4 Key Focus Areas for Effective Performance Engineering

HTML, CSS, and JavaScript. The low level building blocks of all the web have been around for years now. But building at such a low level creates a lot of boiler plate and ofter creates worse code. Enter frameworks! But, frameworks are large, slow, and require a lot of runtime execution. Enter Compilers! We'll look at the current state of web compilers and how building at a higher level and compiling down is a better way to build for the web.

As the cloud is entirely software, management of the entire cloud footprint is increasingly managed by DevOps automation. DevOps automation and its implementation are crucial to capturing benefit out of the digital transformation to the cloud. The transition from manual administration to DevOps automation is a paradigm shift for both infrastructure administrators and application teams.

From Asperitas Consulting, Derek Ashmore will guide you through the different types of DevOps automation commonly used and how they support capturing benefit from your cloud footprint. Common advantages that automation can provide in the cloud include the following:
- Increased speed to market for application capabilities
- Increased productivity for IT staff
- Increased scalability and performance of applications
- Increased Availability and Business Safety
- Automated enforcement for security and compliance
- Increased Cost-effectiveness


Derek will guide you through automation uses and tactics to help the organization be more effective and capture the benefits listed above. Additionally, Derek will review common strategies used by organizations that don't work. This presentation comes with tales from the field. This presentation targets DevOps architects with any cloud and their managers.

Test (execution) automation has been a goal since the earliest programs were written. The mechanics of automated tests have evolved with the technology used to build software, but the fundamental problems of test automation have not changed. Establishing a consistent environment, creating integral and re-usable test data, handling genuine failures, false negatives (and positives), tear-down, and clean-up. These are well-understood challenges. Developers and testers battle with flaky environments, test frameworks, and buggy software under test much the same way they always did. There is little debate about these technical or logistical matters.

The use of unit test frameworks to test low-level components and integration is well-understood and usually most effective. But where the user interface is graphical and/or where tests of larger, integrated systems are required, test automation is more challenging. These tests tend to be longer, slower, and more complex and consequently, they are harder to write, debug, and maintain. These tests also run relatively slowly. All in all, long-winded, complex tests are flaky and far less efficient and economic. Two models dominate people’s thinking in this area – the four-quadrant model and the test automation pyramid. They have some value, but practitioners and managers need something better to guide their thinking.

This is the “state of automation” and has been for many years.

In this talk, Paul sets out a way of thinking about testing and test automation that helps to answer the strategic questions: What does test automation really do for us? When and how is automation the right choice? How do we justify automation? Can automation replace testers? What new tools and skills do we need to implement automation in the future?

Companies are moving to security automation to protect their software and assets. In this presentation PwC and Uleska will discuss the trend towards DevOps and Digital Transformation, and the risks that introduces for companies. Learn about the current problems with DevOps Security, scalability, and effective regulatory coverage through DevSecOps.

Key takeaways will include:
• How to scale DevSecOps
• How to move from measuring inherent risk with software, to residual risk, automatically, and at scale
• What are the current best practices we see in the industry, and what are the blockers
• What will the future of security automation look like

Serverless functions are driving the fast adoption of DevOps development and deployment practices today. To successfully adopt serverless functions, developers must understand how serverless capabilities are specified using a combination of cloud computing, data infrastructure, and function-oriented programming. IT Ops teams also need to consider resource optimization (memory and CPU) and high-performance boot and first-response times in both development and production environments for faster time to market/service. What if we didn’t have to worry about all of that?

In this session, I’ll be speaking about what kinds of open source projects and tools enable you to write a serverless function with superfast boot and response times and built-in resource optimization. Then, you’ll understand how these capabilities take you to advanced DevOps practices as well as business acceleration. Furthermore, developers can avoid the extra work of developing a function from scratch, optimizing the application, and deploying it to Kubernetes.

Cloud Native is taking center stage in the enterprise I.T. cloud world. Netflix coined the term Cloud Native in 2013 and described its cloud goals as: Scalability, Availability, and Performance. While these core goals continue to guide the Cloud Native movement in the cloud application space, what really enables applications to be highly scalable, always available even during upgrades or updates, and truly performant is the end-to-end automated DevOps process that includes: continuous build, continuous integration, and continuous deployment. Cloud Native has no doubt extended the best practices of I.T. cloud computing into application development in the cloud. In this talk, we will take a look at what the all-encompassing Cloud Native application development is, and why DevOps is a critical and integral part of it. We will also see an example of a DevOps delivery “toolchain”, and discuss what some of the challenges are, as well as look at several popular tools and frameworks in this space.

As DevOps takes root at organizations, the day-to-day practices in IT change in ways that are foreign to many auditors. This talk discusses how and why these new practices can potentially improve compliance and accelerate audit practices.

The fundamental concepts behind Agile, DevOps and Artificial Intelligence are decades old,
but it has only been over the past few years where their combined and intertwined strengths
has amplified the power of each, and aggregately served as differentiator in enablement and
acceleration of digital transformation in organizations.

In this session we will review how the Triple-Helix approach helps enterprises identify their
most promising areas to go through the transformation as their best Value Delivery Ecosystems,
how it helps them establish the Roadmaps, Transparency and Trust, top-to-bottom and across
the organization, and how it allows them to turn digital transformation into an state of being,
sustained and safeguarded post-implementation.

Analysts are predicting that throughout 2021, we will continue to see the human element of DevOps shining through. Other predictions forecast that the role of AI and AIOps in DevOps teams will become more prominent and that DevOps will take a larger role in enterprise Digital Transformation efforts.

As DevOps teams continue to grow and adapt to trends and changes that have emerged from the pandemic, it’s important to take a closer look at these changes and trends.

Join this panel to learn what the emerging trends around DevOps are, and to hear best practices about how DevOps teams can continue to collaborate and thrive when dealing with new and increased pressures.
Topics of discussion will include:
- Key learnings DevOps team have experienced from the events of 2021
- What the future for DevOps teams may look like, and how it can help businesses innovate
- The most prominent trends impacting DevOps team and ways of working in 2021, from AIOps to new toolchains
- And more

As software engineers, we’ve seen the world of software development evolve in a myriad of ways. The most prominent transformation was the move from monolith to microservices. This growth meant that software became more distributed and complex in nature, with many moving parts. But how do we, as modern software organizations, keep up with this new and complex evolution of software? Taking it one step further- how do we ensure that we have continuous observability of our application?

This talk will discuss the topics of Monitoring and Observability, and how their symbiotic relationship is not only needed, but necessary, for modern organizations. First, we will discuss Observability Verticals like Tracing, Metrics, and Logging, as well as the standards emerging around collecting telemetry from your applications which many organizations are adopting including OpenTracing and OpenTelemetry. Then, we will do a quick demo of how your app can be instrumented with OpenTelemetry APIs to collect on the fly tracing data. Finally, we’ll do a deep dive into how you can augment the above monitoring/observability standards to allow for continuous observability of your application, ensuring you’re always in the know of what’s going on with your app.

Truly disruptive organizations understand that agile software delivery pipelines are at the heart of their digital transformation. However, while some organizations may understand this in theory, in practice the situation looks very different for most.

This research set assesses the current state of Software Delivery Management (SDM) and examines the impact of SDM adoption in the enterprise. The research consists of survey data and one-on-one interviews with key industry leaders and experts to gather and further refine the data on which this report is based.

In this talk, ASG CEO Mitch Ashley will share data from the research and show how organizations with mature SDM strategies are better able to quantify both the cost of delivery and the cost of delays in delivery. Additionally, the research will show why organizations are enjoying an improved ability to tie software features and their delivery to business impact and customer value. This presentation will also breakdown how an SDM strategy addresses the gaps and inefficiencies in an organization’s ability to deliver software, based on three key capabilities that help organizations increase their software delivery efficiency and effectiveness.

Top takeaways from this presentation include:

• Survey data and research to share the current state of software delivery management
• An understanding of what it takes to successfully execute a digital transformation strategy and why it’s imperative that organizations adopt SDM capabilities
• Three capabilities to help increase software delivery efficiency, including:
o Quantifying the impact of investment in software delivery;
o The capability of software delivery teams to communicate and collaborate;
o End-to-end visibility into the value flow of software delivery streams

In this webcast we’ll travel along the path of the development and operation of “PAD” system,
supported by DevOps practices and infrastructure.

This solution tracks the fueling charge of planes and helicopters by the principal oil company,
in all the Argentinian airports.

It’s composed of rugged tablets (front-end) running off-line (on-line when it’s possible), against
a cloud backend, all over the country.

The keys scenarios that our solution cover is:
- Extensive on-field surveys and device integrations
- Gas fueling to planes before international flights
- Flowmeters interconnection
- Corporate identity management
- Assure a 24x7 operation, 99.9% SLA

DevOps is driving incredible results for many companies, but many more are struggling and every team has lots of room to improve. Recent focus on the bigger picture of value streams and flow provides us a much better perspective and model for improvement. In this talk, I'll share some of what's working for leaders, and how you can see improvement with a little investment in the right areas.

I'll share:
- How to tackle the worst bottlenecks
- Where automation really matters
- Remote-friendly mapping for teams
- Strategies for driving alignment
- How to get metrics from mapping

The role of the IT department has changed in recent years and is more aligned with the business than ever. In 2020, as DevOps matures, what does this mean for the role of DevOps and Agile in delivering business outcomes?

Join this panel as DevOps experts explore what opportunities - and challenges - DevOps and Agile can create for the business. Points of discussion will include:

- Are businesses investing enough in DevOps and IT teams to enable them to remain competitive in a landscape of accelerated Digital Transformation?
- How can businesses ensure that they reap the rewards of investments they do make?
- If businesses do it right, what benefits can they expect?

As we look to momentous changes unleashed by technological advances like 5G, AI, Deep Learning/Machine Learning, AI Accelerator Chips, etc., supported by social changes leading to 9-to-5 jobs taking newer meanings with WFH with higher autonomy for business users. DevOps provides an opportunity for enterprises leapfrog to Industry 4.0 by leveraging their internal data, social media data and finding effective ways to analyze, learn, and inferencing the data from the millions of edge devices to give business users the power to take autonomous decisions within real-time and meet the regulatory and risk management requirements.

Traditional App Dev models that needed elaborate software lifecycle and testing, and an extended roll-out plan, will pose severe challenges in Industry 4.0, and it requires real-time updates rolled out to all users. The traditional models that relied on IT development, Implementation and Processes are now blurred as business users rely more on AI to perform many of the tasks being performed by business process organizations.

To achieve Industry 4.0, enterprises need to critically relook at their internal processes and work towards leveraging AI for many of the tasks that are being done manually today, and then push the inferencing from these AI tools to the end business users. Enterprises would need to rapidly push these inferences from AI tools to the end-users and at the same time keep constantly updating their learning, analysis and inferences on real-time basis from the millions of data generators from devices, users, and social media to ensure that the users always have most current AI inference on their devices. All these updates, including Cloud based machine learning, analysis and AI inferencing and all the business users devices (like mobile, laptops, tablets, AR/VR, wearables, etc., ) need to happen in real-time.

“No Time to Test” – an approach to starting the testing journey with people who think module testing is all you have to do.



You are called in by a development manager who is suffering because of crashes in the system causing outages at critical times and significant revenue losses. They know they have to do something about testing but doesn’t know how to get started or obtain buy in. The situation is that the system is huge and complex. To properly scope out a full functional and regression test plan might take years. At the same time the developers are not interested, providing the blame cannot be pinned on them.



The point of this session is to discuss how to present a strategy that will allow you to make a realistic start without promising the undeliverable.

The search for more efficient, quicker and cheaper testing has been ongoing for a long time. In the past test automation was frequently presented as the solution to this problem. These days it has become at least a small part of any modern software testing process. However, in the next four years the test automation market will grow 2.3 fold to over 25 billion USD.
But it’s not only the size of test automation that is growing, it’s also increasing in maturity. It is now better that ever before as the tools are getting to grow more advanced and the practices more mature.
We will share with you how test automation market is changing, what are the current hot trends, and what new opportunities these will bring to us. Some of the most interesting innovations relate to improving scope selection, execution and maintenance of the automated test pack, powered by AI and ML.
This talk will give a high-level, understandable introduction to what’s happening and is about to happen in test automation. The target audience is testers, developers and technical resources.

Over the last 15 years, organizations have had difficulty with the entire software delivery process, but two artifacts in particular became a recurring problem. The problem stems from the Goldilocks principle: one of these artifacts is much too big to overcome efficiently, and one of them is much too small to make a significant impact, so we need to find the one that is just right.

So what artifact is “just right?” As the user, what we really care about are the Features: the stuff we use and interact with all the time to make our daily lives better. However, the systems we have today haven't advanced to the point where software features are the nearest proxy for customer value. In other words, the feature must be at the forefront of the UI.

In this talk, I will share why features are the proxy for value and explore the different levels of abstraction for the “just right” aspect of a Feature in order to shift people's mindset from thinking in terms of Builds or Releases, to thinking in terms of the customer and business value. I will share tactics to address the Goldilocks problem and how to have these discussions at the right level of the software in order to make prioritizations, decisions, and discoveries.

What Attendees Will Learn:

A different perspective about software delivery, which will help them make better decisions about which features to pursue and builds/releases to postpone.

Learn why features are the future and how they are the perfect middle-ground between individual builds and major releases.

How to ultimately break free from the Goldilocks problem of software delivery.

Artificial Intelligence (AI) techniques are enjoying rapid adoption by all sizes of businesses across the world. However, evolving AI from
“Prototyping” activities to “Production” face many challenges, in large part due to the radically different development and deployment profile of
modern Machine Learning (ML) methods, and the range of practical issues that come with real-world use cases.

This webinar will identify the challenges and demonstrate how these challenges could be mitigated with a remarkably scalable, flexible and
extensible ML platform.