I’m often asked for a list of articles, videos, presentations, interviews, or podcast episodes that I have made on a particular topic. I get this request for a wide variety of topics around cloud computing, DevOps, digital applications, and application modernization. Usually, I can create a list of 8-20 links to things I’ve written, created, […]
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Congratulations to Lee Atchison who is listed #13 on the Thinkers 360 Top 50 Global Thought Leaders and Influencers on Cloud Computing list for January 2020. The list, created by Thinkers 360, provides a holistic measure of thought leadership and authentic influence. If you are interested in seeing the entire list, head over to Thinkers […]
It’s simple, really — services call other services and they take actions based on the responses from those services. Sometimes, that action is a success, sometimes it’s a failure. But whether it is a success or a failure depends on if the interaction meets certain requirements. In particular, the response must be predictable, understandable and reasonable for the given situation. This is important so that the service reading the response can make appropriate decisions and not propagate garbage results. When a service gets a response it does not understand, it can take actions based on the garbage response and those actions can have dangerous side effects to your service and your application.
Bringing down an entire application is easy. All it takes is the failure of a single service and the entire set of services that make up the application can come crashing down like a house of cards. Just one minor error from a non-critical service can be disastrous to the entire application. There are, of course, many ways to prevent dependent services from failing. However, adding extra resiliency in non-critical services also adds complexity and cost, and sometimes it is not needed. Read the entire article today in The New Stack.
By: Ken Gavranovic and Lee Atchison Want to reduce MTTR, reduce incidents and have a data driven discussion on investment allocation? Try what many modern software development and operations companies have implemented, an Enterprise Risk Matrix. We have seen implementing this process on a quarterly, bi-annual or annual basic can reduce MTTR by as much as 70%, incident count by 90% within 6-12 months. Most importantly, the risk matrix can introduce a data driven discussion about investment in products (hopefully you have already migrated away from funding projects).
The #1 book on their list is “Architecting for Scale” book by Lee Atchison. As the article says: “The first one on our DevOps reading list is Architecting for Scale. It is an excellent book to understand real-world paradigms for scaling and managing critical applications. This book covers 5 different elements: availability, risk management, services […]
Lee is a recognized industry leader in cloud computing. He has of experience and committed his career to architecting and building high scale, cloud-based, service oriented, SaaS applications. Lee is the Senior Director, Strategic Architecture at New Relic. Lee leads technical architecture and transformation within the Office of the CTO, where he engages the greater […]