CONFERENCE DAY TWO

“Patterns Led Observability” offers out-of-the-box patterns that can be adopted across all layers of the Observability Value Pyramid, which allows our internal customer development teams ease of function to consume and get moving quickly. Standardizing development practices with leveraging AI and automation technologies, whilst maintaining careful control over costs. This session will delve into the unique observability challenges and opportunities faced at JPMorgan Chase - with upwards of 40k internal developers ready and eager to consume our tooling. Leveraging standardized practices to streamline the adoption of strategic tooling, ensuring consistent and

efficient observability across complex systems, leveraging proven cost effective methods for integration that scales to volumes in the multi-TB-per-day range.

Patterns Led Observability in Financial Services: Understanding the specific needs and constraints of the financial sector and which observability patterns can address them.

Strategic Tooling and Standardization: How standardized practices facilitate the seamless integration of observability tools, driving efficiency and reducing operational complexity.

Leveraging AI and Automation: Exploring the role of AI and automation in enhancing observability, from predictive analytics to automated incident response.

Cost Control Strategies: Techniques for balancing advanced observability capabilities with budgetary constraints, ensuring cost-effective implementation and operation.

Gavin McCallum

Observability Architect - Engineering Platforms and Experience
JP Morgan Chase & Co.

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Jonathan Lowe

Executive Director
JPMorgan Chase & Co.

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Session Available For Sponsorship

As observability data volumes explode, so do the costs - leaving many organizations struggling to balance visibility with financial sustainability. This panel explores how engineering, platform, and finance leaders are working together to control observability spend without sacrificing critical insights. We’ll discuss strategies for smarter data collection, tooling consolidation, and aligning observability investments with business value.

• Understanding where observability costs originate — and how to make them visible.
• Tuning telemetry pipelines to reduce volume and noise.
• Choosing between high-fidelity data and cost-effective sampling.
• Evaluating ROI across vendors, open-source tools, and internal platforms.
• Fostering a culture of cost-awareness among engineering teams.

Marta Lima

Engineering Lead - Observability
Wise

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Session Available For Sponsorship

In this session, Kristina will show how Electrolux built an internal developer platform (IDP) that integrates observability and runbook knowledge into every workflow. By shifting incident resolution upstream, developers own more of the troubleshooting, and SREs get time back for high-impact projects. Specifically, the session will cover:

• Designing an IDP that bakes in observability from the start, ensuring every piece of infrastructure is monitored and auditable by default
• Handing off incident triage and resolution to development teams.
• Freeing your SRE team from routine tickets so they can focus on innovation.
• Decentralizing tribal knowledge by embedding it into your platform.
• Why open source in big companies can provide extra capacity and fuel team motivation.

Kristina Kondrashevich

SRE Product Manager
Electrolux

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Session Available For Sponsorship

GroupOn operates as a much leaner business today as a public company than in its days as a unicorn startup. As the company has scaled down, the engineering team faces the challenge of maintaining and reengineering a system built without cost constraints to be more cost conscious and sustainable. This session explores how GroupOn is tackling legacy complexity, consolidating tooling, and finding the right balance between buying and building to right-size for the future.

• How GroupOn’s tech stack became too big to manage efficiently
• The hidden costs of legacy tooling in smaller orgs
• Strategies for consolidation, integration, and simplification
• What we’re buying vs. what we’re building
• Lessons learned from cleaning up a system built for scale

Nick Simmonds

Infrastructure Engineering Manager
Groupon

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With the scale and complexity of modern systems, human-driven observability alone is no longer enough. This session explores how AI and machine learning are transforming observability - enabling proactive anomaly detection, intelligent alerting, and faster root cause analysis. Learn how enterprises are integrating AI/ML into their observability stacks to surface signals earlier, reduce noise, and accelerate response times.

• Applying machine learning to detect anomalies in high-volume telemetry data.
• Using AI to correlate logs, metrics, and traces for faster root cause analysis.
• Reducing alert fatigue with intelligent alerting and event de-duplication.
• Embedding AI-driven insights into incident response workflows.
• Evaluating the limits of automation and keeping humans in the loop.

Culture is as critical to reliability as any tool or dashboard. This session explores how leading organisations are building SRE cultures rooted in real-time observability - where teams are empowered to detect, respond, and learn from incidents proactively. We’ll look at how observability is shaping everything from on-call practices and team structures to incident reviews and cross-functional collaboration.

• Creating shared ownership of reliability across engineering and SRE teams.
• Embedding observability into the daily routines of developers and operators.
• Using real-time insights to inform decision-making and reduce burnout.
• Designing on-call and escalation models that scale with system complexity.
• Reinforcing resilience through post-incident learning and blameless culture.

Colm Campbell

Head of Engineering
The Gym Group

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Modern Site Reliability Engineers (SREs) are drowning in alert fatigue, repetitive toil, and late night pages. But what if you could flip the script using AI? In this talk, we explore how a solo engineer empowered their SRE practice by building an AI-driven ChatOps bot and anomaly detector - automating the triage of alerts, generating root-cause hints, and triggering runbooks autonomously. What started as a survival tactic evolved into a transformative shift: from reactive firefighting to proactive reliability engineering. Alongside this, the speaker delves into how solo side-projects using code-generation agents and no-code orchestrators helped fast-track innovation,

proving that individual contributors can ship impactful tools without a team. The session rounds out with an honest discussion of what it takes to bring these innovations into a larger engineering culture—navigating the dynamics of engineer-led experiments, middle-management resistance, and the need for CTO-level sponsorship.

• Break the Cycle of Toil: Learn how AI-driven bots can handle alert triage, automate runbooks, and reduce MTTR without sacrificing human oversight.
• Proactive Reliability through Automation: See how anomaly detection and context-aware assistants can help SREs transition from reactive responders to strategic infrastructure engineers.
• Empowering the Solo Engineer: Explore how individual contributors can prototype and deploy high-impact tools using AI agents and no-code workflows.
• Navigating Organizational Friction: Understand the political and cultural hurdles of implementing AI-based tools in different organizational layers (engineer-led, manager-skeptical, CTO-backed).
• Blueprint for Bottom-Up Innovation: Get a practical framework for piloting and scaling AI-based SRE tools inside complex engineering orgs.

Daniel Murphy

Head of SRE
PwC

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