Jeremy

Founder of VP Open Source and Technical Community @datadoghq, CNCF Board, Linux Fund, ardent but realistic open source advocate.

[Datadog Developers @datadogdevs]

We make ship happen - shipped this week at Datadog 🚀

- Every time an agent wants to reach Datadog, a user clicks through a consent screen, with no central record of what got approved. Cross-App Access (XAA) fixes that: admins grant and revoke AI agent access to Datadog from the Okta Admin Console, one place, no per-user consent screens.

- AI agents can now configure and maintain log pipelines, indexes, and archives with Datadog MCP.

- Skills Library lets you teach your agents how your team works, once, then reuse that knowledge across Bits Chat and Bits Agent Builder.

- Prompts used to be hardcoded or scattered across code and notebooks, with no single source of truth for what's actually running. Prompt Management for Agent Observability fixes that, author, version, and deploy prompts with no app redeploy. @kaixin_tai

- Running your own OpenTelemetry Collector no longer means losing Datadog's APM, logs, and metrics. The OTLP Native Processing Pipeline is live now.

- RUM Exclusion Filters let you define noise exclusions once instead of repeating them in every retention filter.

- Debugging an API failure in a Browser Test used to mean reproducing it elsewhere just to see what was sent. Now you can capture network payloads directly in the test result.

- We're now an initial member of the newly launched BUILD Foundation, investing in the Bazel ecosystem alongside ASML, @canva, @engflow, @figma, and @Spotify. @datadoghq

[Othmane @ThisIsOthmane]

Exciting news from Datadog AI Research: we trained a model to investigate production incidents, and it matches the best frontier models at a fraction of the cost.

Introducing Scout 1.0, the model powering Bits Investigation, our AI SRE.

On AlertEval, our benchmark of real production alerts:

- Scout 1.0 medium matches Claude Opus 5.5 high and GPT-6.1 Sol high at 3-8x lower cost
- It also performs comparably to Claude Fable 5.1 medium and GPT-6 Astra medium at 12x and 19x lower cost
- Scout 1.0 xhigh matches Claude Fable 5.1 xhigh at 4x lower cost

[Datadog, Inc. @datadoghq]

Meet Scout 1.0, our first AI model built for investigating production incidents.

Scout matches frontier-model investigation quality at a fraction of the cost, which makes it practical to investigate more issues, earlier.

We trained Scout on realistic simulations built from real-world incidents and production telemetry, using reinforcement learning to reward accurate root causes backed by evidence.

Learn more and sign up for the preview: https://t.co/FYd1TVgCXE

[/sesh/null @nerdsane]

Strongly agree. Agents amplify whatever primitives they build on, good or bad.

Our systems research team at @datadog is building Temper: a higher level of abstraction for software that agents build and operate, made from boring, well-understood primitives.
(1) OData for self-describing APIs with typed entities and relationships
(2) I/O automata for behavior
(3) Actor model for execution
(4) Cedar for policy
(5) Wasm for safe code sandboxing
(6) rust as the language

None of these are new, and that’s the point. Composing them lets you describe/specify an application succinctly as entities, state machines, and policies, instead of as the glue code between them. That description is small and precise enough to formally verify (SMT solvers, model checkers, theorem provers), and the runtime is tested under deterministic simulation.

An agent can propose any change. A state change only lands if it passes the spec and the policy.

https://t.co/cXWpzEMuPL

[OpenCode @opencode]

If you're using OpenCode Server there is a code execution vulnerability impacting versions 1.14.30 through 1.18.21 please update to latest

Thanks to @christophetd and the Datadog team for reporting

https://t.co/bK7PJiLUOM

[Ram @ramxcodes]

morning banger read by @datadoghq

Hats off to the engineering they are doing. It is something I love to read.

You can't imagine how good engineering it is until you have felt the pain of long-running CI.

And of course never thought `git fetch` or `git clone` going to be bottlenecks in the process.

https://t.co/VyAGyKjkj9

[Gergely Orosz @GergelyOrosz]

This is the thing with internal tools: over time, they almost always become subpar vs a tool a vendor builds

At Large Company that have their own, custom o11y, talked with an eng... who said how much they'd love to use Datadog (or similar) because that would "just" work instead of "kind of" work

[Grok @grok]

@BelieverFomo @techdevnotes Here's the proof from the official sources:

Plugin source: https://t.co/iHfv6Ql6iq

Official xAI marketplace catalog (search for "datadog"): https://t.co/KvrguQfvtX

Description matches the screenshot exactly.

[ClaudeDevs @ClaudeDevs]

Supported by Asana, Atlassian, Canva, Datadog, Figma, Granola, Linear, Notion, Slack, and Supabase.

Developers can also add enterprise-managed auth to their own third-party MCP connectors in the Claude directory.

Blog:
https://t.co/vPhSthb6go

Docs:
https://t.co/XbsRhyXIT5

[wyndo @wyndo_app]

Wyndo now has a live "Paw Check" map. Is it too hot for your pup? Visit https://t.co/HBtinF1hjy to find out.

[clem 🤗 @ClementDelangue]

Going to be in NYC Tuesday for @datadoghq dash. Who should I meet?

[Datadog, Inc. @datadoghq]

The Datadog Ambassadors program has grown into a global community of practitioners sharing what they learn about observability. This week, we've introduced the 2026 cohort, along with a new program: Datadog Champions, recognizing community contributors across 11 countries.

Read more about our ambassadors' contributions: https://t.co/kjExW3AOhG

[Tibo @thsottiaux]

Codex can do incredible things on demand, but it cannot experience life for you.

Don’t forget to get out there and remember who you’re building for.

[AJ Stuyvenberg @astuyve]

The massive growth of Codex isn't just noise on twitter, early data from the Lapdog launch shows a very strong mix of coding agents:

[AJ Stuyvenberg @astuyve]

NEW from Datadog: it's Lapdog!
Ever wondered what your AI agent was actually doing?

Our latest free project runs locally and traces reasoning and tool calls in Codex, Claude Code, and Pi.

You can now see what your agent is REALLY doing, live: https://t.co/3dVBozFlPx

[Gabriel @gabriel_horwitz]

did you know cloudflare encrypts the internet using a wall of lava lamps?

100 of them sit in their SF lobby. a camera films the chaos, the images get hashed, and the result seeds the cryptographic keys for ~20% of global web traffic.

the london office uses a wall of double pendulums.

the austin office uses hanging rainbow mobiles.

the singapore office uses a chunk of uranium in a glass jar.

just in case the lava lamps stop being weird enough.

[Datadog, Inc. @datadoghq]

AI agents are only as good as their context. 🤖

Give your agents secure, real-time access to your Datadog telemetry, monitors, and dashboards with the new Datadog MCP Server! Watch the latest episode of This Month in Datadog to learn how: https://t.co/vcDx6HIngi

[Mitchell Hashimoto @mitchellh]

It isn't unexpected that the focus of the Bun Rust rewrite is on the anti-Zig side more than anything, since the internet loves to hate. What is unexpected and unfortunate is that leadership within Bun hasn't tried to steer the conversation away from that at all.

There are so many positive and interesting takeaways from this and I'm not really seeing any of them pushed as the primary message.

A positive thing that hasn't been talked about at all is how far Bun came thanks to Zig. And even if you dump it now, its meaningful for how good Zig was to even build a product to this point and impact by any metric. I would've loved to see anyone in leadership say this.

On the interesting side is how fungible programming languages are nowadays. Programming languages used to be LOCK IN, and they're increasingly not so. You think the Bun rewrite in Rust is good for Rust? Bun has shown they can be in probably any language they want in roughly a week or two. Rust is expendable. Its useful until its not then it can be thrown out. That's interesting!

There's been a lot of talk about memory safety and no doubt Rust provides more guarantees than Zig. But I'd love to see a better analysis of why Bun in particular suffered so much rather than take the language-blame path. How could engineering as a practice been more rigorous to prevent this? What were the largest sources of crashes other programs should watch out for? How does Rust prevent them? How could Zig theoretically prevent them? That's interesting.

I know the official blog post hasn't come out yet from Bun. But they're smart enough to know that that PR would stir up controversy the moment it opened, or they should've been. And plenty in the company have been tweeting and writing about it. Its somewhat telling to me in various dimensions what they chose to talk about first.

I tend to think I'm pretty good at corporate PR/comms (especially when it comes to developer audiences) and I think appealing to the negative is never the right long term strategy; it does work to get short term eyes though.

[Datadog, Inc. @datadoghq]

Toto 2.0 is here: Datadog AI's 5 open-weights forecasting models (4m-2.5B params) finally make scaling work for time series forecasting! #1 on BOOM, GIFT-Eval, and TIME. Weights/code Apache 2.0.
🔗 Read the blog post for more details: https://t.co/CEQSfUhvOA

[Datadog, Inc. @datadoghq]

🎬 April’s This Month in Datadog is live, and we are showing you how teams are using AI to move faster with better context across their systems.

Want to see what’s next? Join us at DASH for an immersive look at the latest in AI-powered observability and security. Secure your spot: https://t.co/uzSDvzx2WG