Datadog Developers retweeted
.@datadoghq gives JavaScript teams full visibility into real user sessions, Core Web Vitals, and frontend errors, all connected to backend traces. Platinum sponsor of JSNation US.
Start free: datadoghq.com/free-datadog-t…
Start free: datadoghq.com/free-datadog-t…
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Datadog Developers retweeted
We are happy to announce our first Compute Speaker, Olivier Pomel, CEO & Co-founder at @datadoghq
Announcing first Compute 2027 speaker: @oliveur, Co-founder & CEO of @datadoghq!
From co-creating VLC media player to building Datadog into a global leader in observability, Olivier knows what it takes to build technology at scale.
See you at Chase Center, SF, February 3–4, 2027ticket here:
luma.com/daytona-compute
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Are you evaluating your AI agents against what users actually do in production?
Datadog Patterns helps uncover gaps in your evaluation datasets and recommends real production traces to improve coverage.
watch Patterns IRL 👇
read the @datadoghq docs: datadoghq.com/blog/patterns-…
Datadog Patterns helps uncover gaps in your evaluation datasets and recommends real production traces to improve coverage.
watch Patterns IRL 👇
read the @datadoghq docs: datadoghq.com/blog/patterns-…
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Datadog Developers retweeted
Excited to announce the AWS EC2 Spot Assessment Tool! This was one of the larger projects I worked on at @datadoghq!! Makes it super easy to scan all your ASGs and see cost savings and spot potential.
looking to work with customers in our preview! Sign up below!!
looking to work with customers in our preview! Sign up below!!
While there is an ongoing compute shortage, you can still save some money using AWS Spot Instances!
Now Datadog can score your ASGs by interruption risk and cost savings, and even help you pick available instance types in your region/AZs
sign up today!
datadoghq.com/product-previe…
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Datadog Developers retweeted
While there is an ongoing compute shortage, you can still save some money using AWS Spot Instances!
Now Datadog can score your ASGs by interruption risk and cost savings, and even help you pick available instance types in your region/AZs
sign up today!
datadoghq.com/product-previe…
Now Datadog can score your ASGs by interruption risk and cost savings, and even help you pick available instance types in your region/AZs
sign up today!
datadoghq.com/product-previe…
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Datadog Developers retweeted
now that I'm no longer on the dataviz team, I can properly glaze them while feeling unbiased...like how pretty is our new heatgrid widget 🤩🌅!!!
Claude connects automatically. Production investigations go multiplayer. Mobile profiling gets down to the CPU method.
And that’s just the beginning of what shipped this week at @datadoghq Here's the full rundown👇
- Connecting an AI client to a tool usually means everyone authorizing separately, every time. Datadog auto-connect for @claudeai (beta) fixes that: admins configure once, teammates connect automatically, no sign-in screens, no identity provider needed.
- Datadog Canvas (Preview) turns production investigations multiplayer: explore, investigate, and keep evidence connected on one shared view with teammates and AI agents.
- Datadog Agent Observability is now live on the Claude Marketplace, with Datadog as a featured launch partner.
- 3 platforms RUM couldn't fully see before now have official SDKs: C/C++, Electron, and .NET MAUI.
- Time to Initial Display tells you a launch is slow. It doesn't tell you why. RUM Mobile Profiling attaches CPU profiles from real iOS/Android sessions so you can see which methods consumed CPU time.
- A lineage graph is only as strong as its weakest link, usually a custom script nobody instrumented. OpenLineage support in Jobs Monitoring closes that gap for any data processing job.
-Comparing 10+ services in a timeseries chart gets crowded fast. The new Heatgrid widget makes that comparison legible in dashboards and notebooks.
- Your dashboards just got more room to breathe: iPhone Duo support for Datadog Mobile. Unfold for expanded dashboards and incident timelines, fold to pick up where you left off.
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Datadog Developers retweeted
A full year of Datadog Pro, up to $100,000 in credits. No cut-down tier — the whole platform.
@datadoghq for Startups 👇
- Series A or earlier, new to Datadog
- Must come through a referral partner
- Apply online, hear back in a few days
Link below 👇
@datadoghq for Startups 👇
- Series A or earlier, new to Datadog
- Must come through a referral partner
- Apply online, hear back in a few days
Link below 👇
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Claude connects automatically. Production investigations go multiplayer. Mobile profiling gets down to the CPU method.
And that’s just the beginning of what shipped this week at @datadoghq Here's the full rundown👇
- Connecting an AI client to a tool usually means everyone authorizing separately, every time. Datadog auto-connect for @claudeai (beta) fixes that: admins configure once, teammates connect automatically, no sign-in screens, no identity provider needed.
- Datadog Canvas (Preview) turns production investigations multiplayer: explore, investigate, and keep evidence connected on one shared view with teammates and AI agents.
- Datadog Agent Observability is now live on the Claude Marketplace, with Datadog as a featured launch partner.
- 3 platforms RUM couldn't fully see before now have official SDKs: C/C++, Electron, and .NET MAUI.
- Time to Initial Display tells you a launch is slow. It doesn't tell you why. RUM Mobile Profiling attaches CPU profiles from real iOS/Android sessions so you can see which methods consumed CPU time.
- A lineage graph is only as strong as its weakest link, usually a custom script nobody instrumented. OpenLineage support in Jobs Monitoring closes that gap for any data processing job.
-Comparing 10+ services in a timeseries chart gets crowded fast. The new Heatgrid widget makes that comparison legible in dashboards and notebooks.
- Your dashboards just got more room to breathe: iPhone Duo support for Datadog Mobile. Unfold for expanded dashboards and incident timelines, fold to pick up where you left off.
And that’s just the beginning of what shipped this week at @datadoghq Here's the full rundown👇
- Connecting an AI client to a tool usually means everyone authorizing separately, every time. Datadog auto-connect for @claudeai (beta) fixes that: admins configure once, teammates connect automatically, no sign-in screens, no identity provider needed.
- Datadog Canvas (Preview) turns production investigations multiplayer: explore, investigate, and keep evidence connected on one shared view with teammates and AI agents.
- Datadog Agent Observability is now live on the Claude Marketplace, with Datadog as a featured launch partner.
- 3 platforms RUM couldn't fully see before now have official SDKs: C/C++, Electron, and .NET MAUI.
- Time to Initial Display tells you a launch is slow. It doesn't tell you why. RUM Mobile Profiling attaches CPU profiles from real iOS/Android sessions so you can see which methods consumed CPU time.
- A lineage graph is only as strong as its weakest link, usually a custom script nobody instrumented. OpenLineage support in Jobs Monitoring closes that gap for any data processing job.
-Comparing 10+ services in a timeseries chart gets crowded fast. The new Heatgrid widget makes that comparison legible in dashboards and notebooks.
- Your dashboards just got more room to breathe: iPhone Duo support for Datadog Mobile. Unfold for expanded dashboards and incident timelines, fold to pick up where you left off.
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Datadog Developers retweeted
Had a great time on the pod, thanks for having us @meganreyno
My timeline is full of RL. RL environments, RL gyms, data labeling companies. Startups scaling to $1B in revenue in months. What is going on?
Post-training seems like the new frontier. Reinforcement learning is the emerging preferred method, with an ecosystem worth $Bs growing s it work? And how much does it really add to good pre-training?
On Ep 3 of Technically Speaking from @readtechnically, a rare conversation from both sides of the RL stack:
@slippylolo (co-founder & CEO of Adaptive ML, now at @datadoghq ) and @nerdsane (Datadog):
→ Why a monitoring company bought an RL startup: "At its heart, this is an observability problem."
→ Whether your startup should train its own model: "for 99% of people it doesn't make any sense to do that"
→ Creating synthetic training data: "You cannot create data ex nihilo and hope for the best."
→ What actually makes for great post-training: "it's mostly a question of high quality execution"
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We used an AI agent to debug itself.
Datadog Insights in AgentObs found 80K unnecessary tokens, broken tool calls, and $2.7K/month in potential savings.
Then we used Bits to turn a finding into a PR.
See how we closed the loop:
datadoghq.com/blog/improving…
@RashelHoover @datadoghq
Datadog Insights in AgentObs found 80K unnecessary tokens, broken tool calls, and $2.7K/month in potential savings.
Then we used Bits to turn a finding into a PR.
See how we closed the loop:
datadoghq.com/blog/improving…
@RashelHoover @datadoghq
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Datadog Developers retweeted
My timeline is full of RL. RL environments, RL gyms, data labeling companies. Startups scaling to $1B in revenue in months. What is going on?
Post-training seems like the new frontier. Reinforcement learning is the emerging preferred method, with an ecosystem worth $Bs growing s it work? And how much does it really add to good pre-training?
On Ep 3 of Technically Speaking from @readtechnically, a rare conversation from both sides of the RL stack:
@slippylolo (co-founder & CEO of Adaptive ML, now at @datadoghq ) and @nerdsane (Datadog):
→ Why a monitoring company bought an RL startup: "At its heart, this is an observability problem."
→ Whether your startup should train its own model: "for 99% of people it doesn't make any sense to do that"
→ Creating synthetic training data: "You cannot create data ex nihilo and hope for the best."
→ What actually makes for great post-training: "it's mostly a question of high quality execution"
Post-training seems like the new frontier. Reinforcement learning is the emerging preferred method, with an ecosystem worth $Bs growing s it work? And how much does it really add to good pre-training?
On Ep 3 of Technically Speaking from @readtechnically, a rare conversation from both sides of the RL stack:
@slippylolo (co-founder & CEO of Adaptive ML, now at @datadoghq ) and @nerdsane (Datadog):
→ Why a monitoring company bought an RL startup: "At its heart, this is an observability problem."
→ Whether your startup should train its own model: "for 99% of people it doesn't make any sense to do that"
→ Creating synthetic training data: "You cannot create data ex nihilo and hope for the best."
→ What actually makes for great post-training: "it's mostly a question of high quality execution"
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Datadog Developers retweeted
such an epic talk.. wish the lighting was a bit better..
enjoyed being in the room and experiencing @bcantrill’s “reality distortion field”.. thanks for hosting @datadoghq and @rust_nyc
enjoyed being in the room and experiencing @bcantrill’s “reality distortion field”.. thanks for hosting @datadoghq and @rust_nyc
Video for my @rust_nyc talk, "Code Matters: Reflections on Rust in the LLM Age", is now up:
youtube.com/watch?v=5D7QPO…
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Your dashboards just got more room to breathe.
Datadog Mobile now supports iPhone Duo.
Unfold for expanded dashboards, monitors, and incident timelines. Fold to pick up where you left off.
Same telemetry, more screen. Get the latest @datadoghq version: apps.apple.com/app/datadog/id…
Datadog Mobile now supports iPhone Duo.
Unfold for expanded dashboards, monitors, and incident timelines. Fold to pick up where you left off.
Same telemetry, more screen. Get the latest @datadoghq version: apps.apple.com/app/datadog/id…
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Datadog Developers retweeted
Offline evals catch the regressions you already know about but Production stresses your agent beyond what you know in a dataset. Run controlled A/B tests of agent versions on live traffic. Test and learn quickly in prod.
datadoghq.com/blog/online-ex…
datadoghq.com/blog/online-ex…
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