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colmmacc's profile
Colm MacCárthaigh
Colm MacCárthaigh
Colm MacCárthaigh
@colmmacc

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Colm MacCárthaigh

@colmmacc

AWS, Apache, Crypto, Irish Music, Haiku, Photography

Seattle
notesfromthesound.com
Joined April 2008

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    1. Colm MacCárthaigh‏ @colmmacc 7 Dec 2018
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      If you have to throttle things to safely recover and shorten the duration of events, do! have a throttling system at hand. But don't kid yourself either: throttling a customer is also an outage. Think instead how throttling can be used to prioritise smartly ...pic.twitter.com/nDPlEoSmYB

      1 reply 1 retweet 10 likes
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    2. Colm MacCárthaigh‏ @colmmacc 7 Dec 2018
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      Example: ELB is a fault-tolerant AZ-redundant system. We can lose an AZ at any time and ELB is scaled for capacity, it'll be fine. We can deliberately throttle ELBs recovery in a zone after a power event to give our paying customers priority. Works great! Good use of throttling.

      1 reply 0 retweets 3 likes
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    3. Colm MacCárthaigh‏ @colmmacc 7 Dec 2018
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      Pattern 9: I couldn't say it at the time, but basically use a system like QLDB (https://aws.amazon.com/qldb/ ) for your control plane data flow if you can! If you have an immutable append only ledger for your data flow then ...pic.twitter.com/N1C9XQuO9D

      1 reply 3 retweets 15 likes
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    4. Colm MacCárthaigh‏ @colmmacc 7 Dec 2018
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      ... you can compute and merge deltas easily minimising data volume, and you get item history, so you can implement point-in-time-recovery and rollback! You can also optimise-out no-op changes. We use this pattern in Route 53, EC2, bunch of places.

      1 reply 0 retweets 7 likes
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    5. Colm MacCárthaigh‏ @colmmacc 7 Dec 2018
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      O.k. I left the most important thoughts and pattern for last. You have filter every element of your design through the lens of "How many modes of operation do I have". For stability, that needs to be minimal.pic.twitter.com/kvXZfbTlzl

      1 reply 3 retweets 10 likes
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    6. Colm MacCárthaigh‏ @colmmacc 7 Dec 2018
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      Avoid emergency modes that are different, or anything that can alter what the system is doing suddenly. Think about your system in terms of state space, or code branches. How many can you get rid of?

      1 reply 1 retweet 14 likes
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    7. Colm MacCárthaigh‏ @colmmacc 7 Dec 2018
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      Branches and state spaces are evil, because they grow exponentially, past the point you can test or predict behaviour, they become emergent instead. A simple example here is relational databases.pic.twitter.com/jiHIm1zGNk

      1 reply 1 retweet 10 likes
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    8. Colm MacCárthaigh‏ @colmmacc 7 Dec 2018
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      I'm not knocking offerings like RDS or Aurora, relational DBs are great for versatile business queries, but they are terrible for control planes. We essentially ban them for that purpose at AWS. Why?

      1 reply 0 retweets 9 likes
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    9. Colm MacCárthaigh‏ @colmmacc 7 Dec 2018
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      RDBMSs have built-in fancy Query Plan Optimizers that can suddenly change what indices are being used, or how tables are being scanned. That can have a disastrous effect on performance or behaviour. Another is that they are very accessible and tempting ...

      1 reply 0 retweets 5 likes
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    10. Colm MacCárthaigh‏ @colmmacc 7 Dec 2018
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      ... an operator, product manager, business analyst might all think it's safe to run a one-time read-only query, but a simple SQL typo can choke up the system! Bad bad. So what's the fix?

      1 reply 1 retweet 5 likes
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      Colm MacCárthaigh‏ @colmmacc 7 Dec 2018
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      Use NoSQL and do things the "dumb" way every time. Because the perf characteristics are much more obvious to the programmer and designer, now you can just do a full join, or a full table scan every time for every query. Much more stable!

      9:52 AM - 7 Dec 2018
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      • graste v4.1 𝚕𝚊𝚛𝚜 𝚏𝚛𝚘𝚗𝚒𝚞𝚜 Adrian White Igor Carron Steffen Opel tinyrobots Timothy Van Heest Preston Tamkin Staying at home Stanley
      1 reply 1 retweet 11 likes
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        2. Colm MacCárthaigh‏ @colmmacc 7 Dec 2018
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          I've tweet stormed about this before, but now we're getting into the "constant work" pattern. The most stable control systems do the same work all of the time, with no change that is dependent on the data, or even the volume of change.pic.twitter.com/Gp0eD5emZi

          2 replies 3 retweets 15 likes
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        3. Colm MacCárthaigh‏ @colmmacc 7 Dec 2018
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          Suppose you need to get some config to your data plane. What if the data plane just fetched the config from S3 every 10 seconds, whether it changed or not? And reloaded the configuration, every time, whether it changed or not?

          2 replies 2 retweets 8 likes
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        4. Colm MacCárthaigh‏ @colmmacc 7 Dec 2018
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          This simple, simple, design is rarely seen in the wild, but I don't know why. It's very very reliable ... incredibly resilient and will recover from all sorts of issues. It's not even expensive! We're talking hundreds of dollars per year. Not even a few days of SDE time.pic.twitter.com/6ZBaxiamwP

          2 replies 0 retweets 9 likes
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        5. Colm MacCárthaigh‏ @colmmacc 7 Dec 2018
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          That's the pattern we use for our most critical systems. The network health check statuses that allow AWS to instantly handle an Availability Zone power issue? Those are always flowing, all the time, 0 or 1, whether they change or not.

          1 reply 0 retweets 9 likes
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        6. Colm MacCárthaigh‏ @colmmacc 7 Dec 2018
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          We have these and so many more patterns, and ... we're been building them into API Gateway and Lambda behind the scenes too! So consider building your control planes on those!pic.twitter.com/DgzdZAyNNC

          2 replies 2 retweets 12 likes
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        7. Colm MacCárthaigh‏ @colmmacc 7 Dec 2018
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          Thank your for listening to my talk! Always always feel free to AMA. This is the last tweet in the thread for now, and I won't even promote my Soundcloud!

          2 replies 0 retweets 24 likes
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        8. End of conversation

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