Track: Sponsored Solutions Track II

10:35am - 11:25am

How to Convince Your Manager to Address Technical Debt

In 2018, poor quality software cost U.S. companies an estimated $2.84 trillion, according to a recent report from the Consortium for IT Software Quality (CISQ). Despite developers spending roughly 60% of their time finding and fixing pesky application issues, errors still result in major software quality expenses.

Many of these high costs are attributed to known culprits, like SLA violations or lost revenue from an outage – but what about the hidden costs? The vast majority of contributing factors to that $2.84 trillion are hidden from plain sight, lurking beneath the surface of your application or buried in technical debt. Even errors that seem harmless can translate to a major pricetag from infrastructure and logging costs.

This session will break down the many costs – both obvious and hidden – that result from error-ridden applications, and provide you with a formula to help convince your manager to make technical debt a priority. It will also provide best practices for taking a proactive approach to improving software quality and reducing costs (and time wasted debugging).

11:50am - 12:40pm

You Only Have to Change One Thing to Do the DevOps. Everything.

10 or 15 years ago we would hear “agile doesn’t work” from lots of people. They had “used agile” on a project, and the project failed anyway. Most of the time a little investigation revealed that they didn’t really try it at all. Instead they worked much like they always had, just for two weeks at a time instead of several months.

The same thing is happening with people “doing DevOps”.

I strongly believe that the most important thing about a DevOps transition is the required changes in culture. But you can’t actually have self organized teams if you’re working on systems that are hard to build and deploy. You also can’t easily automate that build and deploy process if your architecture is hard to test.

In this talk I’ll point out several areas of focus when making the transition, and point out why it’s important that you change everything.

Culture change - DevOps is about culture first and foremost. I’ll talk about some of the organizational structures which can help in creating a sharing culture where the teams and the technology can thrive.

Modern architecture - Adopting a technical architecture which is more testable and changeable is key to the ability to move fast. Taking advantage of microservices and platforms (such as PaaS) can help with this.

Continuous Delivery - Continuous Delivery is more than just automating deployment. Making sure your software is going through things like security, performance and compliance testing in addition to “standard” tests. I’ll show ways to make sure your deployments are not only fast, but safe.

11:50am - 12:40pm

3 Levels of Improving, Continuously

I have a more elaborate vision for DevOps. I define it as a culture where a diverse set of identities, genders, roles, educations, and techniques work together to ensure a balanced and focused perspective for team, product, and users. I hear this term often used when referring to only technical roles, but this version includes marketing, UX, design, and sales.  

I’ll walk through the story of SnapCI, a now defunct continuous delivery tool, the unconscious silos the team built, how we broke them down, and one of the biggest mistakes me made when developing a new feature. I’ll also fast forward to how we built on those lessons learned and relentlessly worked towards improving our culture.

1:40pm - 2:30pm

Index-Free Log Aggregation With Kafka

We are seeing a rise in a new generation of logging solutions. Traditional approaches have been based on database indexes, but the next wave of log management platforms is a combination of techniques including streaming queries, in-memory processing, brute-force search, and filtering.  We call this *Index-Free Logging*.

In this talk, we will provide an overview of the advantages of Index-Free Logging, and how we’re implementing it in Humio, a new log analytics system with a novel storage and query engine for events logs and traces.  Humio was built from the ground up as a multi-tenant on-prem system so you can install it behind your own firewalls or in your own cloud infrastructure.

In a Humio setup, we then use Kafka for two things: buffering ingest and as a sequencer of events among the nodes of a Humio cluster. We love Kafka — it has made implementing a distributed system significantly easier than if we had to do the distributed queue from scratch. Using Kafka as a building block has allowed us to focus our attention on building a fast and easy search experience.

2:55pm - 3:45pm

Mobile Apps: To SQL or Not to SQL

Throughout the course of the mobile apps revolution, the world has seen many changes in the technology landscape. What started off with fewer than 500 apps has quickly surpassed the millions mark. As languages, platforms, and styles have come and gone one thing, above all else, has persisted; data.

Come join us as we examine mobile data usage trends, and navigate through the plethora of options currently available for wrangling it all. More specifically, we’ll take an in-depth look at the two main database options: SQL and NoSQL. We’ll learn what each is, and when to use them to solve business critical problems in mobile. As developers we know when it comes to technology options there’s no silver bullet, but you might be surprised how lop-sided the SQL vs. NoSQL debate is as it pertains to mobile.

4:10pm - 5:00pm

Experimentation for Speed, Safety & Learning in CD

How do companies like Netflix, LinkedIn, and booking.com crush it year after year? Yes, they release early and often. Look deeper and you'll find that all of these teams also build in fine-grained control and observability of the payloads passing through their CD pipelines, allowing them to ship faster, with greater safety, while focusing on observable customer impact (results), not just releases.

The lessons learned from early implementations of this approach (known as “shift right testing” or “feature experimentation”) have been published, but not widely read. This talk is a condensed summary of a decade’s worth of those lessons, followed by key takeaways that will equip you to achieve similar benefits in your own environment.

While this talk is part of the solutions track, it focuses exclusively on the industry leaders and best practices that inspired the Split commercial solution. There won't be any Split sales pitch or demo. For that, you'll want to drop by the Split booth in the exhibit hall before or after the talk.

#continuous delivery #observability #experimentation #data science #devops

5:25pm - 6:15pm

Tracing Is More Than Traces: The Insights in Trace Aggregates

The value proposition for distributed tracing is well-understood: assembling and visualizing end-to-end transactions helps to identify latency bottlenecks and provides a head-start on problem diagnosis. Yet the data from traces – when aggregated – can reveal much more, and can do so with greater precision and certainty. This talk presents the profound insights trace aggregates help unlock, including sources of resource contention, latency anomalies in the context of service infrastructure, and correlations of metrics with high-cardinality characteristics of the distributed system. The talk demonstrates, using concrete examples, how novel applications of aggregated traces reveal new opportunities for performance improvements. However, aggregation is not possible without a standardized tracing output format, as well as a proliferation of traces via cloud-native service mesh integration.