Datadog, Inc. ✓

@datadoghq · New York · joined 15 Mar 2010

Datadog is the monitoring and security platform for cloud applications

51 413Followers

65Following

10 673Posts total

7.1KViews on collected posts

Latest posts

Datadog, Inc. ✓@datadoghq8 Sep

When a ransomware crisis hits, you have hours — not days — to detect, respond, and recover. Join CISO Florian Jörgens and Datadog Field CISO Rob Aragao for an interactive tabletop simulation, plus a conversation on how AI-assisted investigation is helping SOC teams close the htt

226 views · 0 likes · 0 reposts · 0 replies Open on X →

Datadog, Inc. ✓@datadoghq4 Sep

@datadoghq Yes, we are building full-stack kernel observability for AI agent sandbox. https://t.co/So2fljhWVT 2 views · 0 likes · 0 reposts · 0 replies Open on X →

Datadog, Inc. ✓@datadoghq3 Sep

Query optimization tools love to tell you a rewrite should be faster. Proving it is the hard part. Bits Database Optimization benchmarks your actual queries against a simulated version of your database, so you get evidence, not estimates. See how we validate every 1.9K views · 7 likes · 0 reposts · 1 replies Open on X →

Datadog, Inc. ✓@datadoghq2 Sep

70%+ of organizations now run three or more models. The share running six or more nearly doubled in a year. And each version can respond differently to the same prompt, tool definition, or guardrail. Here's what we learned monitoring our own agents at Datadog — and why the 1.6K views · 3 likes · 0 reposts · 1 replies Open on X →

Datadog, Inc. ✓@datadoghq27 Aug

@LayerXcom combines application performance and AI workflow observability with Datadog to speed up troubleshooting and confidently scale enterprise AI. The result? ~95% faster LLM provider triage. Check out what other customers are doing with Datadog: https://t.co/4cyq3zipMu ht

1.9K views · 3 likes · 1 reposts · 0 replies Open on X →

Datadog, Inc. ✓@datadoghq27 Aug

Four breakout sessions, four ways to deep dive into the world of AI, observability, and security at #DatadogSummit San Francisco ✨ Hear from... 🟣Ala Shiban on shipping trustworthy AI code https://t.co/Td96m7VCAu

1.5K views · 1 likes · 0 reposts · 1 replies Open on X →

Against accounts of the same size

6 posts from the last 90 days, next to the 10K–100K follower range. ordinary reach for its size, weaker reaction than most.

Median views1 578this account1 018median for 10K–100K

Reach, %3.07%this account3.99%median for 10K–100K

Engagement, %0.17%this account1.55%median for 10K–100K

Metric	This account	Median for 10K–100K	Ratio
Median views per post	1 578	1 018	1.55×
Reach (views ÷ followers)	3.07%	3.99%	0.77×
Engagement rate	0.17%	1.55%	0.11×

Others in this range → Compare with another account → How these benchmarks are built →

Growth & engagement

How the posts we collected actually performed: views and reaction rate post by post, what the audience did with them, and where the follower count goes.

Views per post

1.5K27 Aug

1.9K

1.6K2 Sep

1.9K3 Sep

24 Sep

2268 Sep

Last 6 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.13%27 Aug

0.22%

0.25%2 Sep

0.42%3 Sep

0.00%4 Sep

0.00%8 Sep

Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.55%.

What the audience does

Likes70.0%14 in total

Reposts5.0%1 in total

Replies15.0%3 in total

Bookmarks10.0%2 in total

Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.

The follower curve appears once this account has two daily snapshots — we take one a day, and this one is on its first.