~/conference

SREcon24 Americas

site reliability engineers, platform engineers, observability engineers, engineering managers, cloud architects, security engineers, frontend engineers

observability 2.0 single event store; columnar telemetry storage (ClickHouse); OIDC for CI/CD credential rotation; high cardinality metric mitigation; sharding strategies and tooling; capacity reservations and autoscaling; synthetic monitoring design and orchestration; incident severity and triage models; cache inconsistency in distributed systems; migrating large search datasets; compliance-friendly continuous delivery; frontend reliability gaps

titleauthorlength
20 Years of SRE: Highs and LowsNiall Murphy27m
Starts from a concrete origin: production was managed by a forked cluster.py list, teams built babysitter to edit arrays at runtime, then evolved into Borg and…
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Scam or Savings? A Cloud vs. On-Prem Economic SlapfightCorey Quinn28m
Argues that cloud is usually chosen for speed and features, not lower cost, and that moving back on‑prem is rare except for small proofs of concept or…
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Is It Already Time To Version Observability? (Signs Point To Yes.)Charity Majors39m
Argues observability needs a major-version bump: Observability 2.0 replaces fragmented metrics+logs+traces with a single source of truth of wide structured…
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Capacity Constraints Unveiled: Navigating Cloud Scaling RealitiesKevin Sonney, Marc-Andre Dufresne29m
Elastic Cloud runs across 64 regions on four CSPs with roughly 40,000 hosts supporting about 50,000 deployments, and capacity shortfalls happen despite…
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Sharding: Growing Systems from Node-scale to Planet-scaleAdam Mckaig37m
Stripe runs a multi-petabyte cluster and the concrete advice is: extract a stable shard key, map it to shards, then iterate — start with read replicas (often…
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Product Reliability for Google MapsMicah Lerner, Joe Abrams25m
Maps reliability shifts from server SLOs to direct user signals for a billion monthly users, run by a ~20‑person SRE team, claiming it catches issues server…
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Build vs. Buy in the Midst of ArmageddonReggie Davis32m
A 10-person SRE team collapses to 3, rebuilds an in-house incident tool Riot (Go), and discovers rapid commit churn, hidden maintenance costs and a…
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Compliance & Regulatory Standards Are NOT Incompatible with Modern Development..Charity Majors37m
Argues that no law forbids practices like continuous deployment, observability-driven development, feature flags or testing in production and shows real-world…
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The Ticking Time Bomb of Observability ExpectationsDavid Caudill38m
Argues that “monitor everything” plus vendor-driven marketing creates runaway cost and noise: observability often consumes 20% of cloud bill, floods teams with…
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Synthesizing Sanity with, and in Spite of, Synthetic MonitoringDaniel O'Dea44m
Four years of in-house work yields a concrete stack: Pollinator (browser runners) and PM2 for orchestration, used by ~30–40 teams across Jira. Tests run on a…
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Migrating a Large Scale Search Dataset in Production in a Highly Available...Leila Vayghan20m
Shopify migrates Elasticsearch data across GCP regions while running clusters on GKE, using CFA for the indexing pipeline and SQL as the primary store. The…
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OIDC and CICD: Why Your CI Pipeline Is Your Greatest Security ThreatMark P Hahn, Ted Hahn17m
Claim: CI pipelines hold long-lived credentials that leak and become the largest attack surface, so replace static tokens with OIDC tokens and tie them to…
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When Your Open Source Turns to the Dark SideDotan Horovits34m
Relicensing and sabotage are real risks: Terraform → BSL and HashiCorp’s fork ecosystem lead to OpenTofu (Linux Foundation) uptake; Elasticsearch → SSPL →…
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The Sins of High CardinalityJef Spaleta20m
Prometheus metrics with free‑form labels like source/destination IPs and trace IDs cause explosive series growth — simple examples jump from 125 to 2,500 lines…
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Optimizing Resilience and Availability by Migrating from JupyterHub to the...David Hoover, Alexander Perlman19m
Migrating from JupyterHub to the Kubeflow Notebook Controller replaces a single-replica Hub API and in-memory CHP routing with a Kubernetes-native operator…
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99.99% of Your Traces Are (Probably) TrashPaige Cruz35m
Sampling reduces trace volume by design: use OpenTelemetry SDKs and the OpenTelemetry collector with head (probabilistic, rate-limit, adaptive) and tail…
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Meeting the Challenge of BurnoutChristina Maslach38m
Burnout is an occupational phenomenon from chronic workplace stressors, not a personal illness, and WHO’s 2019 review of 40 years of research frames it as a…
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What We Want Is 90% the Same: Using Your Relationship with Security for Fun..Lea Kissner31m
Claim: SRE and security want about 90% of the same outcomes and can combine levers to avoid surprises. Evidence: random failures scale with size (law of large…
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Thawing the Great Code SlushMaude Lemaire38m
After October 2020 outages a live, Zoomed change advisory board (CAB) freezes Chef repo for seven months and costs roughly $5,000 weekly; response is to build…
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Resilience in ActionWill Gallego36m
Resilience is framed as adapting to the unexpected and building adaptive capacity — not perfect runbooks but the network, rituals and experiments that let…
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Navigating the Kubernetes Odyssey: Lessons from Early Adoption and Sustained...Raul Benencia35m
Journey from scavenged servers to global Kubernetes infrastructure shows concrete choices and outcomes: bootstrapped K8s v1.12 on CoreOS, replaced with Ubuntu…
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"Logs Told Us It Was Kernel – It Wasn't"Valery Sigalov30m
Investigation shows a 30% slowdown on a tiny loop and a clock_gettime jump from 17ns to 47ns that falls back to 23ns after boot-parameter fixes; root causes…
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What Is Incident Severity, but a Lie Agreed Upon?Em Ruppe35m
Argues severity is a negotiated artifact, not a truth: a spreadsheet used a percentage of events unavailable within 24 hours threshold that teams could not…
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Hard Choices, Tight Timelines: A Closer Look at Skip-level Tradeoff Decisions...Laura Maguire, Courtney Nash49m
Analysis mines a public corpus of over 10,000 incident reports (the the VOID), then runs a vignette study with 27 participants using scenario probes and…
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Triage with Mental ModelsMarianne Bellotti37m
Explains why experts triage by matching observations to a large library of small, testable mental models and gives concrete exercises: build process maps to…
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Defence at the Boundary of Acceptable PerformanceAndrew Hatch31m
Applies Jens Rasmussen’s Dynamic Safety Model to tech companies and claims the economic boundary is the strongest and the performance boundary the weakest…
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Lightning TalksLaura Nolan, Chitkala Sethuraman, Prathamesh Sonpatki, J. Paul Reed, Ted Hahn, Cail Young, Tushar Gupta, Adam Mckaig, Corey Quinn39m
Nine micro-updates: cognition research shows experts use recognition and mental simulation with limits of three moving parts and ~six steps so planning lets…
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System Performance and Queuing Theory - Concepts and ApplicationJeff Poole40m
Queueing theory explains why systems with 80% utilization still see long delays: variability in arrivals or service makes queues form and average residence…
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It Is OK to Be MetastableAleksey Charapko38m
Defines a metastable failure as a positive feedback loop that keeps a system degraded after a trigger and argues avoiding the metastable vulnerable state is…
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The Art of SRE: Building People Networks to Amplify ImpactDaria Barteneva39m
Argues that structured cross-team practice groups replicate choir techniques to amplify learning: sets up weekly 20–60 minute retrospective review “choirs”…
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Teaching SREMikey Dickerson46m
Designed course "Managing Complex Systems" at Pomona College that turns CS majors into SREs by having durable teams of 4–5 build and run a messy, real web app…
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Cross-System Interaction Failures: Don't Fail through the CracksTianyin Xu, Xudong Sun40m
Empirical study of 120 cross-system incidents and a random sample of 360 issues finds roughly 30% are CSI failures that arise only when systems interact…
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Gray Failure: The Achilles’ Heel of Cloud-Scale SystemsZe Li, Ryan Huang44m
Argues that subtle “gray failures” arise when built-in detectors disagree with application symptoms, calls this differential observability, and shows a…
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The Invisible Door: Reliability Gaps in the Front EndIsobel Redelmeier43m
Front end reliability focuses on crashes, TTI, jank and ANRs, not just CPU, and often requires high‑cardinality metrics and heavy sampling. A pilot team…
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Automating Disaster Recovery: The Ultimate Reliability ChallengeRicard Bejarano25m
Claims day Zero reliability is required and shows a pragmatic patch: Cisco automates cross‑region recovery for 215 services by shipping a standby data copy…
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From Chaos to Clarity: Deciphering Cache Inconsistencies in a Distributed...Akashdeep Goel, Prudhviraj Karumanchi15m
A distributed EVCache deployment spans 194 clusters and 22,000 servers storing 2 trillion items (14.3 PB) and its replication engine handles 30 million…
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Patching Your Way to Compliance with a Small Team and a Pile of Technical DebtFilipe Felisbino18m
A three‑pronged strategy cuts a mountain of patches down to manageable work: pick core technologies, decommission low‑value systems, and move remaining…
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Strengthening Apache Pinot's Query Processing Engine with Adaptive Server...Jia Guo40m
Apache Pinot at LinkedIn adds Adaptive server selection and Runtime query killing to handle 1,500+ brokers, 8,000+ servers, 4,500 tables and ~300K QPS…
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Taming the Linux Distribution Sprawl: A Journey to Standardization and...Raj Shekhar, James Fotherby16m
A company narrows dozens of distributions to two hardened images — Amazon Linux 2 and CentOS 7.9 — selected because they are RPM‑based, prioritize stability…
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Frontend Design in SREAndreas F. Bobak17m
Claims that SRE tooling must shift from training-heavy pet tools to scalable cattle-facing frontends that non-SREs can use; recommends three concrete…
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Measuring Reliability Culture to Optimize Tradeoffs: Perspectives from an...Kathryn (Casey) Bouskill18m
Conducted over 40 interviews and four survey waves, the team uses MAXQDA to code themes and finds 78% say teams value reliability while about half still can’t…
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Storytelling as an Incident Management SkillLaura de Vesine19m
Argues that incident narratives must show the logical progression of cause and effect not just who did what and when Tools: architecture diagrams, telemetry…
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Real Talk: What We Think We Know — That Just Ain’t SoJohn Allspaw37m
Argues that several SRE assumptions fail when tested: the lines of code metric is discredited (Capers Jones, 1995); a widely quoted 85% change claim (Gartner…
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What Can You See from Here?Tanya Reilly49m
Argument: your immediate context warps priorities and fuels pointless fights; concrete example: bike-shedding origin is a 1999 FreeBSD thread about sleep…
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