After much hand wringing and collaborative sessions with teammates (most notably fellow Muleys Andrew Latham and Alison Jarris) and customers, a framework for how to think about agility has emerged that suggests a path about how to measure it (while not falling victim to Goodhart’s law).
As organizations plan their IT strategies for 2019, increasing attention is being given to DevOps.
Predictability is the primary reason companies embrace agile over waterfall. The full slate of reasons vary depending upon the context of the company, and it would certainly not come as a shock that many companies embrace agile because it’s hip. But for the most part, large companies (aside from the ones trying to be hip) tend to embrace agile for predictability with a capital P.
DevOps has become a crucial factor in IT’s success. It’s been a long journey but we are finally here.
Over 10 years ago, about every IT department—small or large—was chaotic and lacked a balance of collaboration, processes, automation, and monitoring on both sides of development and operations. Application development followed waterfall models, while applications tended to be monolithic and deployments were labor intensive but not frequent. What resulted was missed business opportunities and horrible experiences for engineers (i.e.,
In our technology-driven world, organisations cannot afford to stand still. They need to deliver software at high velocity without sacrificing stability, which is why DevOps has become such a popular approach.
As the name suggests, DevOps is an attempt to combine software development and IT operations in order to effectively get the best of both worlds: the rapid iteration favoured by the former and the stability, reliability and security favoured by the latter.
In this Q&A, Splunk CIO Declan Morris shares insight into the technology approaches that will enable Splunk to double revenue in the next three years.
The role of IT has evolved from a centralized delivery model to IT as a service, where IT-owned capabilities are being offered as a service throughout the business to drive new levels of agility. One CIO embracing the changing role is Declan Morris of Splunk, which enables organizations to turn massive streams of data into operational intelligence.
This is second in series of how to DevOps articles, and is a follow-up to the MUnit blog – HowTo(DevOps) – Leveraging MUnit For Test Automation.
A core component of the continuous integration process, that includes the previously discussed test automation framework, is the build process. As soon as the developer commits the code to version control repository, the build tool compiles the source code runs unit and integration tests and generates feedback for the developers.
Every business needs to stay agile. Every business wants to improve their speed. Every business wants to innovate faster. And they want to achieve these things not only today, not only tomorrow but for years in the future. This is true for established businesses dealing with digital disruption, but also the disrupters themselves. That’s why we’re excited to announce that Spotify, the world’s most popular and powerful streaming music service, has implemented MuleSoft’s Anypoint Platform™ to improve business agility and operational efficiency.
At MuleSoft, we are committed to customer success by investing in product and engineering operational excellence. The faster we can innovate/produce new features, the better equipped our customers are at enabling IT and transforming their businesses. One of the ways we’ve been able to move faster is by migrating to Infrastructure as Code (IaC).
IaC is the process of managing and provisioning infrastructure and its configuration through templates using code.
We all recognize the need for both server and application monitoring in a production environment and Tcat Server makes this easy. However, the development and QA process can also benefit from this feature.
At MuleSoft I’m often asked to write small one-off webapps for different parts of our internal infrastructure — often they are interim solutions or somewhat experimental; since these are somewhat less critical applications, at best I’ll create some unit tests,
