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  • How to Measure Continuous Delivery

    Stability and throughput are the things that you can measure when adopting continuous delivery practices. These metrics can help you reduce uncertainty, make better decisions about which practices to amplify or dampen, and steer your continuous delivery adoption process in the right direction.

  • Metrics Collection and Monitoring at Robinhood Engineering

    The Robinhood server operations team published a series of articles talking about their metrics collection, monitoring and alerting infrastructure. OpenTSDB, Grafana, Kafka and Riemann form the core of the stack, with Kafka acting as a proxy layer from which the data is pushed into Riemann for stream processing of the metrics and into OpenTSDB for storage.

  • Monitoring Metrics for Docker Containers

    Stefan Thies, DevOps Evangelist at Sematext, in a recent post discusses ten important container monitoring metrics and their implications on operating Docker containers, specifically when running many containers per host. Combined in a single correlated view these metrics provide a starting point for monitoring Docker-based environments.

  • DevOps Days Kiel Day 2

    Round up of the talks at DevOps Days Kiel's second day.

  • Eight Dragons of Agile Measurement

    Larry Maccherone, Director of Analytics and Research at AgileCraft and frequent speaker at agile conferences like QCon, gave a webinar in which he discusses the major risks and challenges when introducing metrics in an agile environment. Risks are referred as "dragons" and the techniques to get rid of them as "slayers".

  • Defining Devops as CALMSS

    Forrester has come-up with a new definition of DevOps. Forrester has added an additional “S” for sourcing in the CALMS definition of DevOps. They believe that DevOps must be supported by a solid sourcing strategy to extend the ecosystem. This then brings them to the acronym of CALMSS.

  • Measuring Success in Agile Organizations

    Matthew Badgley, shares ten tips for measuring agile success in a recent VersionOne blog based on the 9th annual State of Agile Survey.

  • Codecity for Eclipse Visualises Source Code Metrics

    Codetrails has released Codecity for Eclipse, which provides a visualisation of Java packages and classes in a 3D visualisation to identify where code can be improved. InfoQ evaluates the plug-in.

  • Using Objectives and Key Results in a Results-Only Work Environment Company

    Matt Rogish talked about using Objectives and Key Results (OKRs) for company, team, and personal goal setting at the No Pants Festival 2015 in Antwerp, Belgium. InfoQ interviewed Rogish about what OKRs are and how you can use them, their strengths and pitfalls, doing annual performance reviews and managing people with numerical goals, and starting with OKRs.

  • How to Use Metrics to Influence an Agile Environment

    Larry Maccherone, a Data Scientist at Tasktop Technologies, gave a talk at QCon London 2015 regarding the importance of metrics usage and how they should influence important decisions in the organizations.

  • Examples of Applying Metrics in Kanban

    Metrics are engrained in kanban. They play a role in several kanban practices like visualizing and managing flow, and support the agenda’s for sustainability, service orientation and survivability. At the Lean Kanban Central Europe 2014 Conference Wolfgang Wiedenroth talked about the power of metrics. In his presentation he provided may examples of using metrics with kanban.

  • Forecasting at Twitter

    Arun Kejariwal, from Twitter, talked at Velocity Conf London last month about forecasting algorithms used at Twitter to proactively predict system resource needs as well as business metrics such as number of users or tweets. Given the dynamic nature of their data stream, they found that a refined ARIMA model works well once data is cleansed, including removal of outliers.

  • Detecting Abnormal Traffic in Real Time with APM 9.5

    CA Technologies’ Application Performance Management 9.5 adds the ability to detect and analyze unusual performance metric patterns in near real time. This can be used to detect the beginnings of a denial of service attack, failing hardware, or a rouge application.

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