Name: Predictive Delivery Using a Data-Driven Early Warning System
Start: 2021-06-09T03:01:00Z
End: 2021-06-09T03:01:46.000Z
Location: BrightTALK
Rating: 0

Enterprises typically rely on numerous metrics and dashboards to monitor the health and performance of their DevOps initiatives. However, toolchain complexities make it difficult for DevOps teams to realize a consolidated view of data across applications, infrastructure, and platforms.

Join experts from Impetus and Klera to learn how you can quickly assess DevOps success, automate strategic workflows, manage cloud costs, and resolve performance issues. Discover best practices and proven strategies to simplify the management of disparate DevOps toolchains.

Key takeaways:

- Navigate the complexities of DevOps toolchains and avoid common pitfalls
- Discover an out-of-the-box app for data unification, monitoring, and process automation
- Optimize software delivery and quality through data-driven visibility

Enable a holistic view across your DevOps toolchains

As organizations all over the world are forced to work remotely, how have Quality Engineering (QE) teams been impacted? How can QE leaders ensure faster and high-quality releases, while efficiently managing a remote workforce? How can they identify and address risks at an early stage? How can they make continuous quality improvement a reality using data?

Join us for this webinar to learn from Ramana Sampangi - Vice President, Engineering, 8×8, Inc. and Mayur Patel - Senior Director of Quality Engineering, 8x8 Inc., on how their organization realized end-to-end, data-driven control and decision making across QE processes, making it easier for QE leaders to take the right action at the right time independent of their geographic location.

Reinvent Quality Engineering For An All Remote Workforce

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

DevOps DORA Metrics: Implementation Demystified

Take Your Agile Transformation from Concept to Reality – The Tony Stark Way

In an increasingly dynamic business landscape, more and more enterprises are recognizing the need to rapidly adapt to market changes by becoming truly agile across all dimensions. The global pandemic has further reinforced the importance of business agility as a must-have competency for thriving in ambiguity.  While many organizations have embarked on their agile journey, most of them have barely scratched the surface. 

Join us for a webinar with Agile Coach - Brian Monthie, as he looks at the various dimensions of agility through the lens of Tony Stark and charts out a path to take agility beyond software development to all aspects of your business.

Topics to be covered in the session:
•	Taking a holistic view of agility (org., dept., team, and individuals)
•	Sharing known pitfalls, traps and anti-patterns
•	Tapping into the relative unknown:  The importance of Being Agile vs Doing Agile
•	Truing up transformation: How to measure non-causality

Being Agile – The Beginning of the Endgame

Are complex development lifecycles and toolchains making incident traceability difficult? Is it hampering your serviceability and impacting risk and turn-around times for customers?

Tracking tickets or vulnerabilities down to the exact line of code can be challenging across the entire DevOps lifecycle. With greater correlated visibility across the entire development and delivery lifecycle, development teams can react quickly to issues.

Automate end-to-end traceability to quickly get to the root cause of an issue., Learn from historical issues and apply Machine Learning to identify the most suitable engineer, thus minimizing the time for resolution and enhancing customer experience.

Explore the what, why, and how of DevOps traceability:

- Why is traceability important for DevOps success?
- Roadblocks to end-to-end traceability
- Benefits of automating traceability

From Incidents and Vulnerabilities to the Exact Lines of Code in Minutes

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

Experience the Power of a Unified Product Backlog

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

Desarrollo inteligente – Maximizando la productividad de nuestros equipos

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

Predictive Delivery Using a Data-Driven Early Warning System

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

A Data-Driven Approach to Driving Quality & Reliability in Engineering

Risk Assessment

Software Delivery

On-time delivery

Predictive Analytics

Application Delivery

Application Management

Application Development

Application Lifecycle Management

DevOps

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Predictive Delivery Using a Data-Driven Early Warning System

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