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David Yanacek is a Senior Principal Engineer working on AWS Lambda. David has been a software developer at Amazon since 2006, previously anemia symptoms working on Amazon DynamoDB and AWS IoT, and also internal web service frameworks and fleet operations automation systems. One of David’s favorite activities at work is performing log analysis and sifting through operational metrics to find ways to make systems run more and more smoothly over time.
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For example, if a server fails to process the message that it pulls off SQS, then SQS redelivers that message to another server after a configured message visibility timeout. Another compensating factor is an alarm that goes off when there are too many errors processing messages, alerting an operator to investigate.
- Or you might get a procedure to show arteries in the heart that has a risk of heart attack or death in two patients for every 100 who get the test.
- For example, a false-positive blood test can result in a biopsy.
- These false alarms can cause anxiety, and unnecessary follow-up tests and treatments.
- This plugin will perform a number of checks on your WordPress installation to detect common configuration errors and known issues, and also allows plugins and themes to add their own checks.
• Tests that perform a basic HTTP requests and make sure that the server responds with a 200 status code. We are using questions recommended by the CDC as our starting point. Based on our research, these are common questions that almost all teams, organizations and health departments are requesting.
If any of these alarms trigger, the deployment system halts the deployment and rolls back. • Fleets should be relatively homogeneous—In fleets that include different instance types, some instances might be slower than others, which can falsely trigger passive bad server detection. To work around this scenario, we collate metrics by instance type. • Old code—If a server is disconnected from the network or powered off for a long time and then comes back on line, it could be running dangerously outdated code that is incompatible with the rest of the fleet. • Other unusual software bugs that require a process bounce—Deadlocks, memory leaks, or state corruption bugs can make a server spew errors.
Servers, and the software that runs on them, fail for all kinds of weird reasons. As software developers, we eventually write some bug like the one I describe above that puts the software into a broken state. Multiple layers of checks, from lightweight liveness checks to passive monitoring of per-server metrics, are needed to catch all types of unexpected failure modes. In these kinds of situations, there are often several compensating factors to help contain the impact.
Fortunately, in practice Amazon teams implement multiple mitigating systems to prevent this scenario from taking out their whole fleet. One such mitigation is to configure alarms that trigger whenever the overall fleet size is too small or running at high load, or when there is high latency or error rate.
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