Jellyfish announced the launch of Jellyfish Benchmarks, a way to add context around engineering metrics and performance by introducing a method for comparison.
DevOps and Continuous Delivery are intimately intertwined, both with one another and with revenue growth. In effect, applying DevOps principles across the lifecycle smoothes the way or “greases the wheels” for efficient delivery of application code.
Indeed, in EMA’s latest survey, almost 90% of the respondents reported their companies are utilizing both, and almost 20% are delivering new code daily or more often (see Figure 2). Respondents report business benefits including higher levels of customer satisfaction, faster revenue growth, and better competitive differentiation from their Continuous Delivery initiatives.
Figure 2. 65% of surveyed companies deliver code at least weekly; 15% deliver daily
There is, however, a dark side to this scenario as well. While the business benefits can be significant, adverse impact on production environments and on IT support can also be significant. Fifty percent of companies surveyed report that development and operations teams are spending more time supporting production as a direct result of frequent production changes. Today, development teams spend approximately as much time supporting production as they do developing new applications. Operations spends almost 15% more time troubleshooting application problems than it does troubleshooting infrastructure problems.
These statistics are a good argument for tools supporting change control, unit and integration testing, workflow management, and deployment automation. They also support investments in Application Performance Management (APM) tools that can be used across the lifecycle to troubleshoot issues in complex application environments.
Increasingly, these high-performing companies are turning to automation to solve these problems. Companies that have automated Continuous Delivery processes often report that production problems decrease, based on the fact that hardware and software provisioning becomes planned and policy-driven, enabling a “cookie cutter” approach. To enable maximum flexibility in terms of deployment targets, best practice dictates that tools supporting deployment, provisioning, workload automation, and release automation should be “cloud ready.”
This means they are equally capable of deploying configurations and code artifacts to cloud infrastructure, such as Infrastructure as a Service (IaaS) and private cloud environments incorporating virtualization, as they are deploying to traditional physical hardware.
To sum up, the companies growing revenue today appear to be those that are also maximizing investments in DevOps and Continuous Delivery practices and the tools that support them. As the statistics above demonstrate, the results can be stunning. However, automation, properly applied, can mean the difference between applications and services that benefit the business and those that introduce chaos into production and consume additional resources.
Julie Craig is Research Director for Application Management at Enterprise Management Associates (EMA).