Sökning: "DevOps Lifecycle"

Visar resultat 1 - 5 av 6 uppsatser innehållade orden DevOps Lifecycle.

  1. 1. ITIL4 & DEVOPS : EN STUDIE OM ITIL4 OCH DESS SAMEXISTENS MED DEVOPS

    Kandidat-uppsats, Högskolan i Borås/Akademin för bibliotek, information, pedagogik och IT

    Författare :Emil Thornberg; Daniel Arvidsson; [2022]
    Nyckelord :TSM; ITIL4; DevOps; Agile; IT Framework; SVS; Service Value System; DevOps Lifecycle; ITSM; ITIL4; DevOps; Agilt; IT ramverk; SVS; Service Value System; DevOps Livscykel;

    Sammanfattning : I dagens IT-landskap kan det vara väldigt besvärligt för organisationer att navigera sig. Med den snabba utveckling som sker med teknik och applikationer, men även kring ramverk och arbetsmetoder som alla säger sig vara det bästa för just ens egen organisation. LÄS MER

  3. 2. Development and Evaluation of an Artefact Model to Support Security Compliance for DevSecOps

    Master-uppsats, Blekinge Tekniska Högskola/Institutionen för programvaruteknik

    Författare :Pranavi Bitra; Chandra Srilekha Achanta; [2021]
    Nyckelord :DevOps; DevSecOps; Security Compliance; Standard; Artefacts;

    Sammanfattning : Background. DevOps represents a set of principles and practices of the software development (Dev) and information technology operations (Ops) of the product lifecycle requirements. DevOps has become a buzzword in organizations because it is an agile software development offspring. LÄS MER

  4. 3. Scalable Architecture for Automating Machine Learning Model Monitoring

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Javier de la Rúa Martínez; [2020]
    Nyckelord :Model Monitoring; Streaming; Scalability; Cloud-native; Data Drift; Outliers; Machine Learning; Modellövervakning; Streaming-metod; Skalbarhet; Molnbaserad; Dataskift; Outlierupptäckt; Maskininlärning;

    Sammanfattning : Last years, due to the advent of more sophisticated tools for exploratory data analysis, data management, Machine Learning (ML) model training and model serving into production, the concept of MLOps has gained more popularity. As an effort to bring DevOps processes to the ML lifecycle, MLOps aims at more automation in the execution of diverse and repetitive tasks along the cycle and at smoother interoperability between teams and tools involved. LÄS MER

  5. 4. DataOps : Towards Understanding and Defining Data Analytics Approach

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Kiran Mainali; [2020]
    Nyckelord :DataOps; Data lifecycle; Data analytics; DataOps pipeline; Data pipeline; DataOps tools and technologies; DataOps pipeline; DataOps; Data lifecycle; Data analytics; DataOps pipeline; Data pipeline; DataOps tools and technology; DataOps pipeline;

    Sammanfattning : Data collection and analysis approaches have changed drastically in the past few years. The reason behind adopting different approach is improved data availability and continuous change in analysis requirements. Data have been always there, but data management is vital nowadays due to rapid generation and availability of various formats. LÄS MER

  7. 5. DevOps-Kultur : En explorativ fallstudie på Arbetsförmedlingens IT-avdelning

    Master-uppsats, Uppsala universitet/Industriell teknik

    Författare :Adam Holm; Johan Virtanen; [2018]
    Nyckelord :DevOps; Organisationskultur; Förändring; Ledarskap; Beroenden; IT- organisationer; Kommunikation; Information; Team; Silos; Självledarskap;

    Sammanfattning : Information Technology has taken a larger focus in today’s society and become a more centralized part of IT-organizations and other businesses. The traditional management models for manufacturing and production has become harder to apply in the software lifecycle. This is since the software no longer is produced and launched with no follow-up. LÄS MER