Marc Brooker

@MarcJBrooker · joined 12 Oct 2013

Distinguished engineer at AWS. AI, agents, databases, and serverless. Views are my own.

25 863Followers

749Following

3 419Posts total

99KViews on collected posts

Against accounts of the same size

15 posts from the last 90 days, next to the 10K–100K follower range. shown widely, but few of those viewers react.

Median views1 921this account1 456median for 10K–100K

Reach, %7.43%this account4.50%median for 10K–100K

Engagement, %0.95%this account1.88%median for 10K–100K

Metric	This account	Median for 10K–100K	Ratio
Median views per post	1 921	1 456	1.32×
Reach (views ÷ followers)	7.43%	4.50%	1.65×
Engagement rate	0.95%	1.88%	0.50×

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

26.8K18 Aug

27.1K

1.3K

1.6K

1.9K

1.4K

1.3K

1.2K

1.2K

979

9.5K31 Aug

3.8K

3.6K1 Sep

7.8K2 Sep

Last 14 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.14%18 Aug

0.95%

0.99%

0.87%

1.15%

1.26%

1.46%

1.30%

0.97%

0.92%

1.16%31 Aug

0.03%

0.28%1 Sep

0.41%2 Sep

Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.88%.

What the audience does

Likes58.5%517 in total

Reposts4.0%35 in total

Replies3.7%33 in total

Quotes0.8%7 in total

Bookmarks33.0%292 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.

Latest posts

If somebody at Apple wants to become my new best friend, all they need to do is backport the MacOS 27 endpoint security feature set to MacOS 26. 7.8K views · 27 likes · 1 reposts · 3 replies 02 Sep 2026 Only read transactions on schemas that specifically use foreign key constraints, to be clear. But if you're using FKCs and coordinating on reads, why not be pessimistic? 3.6K views · 7 likes · 1 reposts · 2 replies 01 Sep 2026 @MarcJBrooker I wonder, at this point, whether PCC would be a better fit, given that even read transactions can now abort at commit time. 3.8K views · 0 likes · 0 reposts · 0 replies 31 Aug 2026 Did you know that Aurora DSQL now supports foreign key constraints? The team's done a great job here: FKCs that scale well, especially for your read-heavy workloads. Check it out here: https://t.co/LkGszVsKFu Quick thread on how FKCs in DSQL work... https://t.co/kTK34XAqMI 9.5K views · 88 likes · 15 reposts · 5 replies 31 Aug 2026 @MarcJBrooker out of curiosity, have you observed fsync failures in production before? 979 views · 7 likes · 0 reposts · 2 replies 18 Aug 2026 It requires the assumption that fsync() failures are uncorrelated. They may be correlated between machines (e.g. by temperature or power quality), but highly unlikely to be correlated between AZs and regions. 1.2K views · 9 likes · 0 reposts · 3 replies 18 Aug 2026 This is converting a complex/partial/gray failure into a simple "fail stop" failure. The ability to do this is a great system simplifier. 1.2K views · 14 likes · 0 reposts · 1 replies 18 Aug 2026 Love this topic, because it's a perfect illustration of why so much of the "single system is simpler" discourse is wrong (because it mostly ignores the hard problems that introduces). 1.3K views · 19 likes · 0 reposts · 0 replies 18 Aug 2026 Our paper doesn't go into much depth on this, but will give you the context you need: https://t.co/uSRWI4xVAa 1.4K views · 17 likes · 0 reposts · 1 replies 18 Aug 2026 Case 1: sync failure on commit (in Journal). Journal has multiple sync replicas and multiple async replicas. An fsync failure in a sync replica will cause it to be removed from the quorum, and replaced by an async replica. 1.9K views · 21 likes · 0 reposts · 1 replies 18 Aug 2026 Edge cases are handled by the reconfiguration protocol, which makes sure there is a consistent monotonic view of the data. This protocol needs to exist anyway (to get multi-AZ or multi-region fault-tolerant durability). 1.6K views · 13 likes · 0 reposts · 1 replies 18 Aug 2026 Case 2: sync failure on apply (in Storage). Storage isn't responsible for durability, and uses flash (essentially) as an expanded/cheaper memory. Recovery is from Journal/S3. So could safely ignore an fsync failure (but doesn't because it's a symptom of deeper issues). 1.3K views · 12 likes · 0 reposts · 1 replies 18 Aug 2026 Handling edge-case failures like this is way simpler in distributed storage databases (e.g. Aurora) and distributed databases (e.g. Aurora DSQL) than in single-system databases. It's one of many cases where distribution simplifies system properties. Here's how it works in DSQL: 27.1K views · 234 likes · 16 reposts · 5 replies 18 Aug 2026 Does anyone know good blogs around how databases handles fsync failures? 26.8K views · 27 likes · 2 reposts · 7 replies 18 Aug 2026 Absolutely beautiful part of the world. Just don't mess with the hippos. 9.4K views · 22 likes · 0 reposts · 1 replies 13 Aug 2026

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