Database Optimization

Database Optimization gives users automated remediation out of the box. When Database Optimization identifies a query worth optimizing, it generates a concrete fix, validates it empirically against a simulated copy of the customer's schema, and delivers a ready-to-merge pull request on the exact line of code that issued the query. The fix arrives with benchmark evidence embedded, so the reviewer can ship it without leaving their normal workflow. This is not a recommendation to consider, it is a validated change, ready to apply.

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Log Management

Federated Logs

Federated Logs allows customers to query logs in third-party data lakes without moving the data or duplicating it across systems. Teams can now search logs in Databricks from the Datadog Log Explorer, allowing observability and business teams to work from shared context.

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Log Management

BYOC Logs

Datadog Bring Your Own Cloud (BYOC) Logs lets you keep your logs in your own environment while using the Datadog platform for querying, analytics, and investigations. Built for modern AI applications, AI labs, and large-scale data environments, it runs a high-performance, petabyte-scale log engine in your infrastructure, giving you full control over costs, scale, and compliance.

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Digital Experience Monitoring

Journey Monitoring

Journey Monitoring gives engineering, product, and DevOps a single shared view of every critical user journey -- combining traffic, conversion rates, uptime, and errors from Real User Monitoring, Synthetic Monitoring & Testing, and Product Analytics. Every team now has a shared understanding of a journey's performance and can pinpoint exactly whether a drop-off is a technical issue or a behavioral one.

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Bits for Developers

Bits Release

Bits Release is an AI release validation agent that verifies every code change from pull request to production. When a PR is opened, Bits Release analyzes the intended impact of the change, generates a validation plan, runs end-to-end checks in staging, and monitors the production rollout.

Unlike traditional monitoring, Bits Release validates releases in context: it verifies that the expected improvements actually happen while detecting regressions and unintended side effects. When issues occur, it investigates likely root causes and helps generate fixes. Successful validations can be promoted into persistent production monitors, creating a continuous safety loop for high-velocity and AI-generated code.

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Bits for Developers

Bits Testing

Bits Testing is an agent that automatically discovers the user journeys that drive your business and generates self-healing synthetic tests to verify them. It frees teams to ship faster by handling journey discovery and test coverage automatically, no manual scripting required. Unlike tools that require you to prompt the agent on what to test and iterate until it learns, Bits prioritizes critical journeys on its own. And rather than dropping a handful of tests on your lap, it generates end-to-end suites that translate directly into measurable reliability outcomes.

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Bits for Developers

Bits Code

Bits Code is an always-on developer teammate that resolves production issues in code, so engineers can stay focused on shipping features. Powered by Datadog's observability data and built for complex production environments, it picks up the signals surfaced across the platform, investigates them with full production context, and writes production-ready code fixes complete with unit tests. Bits Code closes the loop between finding a problem and fixing it, handling the work an engineer would otherwise do by hand: triaging the signal, locating the offending code, writing the fix, running tests, and opening a pull request for review. Turn signals from products like Error Tracking, APM Recommendations, Continuous Profiler, Test Optimization, Code Security, and Bits Investigations into validated code changes ready for human review, accelerating remediation across Datadog.

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Data Observability

Data Observability

Data Observability helps data and product teams improve the reliability of data for analytics and AI applications and optimize the performance and costs of data pipelines. By unifying quality and jobs monitoring from production to consumption, teams can detect and remediate issues faster while optimizing cost and performance.

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Bits Data Analysis

Bits Data Analysis

Bits Data Analysis, now in Preview, gets teams answers to business questions that are fast and reliable using curated context from across your business.

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Agent Observability

Agent Console

Agent Console acts as your unified view across every AI agent in your organization, including coding agents like Claude Code, Cursor, and GitHub Copilot, plus Datadog's own Bits AI Agents, all in one place. Fully integrated into the Datadog platform, Agent Console attributes spend by agent, team, and user, measures agent impact against non-AI baselines, and suggests fixes to specific waste patterns draining your budget. With one unified view, engineering and business leaders can turn AI agents from an unmanaged line item into a measurable engineering advantage.

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Agent Observability

Agent Observability

With Agent Observability (previously LLM Observability), teams can now automatically surface recurring failure modes in production with Patterns, which clusters traces by behavior, cost, and quality signals. Bits Eval then takes the next step: it investigates any cluster of traces against your code, experiments and datasets to pinpoint root cause and propose targeted fixes, evaluators, and dataset additions. Together, they close the loop from production signal to offline experiment, so AI engineers spend less time triaging and more time shipping improvements with confidence.

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AI Guard

Custom Agent Security Guardrails

AI Guard helps secure homegrown agents from prompt injection, tool misuse, data exfiltration, and other OWASP Top 10 threats. It discovers unprotected agents in your environment, analyzes behavior and historical context, and blocks attacks at runtime. AI Guard sits directly inline with your agents to provide real-time guardrails, so you can ship AI fast without compromising security.

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AI Guard

Coding Agent Security Guardrails

AI Guard helps secure coding agents in developer workflows against prompt injection, backdoor attacks, and other core OWASP Top 10 threats. It detects and blocks malicious skills and scripts directly inline with the coding agent. Integrate real-time AI security guardrails in your developer environments, so you can ship AI fast without compromising security. Support for Claude Code is in Preview, with Codex, Cursor, Github Copilot to follow.

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Cloud Security

Runtime Prioritization Engine

The Datadog Runtime Prioritization Engine helps security and engineering teams focus on the ~5% findings that present the highest operational risk by using real-time observability and security telemetry. The engine identifies findings that are running, reachable, exploitable, and tied to business-critical services without relying on stale tags or manual ownership mapping.

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Security

AI-native SAST

Detect OWASP Top 10 code vulnerabilities with high-accuracy LLM-based analysis.

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Security

Code Threat Detection

Detect malicious changes to your source code repositories and prevent supply chain compromises.

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Bits for Security

Bits Threat Hunting

Bits Threat Hunting is an autonomous agent that runs hypothesis-driven threat hunts across your environment. It reasons with your telemetry—logs, network flows, identity events, and endpoint activity—to determine whether your organization may be impacted by known attacker behaviors, emerging threat campaigns, or unusual deviations from baseline activity. It surfaces affected assets, users, and indicators of compromise (IoCs), helping analysts quickly answer "Are we impacted?" and investigate potential threats before detection rules fire. It can also recommend and deploy detection rules for newly identified IoCs and tactics, techniques, and procedures (TTPs) based on its threat intelligence and hunt findings.

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Bits for Security

Bits Security Analyst

Bits Security Analyst is an always-on SOC analyst built to investigate complex threats and triage security alerts. It autonomously investigates alerts and creates actionable reports in minutes, following security investigation best practices. SOC teams can spend less time on false positives and benign activities and focus on real threats. Bits Security Analyst is now available as a standalone solution that you can deploy in popular SIEMs—including Splunk and Microsoft Sentinel—in minutes. Bits Security Analyst delivers value from day one without disrupting existing workflows

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AI in the Making

On-demand

Breakout 1 Agenda

The New Shape of Engineering

01:00 PM - 01:40 PM

AI’s ability to write code made huge strides over the past year. Today, coding agents aren’t just assisting developers; they are winning the "coding race" by orders of magnitude and fundamentally changing the way engineers work.

 

In this fireside chat, Datadog CTO Alexis Lê-Quôc will host Thibault Sottiaux, OpenAI Engineering Lead for Codex. They’ll give you a peek inside Codex and discuss its background, the challenges that the team at OpenAI faced, and the importance of data in powering AI agents. They’ll also examine how coding agents are changing the shape of software engineering and what this means for you and the engineering teams you work with.

 

Session Speakers

Alexis Lê-Quôc

CTO & Co-Founder Datadog

Thibault Sottiaux

Head of Product and Platform OpenAI

Fireside Chat with Datadog Co-Founder and CEO Olivier Pomel and Hugging Face Co-Founder and CEO Clément Delangue

01:50 PM - 02:30 PM

In the same way that open source radically changed how software is developed, openly shared Machine Learning models have fueled the rapid growth of AI. Join Datadog co-founder and CEO Olivier Pomel as he hosts Clément Delangue, co-founder and CEO of Hugging Face, the leading open source platform and hub for sharing models and datasets. They’ll discuss how AI is evolving, how organizations are responding, and what this means for you and your engineering team.

This session will be part of our livestream programming.

 

Session Speakers

Clément Delangue

CEO & Co-Founder Hugging Face

Olivier Pomel

CEO & Co-Founder Datadog

Progressing AI Beyond Scaling and Into Deep Reasoning

02:50 PM - 03:30 PM

The breakthroughs in AI today aren’t just coming from bigger datasets and more compute; Reinforcement Learning (RL) has quietly become one of the most powerful forces in modern AI development. RL is teaching models to reason and self-correct, enabling capabilities that make AGI feel less like science fiction and more like an inevitable future.

 

In this fireside chat, Datadog Chief Scientist Ameet Talwalkar and Sholto Douglas of Anthropic will discuss the rise of RL-based post-training and its role in making the case for imminent AGI. They’ll look at the technical signals currently pointing toward general intelligence and the obstacles that could still derail it. The conversation will also examine the tension between specialized and generalized models, how they’re being used to build products today, and their implications on future intelligence. Join them as they explore what today's choices in AI research and product development mean for the intelligence of tomorrow.

 

This session will be part of our livestream programming

Session Speakers

Sholto Douglas

Member of Technical Staff Anthropic

Ameet Talwalkar

Chief Scientist Datadog

Fireside Chat with Datadog CPO Yanbing Li and Vercel CPO Tom Occhino

03:40 PM - 04:20 PM

The way we build, ship, and run software is being reshaped by AI. In this fireside chat, Yanbing Li (CPO, Datadog) and Tom Occhino (CPO, Vercel) will discuss their perspectives on the impact AI is having across the industry and what it means for teams navigating this shift today.

Session Speakers

Yanbing Li

Chief Product Officer Datadog

Tom Occhino

Chief Product Officer Vercel

Inside Modern Engineering

On-demand

Breakout 2 Agenda

From Alerts to Autonomy: Scaling Incident Management at PUBG with Automation and AI

01:00 PM - 01:40 PM

Modern game platforms operate across regions, cloud providers, and highly dynamic workloads. At Krafton (maker of PUBG: Battlegrounds), fast-moving teams building player-facing and backend systems faced a key challenge: speed without autonomy creates friction, but autonomy without guardrails creates risk.

Junghun Kim, Lead of the DevOps Team at Krafton, will share how his team transformed incident management from a centralized SRE function into a developer-centric platform powered by Datadog. By combining unified observability, high-signal monitors, and integrated workflows across Datadog Incident Management, On-Call, and Slack, teams can now detect, declare, and respond to incidents with greater ownership.

He will explore how automation and AI reduce cognitive load during incidents, from automatically creating context-rich Slack war rooms, to enforcing safeguards such as scale-in prevention, capturing response and change context in the incident timeline, and assisting with postmortem reviews.

Through a representative incident-response walkthrough, attendees will gain a practical blueprint for building an incident response model that increases ownership, reduces alert fatigue, and enables faster detection, safer mitigation, and streamlined postmortems.

This session will be part of our livestream programming.

Session Speakers

Junghun Kim

DevOps Engineer Krafton Inc.

Stop Ingesting Noise or How I Learned to Stop Worrying and Love Observability Pipelines

01:50 PM - 02:30 PM

Ingesting everything isn't a strategy, it's a bill that keeps growing, dashboards nobody trusts, and a compliance posture that's one audit away from a very bad week.

Bryan Pierson from Enterprise Observability Engineering at US Bank will share how his team moved from ingesting everything-just-in-case to running a deliberate, multi-destination observability pipeline that actually reflects what the business cares about. He'll walk through how Datadog Observability Pipelines became the foundation for something more than log forwarding but a platform for filtering noise before it hits ingest, sampling high-volume low-value sources, scrubbing sensitive data at the edge, and routing logs to the right destination for the right reason.

He'll also cover the piece most teams skip: accountability. A custom quota program tied directly to the pipeline gives every application team a log budget based on resiliency tier with automated enforcement that scales from a friendly incident at 80% all the way to disabled log flow at 120%.

The result? Teams that care about what they log. Costs that behave. And an observability practice that stopped worrying and started working.

You will leave with practical routing strategies, a framework for log accountability, and at tangible ideas they can implement before the week is out.

This session will be part of our livestream programming.

Session Speakers

Bryan Pierson

Vice President, Enterprise Observability Engineering U.S. Bank

How Coding Agents are Changing the Traditional Software Development Lifecycle

02:50 PM - 03:30 PM

AI coding assistants are rapidly evolving from passive copilots into active, agentic collaborators capable of planning, executing, and iterating on complex software tasks. This shift has huge ramifications onthe software development lifecycle (SDLC), developer productivity, and even the structure of engineering teams.

In this panel, we chat with AI early adopters who tackled those challenges and ultimately saw opportunities to solve them. Join the founders of Greptile, Warp.dev, and Opencode as they explore how agentic systems are redefining how code is written, reviewed, debugged, and deployed. Drawing from their work at the frontier of developer tooling, they’ll discuss the emergence of autonomous workflows, the changing role of developers as orchestrators rather than implementers, and the infrastructure required to support reliable, secure AI-driven development.

Topics will include:

  • How agentic coding systems are transforming each stage of the SDLC
  • The evolution from IDEs to AI-native development environments
  • Trust, verification, and observability in autonomous code generation
  • The future role of developers in an increasingly automated stack

Expect a forward-looking conversation grounded in real-world product engineering, with candid perspectives on what’s hype, what’s working today, and what still needs to be built.

This session will be part of our livestream programming.

Session Speakers

Clémence Burnichon

Senior Engineering Director Datadog

Daksh Gupta

CEO Greptile

Zach Lloyd

CEO Warp

Sesh Nalla

Vice President, Engineering Datadog

Jay V

CEO OpenCode

Building a Proactive Incident Management Practice at Swish

03:40 PM - 04:20 PM

Swish isn't just an app in Sweden, it's a verb. When "swisha"—meaning “to pay with Swish”—entered the official Swedish dictionary in 2015, it marked the moment Swish became part of everyday language and life. Today, millions rely on it, which means that when something goes wrong, everyone notices.

At that scale, incidents don't stay internal. They unfold in real time, in the hands of users, across the entire country. The pressure isn't just to fix the problem, but to understand it, communicate it, and restore trust, fast.

In this session, Nicole Johnsson (Platform Engineer) and Jonas Cronholm-Lundin (Head of Platform) take you behind the scenes of how Swish transformed their incident management approach from reactive firefighting to a proactive, resilient practice. They’ll share how they introduced stronger engineering foundations like GitOps, SRE, and end-to-end observability to surface better signals during incidents and releases. You'll also see how they designed runbooks around the OODA loop—Observe, Orient, Decide, Act—and combined them with automation to create consistency, while still empowering developers to explore, diagnose, and resolve issues independently.

You'll leave with practical, battle-tested ideas for reducing MTTD, improving incident response, and building a culture that can handle the spotlight—protecting both customer experience and brand trust when it matters most.

This session will be part of our livestream programming.

Session Speakers

Jonas Cronholm-Lundin

Head of Platform Getswish AB

Nicole Johnsson

Platform Engineer Getswish AB

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