Mark Mansour, a senior manager of software development at Amazon Web Services, writes about continuous delivery at AWS.

Over 10 years ago, we undertook a project at Amazon to understand how quickly our teams were turning ideas into high-quality production systems. This led us to measure our software throughput so that we could improve the speed of our execution. We discovered that it was taking, on average, 16 days from code check-in to production. At Amazon, teams started with an idea, and then typically took a day and a half to write code to bring the idea to life. We spent less than an hour to build and deploy the new code. The remainder of the time, almost 14 days, we spent waiting for team members to start a build, to perform deployments, and run tests. At the end of the project, we recommended automating our post check-in processes to improve our speed of execution. The goal was to eliminate delays while maintaining or even improving quality.

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14%

Which of the following best describes how you currently monitor and manage systems across your hybrid cloud environment?(Required)

Multiple separate tools for different environments

Multiple separate tools for different monitoring and management functions

Single consolidated dashboard

Custom built monitoring and management solution

No full monitoring and management solution

Don’t know

How valuable would it be for your monitoring and management solution to incorporate predictive analytics to help you identify and address system issues that are critical and not waste time or effort working through all the data and “noise” that is not critical?(Required)

Extremely valuable

Moderately valuable

Somewhat valuable

Slightly valuable

Not valuable

How do you most typically address potential system issues BEFORE they impact your operations?(Required)

Automated workflows and playbooks to remediate potential issues as soon as they are detected

An orchestrated response process that leverages automation, AI, and human expertise to rapidly respond to potential issues

Advanced monitoring tools such as predictive analytics and anomaly detection to proactively identify and address potential issues

Respond to issues as they arise, using manual processes and troubleshooting techniques

A combination of automated remediation, orchestrated response, and/or proactive monitoring to address potential system issues

Don’t know

Other

What methods does your organization use to control and monitor cloud/IT spending?(Required)

Centralized procurement processes

Pre-approved budget thresholds

Automated cost monitoring tools

Department-level spending controls

Regular cost audits and reviews

Cloud cost optimization platform

Approval workflows for resource provisioning

Native financial operations tools provided by the cloud provider

No formal controls in place

Don’t know

Other

Please specify:

Which methods do you rely on most to detect security vulnerabilities in your systems?(Required)

Automated scanning tools

Manual assessments

Vendor notifications

Threat modeling (for early detection)

None of these

Don’t know

Other

Please specify:

What are the TWO most common ways you prioritize vulnerabilities to address within your environment?(Required)

Based on potential impact

Based on exploitability

Regulatory compliance requirements

Based on CVSS scores

Risk-based analysis of multiple factors

First-in-first-out approach

No formal prioritization process

Don’t know

How do you typically handle system updates and security patches?(Required)

Automated updates and patches

Manually review and apply updates and patches on a regular schedule

A combination of automation and manual review

Apply updates and patches on an as-needed basis.

Outsourced update and patch management

No defined process

Don’t know

Other

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Amazon had already built software development tools to make our software engineers more productive. We created our own centralized and hosted build system, Brazil, that executes a series of commands on a server with the goal of generating an artifact that could be deployed. At this point Brazil didn’t listen to source code changes. A person had to initiate a build. We also had our own deployment system, Apollo, which required a build artifact to be uploaded to it as part of initiating a deployment. Inspired by the interest in continuous delivery occurring in the industry, we built our own system, Pipelines, to automate the software delivery process between Brazil and Apollo.

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