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DevOps on Azure engagement report

@AzureDevOps - 96K followers on X

Measured over 22 original posts from a 30-day window, last computed on August 24, 2026.

Engagement

Middle of its size range
Per follower
0.03%
of 96K followers
Per impression
0.875%
3.3K views on a typical post
Reach
3.40%
of its followers see a post
Typical post
28
interactions (median)
Saved
0.2%
6 bookmarks on a typical post
Posting rate
0.73/day
active 70% of days
Peak time
15:00 UTC
Monday

A typical post picks up 28 interactions against 96K followers, an engagement rate of 0.03%. Measured over 22 original posts, its engagement rate beats 32% of 3,899 tracked accounts of a similar size, which puts it in the middle of its size range rather than at either end. Posts are seen about 3.3K times each, and 0.875% of those impressions turn into an interaction. That is about 3.40% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.73 post a day over the last 30 days, with activity on roughly 70% of days. Most posts go out around 15:00 UTC, and Monday is the busiest day of the week. Of the 22 posts sampled, 100% carry an image or video and 100% link out. The account's strongest tracked post pulled 66 interactions, about 2.4x its own typical post.

Measured over 22 original posts from a 30-day window, last computed on August 24, 2026.

Compared with accounts its own size

DevOps on Azure's engagement rate beats 32% of the tracked X accounts closest to it in follower count (3,899 accounts, accounts of similar size (decile 5 of 10)). A percentile is spread evenly by construction, so 50 really is the middle of that group and 90 really is its top tenth.

On engagement per impression rather than per follower it beats 42% of the same group. When those two numbers disagree, the gap is about how far its posts travel rather than how people react to them.

Where this sits in the catalog

At 0.03%, DevOps on Azure sits above the 25th percentile of the 37,701 accounts in this comparison. That places it in the below the median band, which runs 0.012% to 0.081%.

p100.002%
p250.012%
p50 (median)0.081%
p750.439%
p902.10%
p99156.3%
Engagement rate as a share of followers, across the 37,701 accounts we have scanned enough to measure. The axis is logarithmic, because the top and bottom of this population are about 104,204 times apart and a linear axis would flatten everything below the median into a single point.
Show the percentile table
Engagement rate percentiles
PercentileEngagement rate
10th percentile0.002%
25th percentile0.012%
50th percentile0.081%
75th percentile0.439%
90th percentile2.10%
99th percentile156.3%

This ruler is the whole measured catalog, not a size-matched group: it shows where the raw rate falls across every account we can measure, all of which are large. For a like-for-like comparison, read the size-band percentile above instead. See how the bands are built

Posting timing

This account posts most often around 15:00 UTC, and Monday is its busiest day of the week. The bars below are the catalog-wide pattern, with this account's own busiest slot marked. They do not show how this account performs at each hour: we keep one aggregate per account, not one per hour, so that measurement does not exist in our data.

Engagement by hour posted, UTCTwenty-four bars, one per UTC hour. Each bar shows how posts published in that hour compare with their own authors' median engagement. Bars above the centre line ran higher than the median, bars below ran lower. A marker flags Busiest hour: 15:00 UTC.
0003060912151821
Above the authors' own mediansBelowScale: plus or minus 6%Busiest hour: 15:00 UTC
Show engagement by hour posted, utc as a table
Engagement by hour posted, UTC
Hour (UTC)Vs author medianPosts
00:00 UTC-1%53K
01:00 UTC-2%53K
02:00 UTC-3%52K
03:00 UTC-4%55K
04:00 UTC-6%44K
05:00 UTC-4%43K
06:00 UTC-4%50K
07:00 UTC-5%54K
08:00 UTC-4%63K
09:00 UTC-3%72K
10:00 UTC-2%75K
11:00 UTC-3%81K
12:00 UTC-2%90K
13:00 UTC-2%98K
14:00 UTC-3%101K
15:00 UTC-2%105K
16:00 UTC-4%102K
17:00 UTC-3%95K
18:00 UTC-1%88K
19:00 UTC-2%83K
20:00 UTC-1%77K
21:00 UTC-1%69K
22:00 UTC-2%60K
23:00 UTC-2%53K
Engagement by day of weekSeven bars, one per weekday, Sunday first. Each bar shows how posts published on that day compare with their own authors' median engagement. Bars above the centre line ran higher than the median, bars below ran lower. A marker flags Busiest day: Monday.
SunMonTueWedThuFriSat
Above the authors' own mediansBelowScale: plus or minus 5%Busiest day: Monday
Show engagement by day of week as a table
Engagement by day of week
DayVs author medianPosts
Sunday+5%238K
Monday0%302K
Tuesday-3%302K
Wednesday-1%257K
Thursday-2%250K
Friday-3%259K
Saturday+3%233K
See what moves engagement across the whole catalogWhat counts as a good engagement rate at this size

Best tweets

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    OpenClaw + MCP + Azure Container Apps bring a steady, structured approach to autonomous DevOps. Agents plan, code, test, and deploy from a Teams message — all inside secure microVM sandboxes. A practical pattern for multi‑agent workflows. 👉 https://t.co/FGirQHPDf6 https://t.co/8EUvd2RXcG

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  • Aug 18, 20262.0x their median

    Azure Boards now shows PR status right on work item cards. 🔥 Instant “what’s in review?” clarity without opening the item or switching to Repos. Clean board fans: you can turn it off in settings. 👉 Blog: https://t.co/WD0wS34Cgw https://t.co/8Y1a1HrNy3

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    PAT‑free pipelines 🔐🔥 Azure DevOps now supports Service Connections using Entra workload identities — least‑privilege, no secrets, audit‑logged, cross‑org access. YAML repo resources, REST API calls, AzureCLI@3 Entra auth… all without tokens. 👉 Blog: https://t.co/lvfx9B99Kf https://t.co/MvCKTRbJcq

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  • Jul 13, 20261.6x their median

    ⚙️ MCP tools that run longer than client timeouts? Azure Functions + Durable Functions have your back. ⏳ Long‑running workflows 🔁 Orchestrations + checkpoints 🧩 Async task handles (via MCP Tasks extension) See how to build them 👇 https://t.co/63Gm5R3nNK https://t.co/3rXEdo1wRQ

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  • Aug 12, 2026

    Markdown for Agents is live in public preview. 🎉 • App Service can auto‑convert HTML → Markdown with zero app changes • Cleaner agent input + big token savings (median 97% smaller, ~2ms) • Windows App Service only (for now) 🔗 https://t.co/ab3u6wegqg https://t.co/abd8TxchxU

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  • Aug 13, 2026

    Azure Functions Agents now trace everything automatically. 🤖⚡ Model calls, tools, sub‑agents — all show up in App Insights with zero telemetry code. Even Model Router’s hidden model swaps (gpt‑5‑mini → gpt‑5.4) become visible for free. 👉 Blog: https://t.co/w1RAS7mMbK https://t.co/ou51vVmMap

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  • Aug 20, 2026

    WIQD = one flow for Copilot plugins. 🌀 Scaffold → validate → provision → package → publish → monitor — same verbs, same engine, same contract. LSP diagnostics, JSON outputs, evals, and full agent lifecycle automation baked in! 🔧✨ 👉 Read: https://t.co/ibaIt0nDG3 https://t.co/uRNQfh1mrN

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  • Aug 7, 2026

    ⚡ New in Azure DevOps: Commit Search! 🔍 Find any commit in seconds 🧠 Filter by author, branch, message 🚀 Indexed speed for massive repos 🔗 Works across PRs + pipelines 👉 Blog: https://t.co/LzLFnF0g1I https://t.co/yvx136AH2l

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  • Jul 28, 2026

    💸⚙️ DevOps folks: tokens = cost. Agentic AI can fire off dozens of model calls per task — planning, tools, retries, summarization. FinOps for AI = compression, caching, routing, and metering so frontier models only run when they matter. 📚 Blog: https://t.co/q1fnsULNuL https://t.co/ob5qeG7DCp

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Ranked by total interactions across everything we have tracked for this account, which is a longer history than the 30-day window the rates above use. The multiple compares each post to this account's own median.

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Reading these numbers

A typical post picks up 28 interactions against 96K followers, an engagement rate of 0.03%. Measured over 22 original posts, its engagement rate beats 32% of 3,899 tracked accounts of a similar size, which puts it in the middle of its size range rather than at either end. Posts are seen about 3.3K times each, and 0.875% of those impressions turn into an interaction. That is about 3.40% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.73 post a day over the last 30 days, with activity on roughly 70% of days. Most posts go out around 15:00 UTC, and Monday is the busiest day of the week. Of the 22 posts sampled, 100% carry an image or video and 100% link out. The account's strongest tracked post pulled 66 interactions, about 2.4x its own typical post.

What is DevOps on Azure's engagement rate on X?
DevOps on Azure (@AzureDevOps) has an engagement rate of 0.03%, based on the median interactions across 22 original posts from the last 30 days against 95,879 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
Is that a good engagement rate?
At 0.03%, DevOps on Azure sits above the 25th percentile of the 37,701 accounts in this comparison. Those comparison accounts are all large ones, because our scanning cadence is weighted towards big accounts, so this is a ranking among peers of similar scale rather than a ranking across X.
Does @AzureDevOps have real engagement?
Its engagement rate beats 32% of the tracked X accounts closest to it in follower count (3,899 accounts), which puts it in the middle of its size range group. Ranking inside a size band matters because engagement rate falls as accounts grow, so a raw rate would mostly re-measure the follower count. It is a starting point for a look at follower quality, not a verdict on it.
When does @AzureDevOps post?
Most posts go out around 15:00 UTC, and Monday is its busiest day, at roughly 0.73 posts per day across the measured window.

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