Why DevOps is Doomed – Ops teams are lost!
The problem between dev and ops is primarily a terminology, communication and respect problem resulting in poor operational support. The two organizations say common things backed by different definitions that are not in agreement. For example, would ops define an “application” in Puppet the same way dev would define an “application” in Hudson? If not, how would you automate or even communicate between the two for automated application deployments? Dev and Ops really have no concept of each other’s world, yet they assume the other side understands their view, or they expect that the other side should understand their view.
I love the concept of DevOps and I am very optimistic about the movement’s value. However, I’m also very concerned about traditional IT leadership’s capacity to focus on the right goals to make DevOps successful. Bridging development and operations is NOT about dev teams utilizing a continuous integration tool like Hudson or Bamboo. And it’s NOT about ops teams standing up a configuration management tools like Puppet or Chef. Both may be needed for your automation efforts, but DevOps is about bringing dev and ops teams together so people and tools from both realms are communicating with common terminology, data sources and objectives. As always, communicating and working together for a common goal is the challenge!
- Developers tend to think infrastructure is pretty straightforward. “I can stand up a server at Amazon in seconds. These clowns at work take forever with the simplest requests.”
- Systems Administrators tend to expect developers to understand the infrastructure their applications run in. “The developer said it worked on his dev server, so obviously we screwed it up in production. The dumbass doesn’t understand firewalls or our company’s network.”
On average, developers know application code architecture and think they know systems architecture, but they DO NOT. On average, systems and network administrators have good diversity and know a lot of different infrastructure disciplines, and think they know application code architecture, but they DO NOT.
So why would DevOps be doomed for failure?
Web applications, services architecture and cloud providers have destroyed any hope of success for the traditional IT leadership sold on yesterday’s operational support model. There has to be a fundamental change to recognize that systems and applications are no longer static, documented operational models; they are dynamic release-time dependency models. And there has to be a systematic way for dev teams to communicate application architectures so ops teams understand them.
Have you ever been asked to document application dependencies? If so, could you? If so, how long was it valid? Documenting a traditional three-tiered application is pretty easy. Documenting an application in a service-oriented architecture is only valid until the next code release –As each release may utilize a new service end-point, dependent on a new network segment, dependent on a new database, dependent on a new data center in a different region. Good luck on managing the relationships for your ops teams!
Application designs no longer have a universal hierarchy; the diversity and rate of change can not be easily modeled in a traditional database schema. Enterprise IT tools used to manage the environment provide little help as they expect a static hierarchical application model. ITIL and service catalog implementations also tend to expect a static hierarchical application model. The three-tiered app is gone with the introduction of web application, service architectures and cloud providers. It’s game over if you can’t define your applications, model it, and use that same data to automate the build, deployment and operations life cycle.
The bottom line
Operations teams are lost and have no idea what an application looks like, how to model it, or how to support it. Nor have traditional enterprise IT solutions provided the tools to help model the web app and cloud era. Today’s dependency maps look like circuit boards. If you zoom in, you only see some components of your applications dependencies. If you zoom out, you see the circuit board but can’t read or understand any details.
Let’s say your web application renders a page. For that simple transaction, your application calls multiple service applications, each with multiple endpoints, each with multiple database dependencies. Some databases may be dependent on nightly ETL jobs to provide valid data for your functionality. Maybe the UI is rendered by a separate UI platform with its own application, service dependencies and databases. Now, let’s say the relevant applications, services, and databases are developed by five different dev teams across three different states.
An event: some functionality in your application fails intermittently. How does your ops team troubleshoot the problem and resolve it? Is the “application” just the part your dev team developed, or is the application the whole “circuit board” of dependencies? Can your app be described effectively in a knowledgebase, KB article, or wiki site? Can the “circuit board” be effectively described in a CMDB or support tools? If so, who out of the five dev teams is accountable for maintaining changes to it? Is your ops team relegated to calling in subject matter experts from each team for troubleshooting? Is your ops team able to be effective without a clear understanding of the application?
To be successful, we have to enable our ops teams to manage the dynamic changes and complexity of today’s applications. Manual communication processes will fail, so we need to redefine the minimum bar for “automation.” Systems Administrators creating a bunch a scripts and standing up Puppet or Chef is not automation. Developers using Hudson or Bamboo for continuous integration builds is not automation. Automation has to link the application, build, and configuration management together.
- “Automation” needs to be an architecture platform, not an individual tool or effort.
- Automation “platforms” must bridge the technical communication gap between development and operational lifecycle tools, thus enabling organizational DevOps efforts.
The key is establishing common data models and service architectures that enables the automation and a common communication language at a very technical level. If you have been following Willie’s posts on skydingo.com, then it should be clear why we think a CMDB architecture using an unstructured NoSQL technology like Neo4j is so valuable.
In part 2 of this series I will illustrate an application example providing details on how it lacks hierarchical structure, and why the term “application” creates so many problems for DevOps in enterprise organizations. Then I’ll describe how we are working to solve the problem with our automation platform.