Predictive Delivery Using a Data-Driven Early Warning System

While the DevOps Research and Assessment (DORA) group’s metrics are taken as gospel for tracking DevOps success, many enterprises have a hard time getting started. Some organizations have even lost contracts to competitors since they could not establish DevOps compliance, owing to lack of visibility throughout the DevOps lifecycle. Given the value of tracking DORA metrics is already established, and the potential business impact of not doing so is huge, why haven’t enterprises been able to get started and crack the code?

Some enterprises have started the journey but are unable to drive decisions since they cannot drill across or deeper into the failures. Further, benchmarking these metrics across other successful implementations remains a far-fetched mystery at this stage for many.

Specific areas to be discussed in this webinar include:
1. Where to begin with implementation of DORA metrics? What is required?
2. What are some common challenges?
3. How to drill through and across various metrics?
4. How to course correct and sustain once things go off-track?
5. How to scale these DevOps metrics for various teams?

Why Attend?
• Learn from real-world implementations enabled by Klera
• Get your DevOps tool chain related questions answered by experts
• Discover how to realize value from DevOps metrics analysis, and enable teams faster

Break Data Silos Across Tools, to Build a Unified To-Do List

Product engineering organizations typically juggle multiple sources of inputs during product planning. New requirements, tickets, bugs, and historical backlog issues – all exist in disparate tools. It is difficult to get a unified view across all these tools to see a complete picture of the situation. The probability of missing something is very high. The consequences are dire. The solution lies in creating a single source of truth – a unified product backlog.

Key takeaways:
- Simplify release and iteration planning with a single product backlog
- Prioritize business critical requirements and improve people’s productivity
- Drive business value and align overall product direction with customers’ needs

Estudios recientes, con encuestas hechas a ejecutivos y equipos de desarrollo, muestran que las organizaciones pueden desarrollar productos de una manera más rápida sin necesidad de aumentar el tamaño de sus equipos, utilizando nuevas tendencias para facilitar su trabajo.

En este webinar hablaremos de las principales barreras que impactan el rendimiento de los equipos y compartiremos soluciones para superarlas e incrementar la productividad de nuestros desarrolladores.

Entre dichos obstáculos tenemos:

-Conflictos de última hora en el código
-Limitación en el análisis de impacto del código

Delivery leaders are always seeking ways to mitigate risks to ensure timely delivery of high-quality software. However, enterprises struggle to proactively assess risks and plan actions in order to maintain the schedule, scope, and quality of deliveries.

Ashwani Nandini, Vice President - Global Delivery Assurance at GlobalLogic, championed predictive delivery by using a data-driven early warning system to assess risks, plan actions and eliminate gut-based inefficiencies.

Join GlobalLogic and Klera for a live webinar to learn:

• How to apply analytics to transform software delivery, by identifying and
eliminating risks using an early warning system

• What type of rigor is required and actions to plan to ensure on-time delivery,
while meeting scope and quality commitments

• What key metrics to track as measures of predictability

• How to get buy-in to normalize processes across teams and projects, and drive
the cultural shift

Deliver Reliable and High-Quality Software while Ensuring Speed and Cost-Effectiveness

Engineering teams play a crucial role in creating value for customers and driving competitive leadership, growth, and profitability for a business. Moreover, quality and reliability measures taken during the development process define customer experiences.

Key takeaways of the webinar:
- Apply a data-driven, customer-focused approach throughout the development lifecycle, to ensure reliability and quality
- Develop a framework to measure reliability and quality of development on an ongoing basis
- Identify process gaps and create actionable proposals and plans
- Minimize the need for meetings and use self-service analytics to course correct as needed

Los equipos de ALM y DevOps utilizan varias herramientas que operan de manera independiente. Esto dificulta una visión global de los distintos procesos involucrados en estas y otras áreas, y crea una barrera para mejorar la productividad de los equipos de ingeniería, al no tener la visibilidad suficiente sobre el trabajo y los resultados.

Las soluciones tradicionales para identificar riesgos, bloqueos, entre otros problemas en los desarrollos de metodología Agile y procesos de CI-CD, suelen ser costosos en cuanto a tiempo y recursos, y pueden resultar en fracaso si no son ejecutados de la manera adecuada.

Los equipos requieren una solución integral que les permita recolectar, analizar y sincronizar información de varias herramientas de una manera sencilla.

En esta sesión, demostramos cómo analizar el rendimiento en un proyecto ágil y explicamos la mejor manera de:
-Recolectar información de herramientas como Jira, Git, y SonarQube, utilizando conectores bidireccionales.
-Navegar y analizar de manera interactiva la información de varias herramientas
Sincronizar información de manera inteligente.

Top Developer Challenges – Last Minute Code Conflicts at Merge and Inefficient Impact Analysis

Eliminating productivity barriers and boosting developer performance is key to the success of any software product enterprise. Decode the challenges faced by product development teams and explore pathways to eliminate these challenges to boost developer productivity.

Key takeaways of the webinar:

- Discuss and quantify how merge conflicts and inefficient impact analysis hamper developer productivity
- Learn how to apply a data driven approach to identify and eliminate process bottlenecks with early warnings