The Psychology of the AWS Outage
Unless you’ve been living on another planet, you’re certainly aware that over the past couple of hours Amazon’s AWS S3 service has experienced a serious outage, which has affected thousands of sites and services around the world. For reasons I will elaborate in this post, the coverage of this outage has been blown completely out of proportion. So, what’s the difference between the perceived risk associated with the AWS outage and the actual risk of this outage?
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Developing in the Cloud
Running a top-notch software development organization used to be a capital-intensive endeavor, requiring significant technical and organizational resources, all managed through layers of bureaucracy. Not anymore. First, many of the pricey systems and tools that we developers need to work effectively are usually available for free as open source software. More importantly, cheap, cloud-based offerings do away with the setup, maintenance, and user support costs and complexity associated with running these systems. Here are just a few of the services and providers that any developer group can easily tap into
(you can find many more listed here):
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The virtual machine (VM) is the most dazzling comeback in information technology. IBM implemented a VM platform architecture in the late 1960s in its CP/CMS operating system. The company’s goal was to provide the time-sharing capabilities that its batch-oriented System/360 lacked. Thus a simple control program (CP) created a VM environment where multiple instances of the single-user CMS operating system could run in parallel. Thirty years later, virtualization was rediscovered when companies like VMware found ways to virtualize the less accommodating Intel x86 processor architecture. The popularity of Intel’s platform and the huge amount of software running on it made virtualization an attractive proposition, spawning within a decade tens of proprietary and open source virtualization platforms.
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Why are AWS Command-Line Tools so Slow?
Amazon's Elastic Compute Cloud command-line tools are useful building
blocks for creating more complex shell scripts.
They allow you to start and stop instances, get their status,
add tags, manage storage, IP addresses, and so on.
They have one big disadvantage: they take a long time to run.
For instance, running ec2-describe-instances for six instances
takes 19 seconds on an m1.small AWS Linux instance.
One answer given,
is that this is caused by JVM startup overhead.
I found that hard to believe,
because on the same machine a Java "hello world" program executes in 120ms,
and running ec2-describe-instances --help takes just 321ms.
So I set out to investigate, and, using multiple tracing tools and techniques,
this is what I found.
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