Managing machine learning

In July 2018 I wrote here about the next evolution of application life-cycle management (ALM), which is extending its reach into the space of DevOps continuous delivery management, helping to extend the reach of full traceability from requirements to deployed code. ALM tools and the art and science of software engineering supporting it have much … continue reading

Analyst View: Making Java a modern language

Programming languages go through cycles of adoption. A nice visual timeline of popularity as measured by TIOBE shows Java dominant since the index began in 2002, with C showing close tracking and resilience throughout, and with C++, Python, and VB.NET falling into the next cluster that formed through 2018 at half the percentage rating. Other … continue reading

Analyst View: The next evolution in application life cycle management

Software lifecycle management (SLM) is the discipline for managing software development across its life cycle. I’ve been covering this space since 2003 when I started as an IT industry analyst and have witnessed its evolution as the vendor tool category of application life cycle management (ALM). It’s useful to ask what the difference is between … continue reading

Analyst Watch: From monoliths to microservices

Once organizations and their development teams have mastered agile and DevOps, the next step is to look at what software architecture is the best fit for DevOps. DevOps introduces automation into operations with continuous delivery. However, the benefits of rapid change in production can only be realized if it is possible to make these changes … continue reading

Analyst Watch: The diverse market for performance management

Research indicates that APM is in demand by the various elements of software development … continue reading

Analyst Watch: Adobe beyond Flash

Flash will still receive some support from Adobe; IBM’s Worklight purchase sheds light on its mobile plans … continue reading

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