- Seven Microservices Anti-Patterns — One common mistake people made with SOA was misunderstanding how to achieve the reusability of services. Teams mostly focused on technical cohesion rather than functional regarding reusability. For example, several services functioned as a data access layer (ORM) to expose tables as services; they thought it would be highly reusable. This created an artificial physical layer managed by a horizontal team, which caused delivery dependency. Any service created should be highly autonomous – meaning independent of each other.
- CSCI 4974 / 6974 Hardware Reverse Engineering — RPI CS course in reverse engineering.
- The Gremlin Graph Traversal Language (Slideshare) — preso on a language for navigating graph data structures, which is part of the Apache TinkerPop (“Open Source Graph Computing”) suite.
- Why Are There Still So Many Jobs? The History and Future of Workplace Automation (PDF) — paper about the history of technology and labour. The issue is not that middle-class workers are doomed by automation and technology, but instead that human capital investment must be at the heart of any long-term strategy for producing skills that are complemented by rather than substituted for by technological change. Found via Scott Santens’s comprehensive rebuttal.
Elevate automation through orchestration.
As sysadmins we have been responsible for running applications for decades. We have done everything to meet demanding SLAs including “automating all the things” and even trading sleep cycles to recuse applications from production fires. While we have earned many battle scars and can step back and admire fully automated deployment pipelines, it feels like there has always been something missing. Our infrastructure still feels like an accident waiting to happen and somehow, no matter how much we manage to automate, the expense of infrastructure continues to increase.
The root of this feeling comes from the fact that many of our tools don’t provide the proper insight into what’s really going on and require us to reverse engineer applications in order to effectively monitor them and recover from failures. Today many people bolt on monitoring solutions that attempt to probe applications from the outside and report “health” status to a centralized monitoring system, which seems to be riddled with false alarms or a list of alarms that are not worth looking into because there is no clear path to resolution.
What makes this worse is how we typically handle common failure scenarios such as node failures. Today many of us are forced to statically assign applications to machines and manage resource allocations on a spreadsheet. It’s very common to assign a single application to a VM to avoid dependency conflicts and ensure proper resource allocations. Many of the tools in our tool belt have be optimized for this pattern and the results are less than optimal. Sure this is better than doing it manually, but current methods are resulting in low resource utilization, which means our EC2 bills continue to increase — because the more you automate, the more things people want to do.
How do we reverse course on this situation? Read more…
Moving beyond ad-hoc automation to take advantage of patterns that deliver predictable capabilities.
Can you release new features to your customers every week? Every day? Every hour? Do new developers deploy code on their first day, or even during job interviews? Can you sleep soundly after a new hire’s deployment knowing your applications are all running perfectly fine? A rapid release cadence with the processes, tools, and culture that support the safe and reliable operation of cloud-native applications has become the key strategic factor for software-driven organizations who are shipping software faster with reduced risk. When you are able to release software more rapidly, you get a tighter feedback loop that allows you to respond more effectively to the needs of customers.
Continuous delivery is why software is becoming cloud-native: shipping software faster to reduce the time of your feedback loop. DevOps is how we approach the cultural and technical changes required to fully implement a cloud-native strategy. Microservices is the software architecture pattern used most successfully to expand your development and delivery operations and avoid slow, risky, monolithic deployment strategies. It’s difficult to succeed, for example, with a microservices strategy when you haven’t established a “fail fast” and “automate first” DevOps culture.
Continuous delivery, DevOps, and microservices describe the why, how, and what of being cloud-native. These competitive advantages are quickly becoming the ante to play the software game. In the most advanced expression of these concepts they are intertwined to the point of being inseparable. This is what it means to be cloud-native.
Microservices optimize evolutionary change at a granular level.
We just finished the first O’Reilly Software Architecture Conference and the overwhelming most popular topic was microservices. Why all the hype about an architectural style?
Microservices are the first post-DevOps revolution architecture.
The DevOps revolution highlighted how much inadvertent friction an outdated operations mindset can cause, starting the move towards automating away manual tasks. By automating chores like machine provisioning and deployments, it suddenly became cheap to make changes that used to be expensive. Some architects properly viewed this new capability as a super power, and built architectures that fully embraced the operational aspects of their design. The Microservice architectural style prioritizes operational concerns as one of the key aspects of the architecture.
Microservice architectures borrow a design aesthetic from Domain Driven Design called the Bounded Context. A bounded context encapsulates all internal details of that domain and has explicit integration points with other bounded contexts. Microservice architectures reify the logical DDD bounded context into physical architecture. For example, it is common in microservice architectures for services that must persist data to own their database: members of the service team handle provisioning, backups, schema, migration, etc. In other words, in microservice architectures, the bounded context is also a physical context. But that also means that this service implementation isn’t coupled to any other team’s implementation, clearing the path for independent evolution. I recently published some writing about the recent realization that architecture is abstract until operationalized. In other words, until you have deployed an architecture and upgraded parts of it, you don’t fully understand it.
Five things we learned from the O’Reilly Software Architecture Conference 2015.
Within this piece you’ll find my takeaways and lessons learned from the event. I expect these initial impressions to both shape our upcoming exploration of software architecture and be shaped by continued shifts within software architecture.
The O'Reilly Radar Podcast: Neal Ford on the changing role of software architects and the rise of microservices.
In this episode of the Radar Podcast, O’Reilly’s Mac Slocum sits down with Neal Ford, a software architect and meme wrangler at ThoughtWorks, to talk about the changing role of software architects. They met up at our recent Software Architecture Conference in Boston — if you missed the event, you can sign up to be notified when the Complete Video Compilation of all sessions and talks is available.
Slocum started the conversation with the basics: what, exactly, does a software architect do. Ford noted that there’s not a straightforward answer, but that the role really is a “pastiche” of development, soft skills and negotiation, and solving business domain problems. He acknowledged that the role historically has been negatively perceived as a non-coding, post-useful, ivory tower deep thinker, but noted that has been changing over the past five to 10 years as the role has evolved into real-world problem solving, as opposed to operating in abstractions:
“One of the problems in software, I think, is that you build everything on towers of abstractions, and so it’s very easy to get to the point where all you’re doing is playing with abstractions, and you don’t reify that back to the real world, and I think that’s the danger of this kind of ivory-tower architect. When you start looking at things like continuous delivery and continuous deployment, you have to take those operational concerns into account, and I think that is making the role of architect a lot more relevant now, because they are becoming much more involved in the entire software development ecosystem, not just the front edge of it.”
From careers to culture to code, here are key insights from the O'Reilly Software Architecture Conference 2015.
Experts from across the software architecture world came together in Boston for the O’Reilly Software Architecture Conference 2015. Below we’ve assembled notable keynotes, interviews, and insights from the event.
Software architects: post-“post-useful”
The old notion of a software architect being a non-coding, post-useful deep thinker is giving way to something far more interesting, says Neal Ford, software architect and meme wrangler at ThoughtWorks. “Architecture has become much more interesting now because it’s become more encompassing … it’s trying to solve real problems rather than play with abstractions.”