Conf42 Observability 2025
| title | author | length |
|---|---|---|
| Detecting Anomalies in Logs with Time Series Analysis | Yury Nino | 16m |
Claims that log-derived time series let teams catch cost spikes early and shows a working pipeline: Cloud Logging via log router -> BigQuery, aggregate… | ||
| Access is the New Breach: Observability Must Start with Identity | Cynthia Akiotu | 23m |
Claims that 80% of breaches are related to identity and that observability must correlate identities with system events drive the concrete agenda: run… | ||
| Measuring Serverless Apps in Amazon Bedrock | Hazel Andrea Saenz Giron | 28m |
Shows concrete instrumentation and a working demo: a small serverless app deployed to AWS that logs model invocations, tokens and responses to CloudWatch… | ||
| Making Open Source Profitable | Anastasiia Zvenigorodskaia | 28m |
EpicMax builds a Vue.js admin dashboard, Epic Spinners CSS kit, a component library (VCI) and VJ Talks meetups and reports concrete numbers: the admin hits… | ||
| Modular Architecture | Anusha Reddy Guntakandla | 10m |
Claims concrete measurable outcomes: a product catalog migrated to a standalone service with Elasticsearch cuts query time by 47%, customer onboarding… | ||
| From Blind Spots to Insights | Shikha Gurjar | 14m |
Claim is concrete: observable identity stacks using biometrics, AI, blockchain and instrumentation cut meantime‑to‑detection by 87% reduction in meantime to… | ||
| Navigating Digital Landscape with Intelligent Full Stack O11y | Manik Kashikar | 14m |
Claims that 89% lack complete visibility, shows an example where 40 milliseconds increase -> 2% conversion drop, and outlines a maturity path from siloed… | ||
| O11y Starts Before the Outage: Monitoring for Modern Systems | Palak Bhawsar | 12m |
Synthetic monitoring claims to catch failures before users do with concrete results such as payment gateway API crashed at 2:00 a.m. discovered after 50… | ||
| Serverless AI's Rise: Revolutionizing ML Deployment | Shreya Gupta | 18m |
Architecture shows stateless function containers packing models from 75 MB to 1.8 GB and running on serverless platforms with reported inference latencies like… | ||
| Bringing Clarity to gRPC through GoFr: The Role of Observability | Divya Darshana | 14m |
Gofr claims to make gRPC observable with zero manual instrumentation: a CLI generates server scaffolding (greet.pb.go and greet_grpc.pb.go) that wires context… | ||
| Next-Gen Observability: reduce MTTR | Kirti Ranjan Parida, Sarav Jagadeesan | 13m |
Operates across four clouds, 20 regions, 600+ Kubernetes clusters ingesting about 60 TB logs/day (3.8 trillion docs/month, ~15 PB on S3), consolidates sources… | ||
| AI-Powered Observability in Semiconductor Design | Naveen Desai | 04m |
Claims measurable gains: up to 40% faster design cycles and reduction of projects stuck in delays from an asserted 87% figure. Uses an AI-powered monitoring… | ||
| Threat Modeling for O11y: From Blind Spots to Actionable Insight | Srikanth Potla | 14m |
Claims concrete attack chains and fixes: a Grafana exploit leads to exposed dashboards, API keys appear in plain logs, then Prometheus lateral movement gives… | ||
| AI-Powered Anomaly Detection for Telecom Service Reliability | Ajay Averineni | 11m |
Claim: anomaly detection cuts mean time to repair by 41% mean-time-to-repair reduction across telecom services handling up to 25 terabytes of telemetry per… | ||
| AI-Driven O11y for Massive AWS Serverless Workflows | Vamsi Praveen Karanam | 11m |
APIX wires OpenTelemetry spans from every AWS Step Functions branch into a Fargate collector, feeds 60s windows to a two‑layer graph neural network (about 1.2… | ||
| AI-Powered O11y in Microservices Architectures | Srinivas Sriram Mantrala | 25m |
Claims concrete wins: uses Grafana dashboards for visualization and queries, maps metrics logs and traces to SLOs tied to revenue and latency, applies ML for… | ||
| Building Resilient Asynchronous Commerce Systems | Anup Raja Sarabu | 23m |
Claim: observability is the linchpin that makes async event‑driven commerce reliable. Concrete moves include decoupling payments and building an async BOPIS… | ||
| Mastering Observability in Distributed Systems | Raghavender Puchhakayala | 12m |
Claims concrete outcomes: 73% reduction in meantime to resolution, 42% cost savings, 91% uplift in customer satisfaction and a 99.99% availability target that… | ||
| Transforming Public Sector Observability | Indraneel Madabhushini | 16m |
Shows a concrete roadmap: build pipelines from legacy mainframes to cloud, normalize telemetry into Azure data lake / Snowflake, run ML in Data bricks for… | ||
| DataOps: Accelerating Digital Transformation | Lakshmi Narayana Gupta Koralla | 26m |
Claims concrete outcomes: CI/CD pipelines for data using Apache Airflow and containerized runs with Docker automate deployments; stream processing with Apache… | ||
| Dashboards, Not Drama: How Fixed-Cost Clouds Made O11y Fun Again | Denish Tomar | 10m |
A concrete claim: switching to a fixed-cost cloud model with platform-integrated observability cuts incident debugging from ~2 hours to 25 minutes vs ~2 hours… | ||
| Designing the Right Observability Stack in AWS Cloud | Prudhvi Raj Atluri | 20m |
Claims a concrete checklist: map workload requirements to specific AWS services to avoid over‑ or underprovisioning, centralize telemetry into S3/OpenSearch… | ||
| Operational Efficiency & Collaboration in Nonprofits | Sekhar Midathana | 25m |
Claims a Salesforce Nonprofit Cloud deployment that unifies donor, volunteer and program data, automates workflows, and adds real‑time dashboards. Cited… | ||
| Cloud-Native O11y: Building Scalable Enterprise Systems | Vamsi Krishna Munnangi | 17m |
Claims a 40% faster incident resolution and 25% resource efficiency during peak traffic, with 200 ms anomaly detection and 58% faster incident detection… | ||
| Cloud-Native Observability for Financial Systems | Siva Prakash | 21m |
Claims concrete outcomes: a 99.4% anomaly detection accuracy and 87% reduction in false alerts from a system built around graph-based topology analysis and… | ||
| Emotional Intelligence in the Cloud | Karthik Mohan Muralidharan | 27m |
Claims include concrete metrics: typing rhythm analysis and mouse/sequence features feed ensemble models achieving around 79.5% classification accuracy, cloud… | ||
| Observing the Invisible: Real-Time Financial Risk Detection | Diliprao Boinapally | 08m |
Concrete system narrative: a cloud native pipeline built with serverless event-driven functions feeding Apache Spark + Airflow and instrumented with… | ||
| Enhancing Security and Trust in Modern Banking | Subrahmanyam Mamidi | 12m |
Claims specific measurable outcomes: distributed tracing with anomaly detection reduces detection time to 99.8% accuracy and under five minutes, cutting a… | ||
| Next-Gen Cloud: Enabling Secure and Seamless Cross | Naga Swetha Kattula | 13m |
Claims specific wins: 94% of enterprises run multicloud and each added cloud raises integration complexity by about 70% while a comprehensive integration… | ||
| Aircraft Observability Revolution | Divakar Duraiyan | 12m |
Digital twin systems claim to ingest 1.2 terabytes per day from 200,000+ signals per aircraft, run onboard edge-to-cloud architecture with 20 kHz vibration… | ||
| Optimizing Multi-Cloud Platforms with AI Ops and FinOps | Ganeshkumar Palanisamy | 17m |
Claims a unified observability platform that correlates metrics logs and traces across AWS GCP and Azure, with ML models that detect incidents 67% faster and… | ||
| Unifying Multi-Cloud Data for Actionable Intelligence | Ravi Kumar Amaresam | 15m |
A concrete system claims an AI-driven integration framework built from standardized connectors, adaptive security and intelligent orchestration and delivers… | ||
| Journey from Broken Dashboards to O11y Maturity | Chaitanya Reddy Krishnama | 21m |
Claims a concrete outcome: an observability QA framework that embeds Great Expectations, dbt, OpenTelemetry and Prometheus and Grafana into pipelines, adds… | ||
| Instrumenting at 10 years per second | Jean-Mark Wright | 27m |
Claims a concrete pipeline: KSI (config accelerated custom instrumentation) turns declarative capture configs into runtime hooks, using Python metaclass… | ||
| Writing Custom eBPF Programs for O11y: What You Need to Know | Sooter Saalu | 14m |
Shows an actual C eBPF program that compiles to bytecode, passes the verifier (no loops), and creates a BPF map for packet counters and events; demonstrates a… | ||
| Observability in Privacy Infrastructure | Krishna Ganeriwal | 12m |
Claims real numbers: billions of log events and petabytes of telemetry require subsecond processing to meet GDPR/CCPA fines up to 4% of revenue. Architecture… | ||
| RAG Beyond Chatbots | Vaibhav Fanindra Mahajan | 15m |
Argues that retrieval-augmented generation replaces static dialog trees by running query understanding, embedding with models like BGE or miniLM, and top-K… | ||
| Lighting Up Design Blind Spots | Pradeep Karanam | 11m |
An event driven observability layer connects ECAD and MCAD with a shared schema, immutable audit logs, and Kafka broker stream processor plumbing that emits… | ||
| O11y in the Evolution of AI-Era Networking Infrastructure | Bhaskararao Vakamullu | 20m |
Claims concrete upgrades: cites OpenTelemetry and tools like fiddler AI and erase AI for model drift and explainability, describes silicon-level telemetry and… | ||
| Using the activity logs to predict user behaviour | Alexandru Hang | 19m |
Claims a working prototype that predicts each user’s next page from activity logs and uses the forecast to preload data and estimate server load. Model uses… | ||
| Logging in the Age of Cost-Cutting | Venkata Madhu Prateek Reddy Kambala | 20m |
Concrete numbers and actions: Uber cuts debug ingestion to 5% retained and saves about $8M a year, then later compresses massive jobs with 169:1 compression to… | ||
| Building Resilient Healthcare Systems | Brahmanand Reddy Bhavanam | 08m |
Seventy-three percent of healthcare orgs lack comprehensive visibility, so the concrete fixes matter: implemented end-to-end distributed tracing across service… | ||
| O11y-Driven Quality Assurance for Health Insurance | Subash Lekshmi Velayudhan | 14m |
Health-insurance QA shifts to measurable outcomes: 43% revenue loss during outages and uptime targets of 99.99% drive adoption of distributed tracing across… | ||
| Cloud-Based Data Integration is Transforming Enterprise Data | Sudhakar Guduri | 08m |
Claims specific cost and time gains: 30–40% reduction in total cost of ownership, 60% faster time to insight and 6–8 week deployments versus 8–12 months. Lists… | ||
| Seeing Beyond the Signatures: Federated Multisig O11y | Onyebuchi Mark Irozuru | 09m |
Describes a deployed observability stack using Grafana Alloy with Prometheus metrics, OpenTelemetry traces and a centralized Loki endpoint that aggregates logs… | ||
| Shrinking the Observability Bill | Aritra Ghosh | 16m |
Claims a concrete 40% cost reduction from dropping health‑check logs, switching to Prometheus histograms and moving cold data to cheap object storage. Presents… | ||
| Real-Time Edge Observability: Security Monitoring | Chintan Udeshi | 19m |
Claims concrete outcomes: deploy lightweight microagents to stream CPU/memory and behavioral signals, correlate across devices, and trigger automated isolation… | ||
| Power of O11y with FLUENT BIT in AWS EKS environment | Dharmendra Ahuja | 34m |
Shows a reproducible pipeline: deploys Fluent Bit as a DaemonSet via Helm on an AWS EKS cluster created with eksctl, configures IAM OIDC + service account and… | ||
| Turning Synthetic Traces into Gold: Monitoring for User Journeys | Sudeep Kumar | 14m |
Claims a centralized tracing platform handles 300 million spans per minute and ingests telemetry at the scale of millions of traces and petabytes of logs, uses… | ||
| Seeing Through the Chaos of Modern Systems | Naga Murali Krishna Koneru | 22m |
Claims that OpenTelemetry standardizes telemetry and that an OpenTelemetry Collector centralizes receivers processors and exporters and reduces resource use… | ||
| Observability-First Kafka: Engineering Visibility at Scale | Abhishek Walia | 33m |
Shows concrete instrumentation: enable JMX, scrape Kafka with Prometheus JMX exporter, push client metrics via KIP-714 on Kafka 3.7+, and centralize logs as… | ||
| Scaling Observability for Real-Time Personalization Engines | Sai Kumar Bitra | 28m |
Claims concrete wins: up to 40% revenue lift from better personalization, incident case where ETL fixes restore relevance and debugging time drops 3x, and… | ||
| Observability in Modern Treasury Trading Platforms | Ganesh Marimuthu | 17m |
Claims concrete wins: observability handles 8.4 terabytes of market data daily and algorithmic trades at 145 microseconds, distributed tracing reduces mean… | ||
| OpenTelemetry Is Not a Silver Bullet | Meletius Mgbeodichimma Igbokwe | 28m |
Claim: OpenTelemetry is a foundation not a finished product; deployments hit real failures like collector crashes under preload, version drift causing weeks of… | ||
| OpenTelemetry or OpenTeleMessy? | Narendra Reddy Sanikommu | 09m |
Claim: OpenTelemetry Collector centralizes export but forces large, brittle YAML configs and lots of auth/connectivity fiddling. Evidence: language SDK… | ||
| Building lightweight observability system for Lean Teams | Vignesh Iyer | 11m |
Concrete setup steps and tradeoffs: recommends deploying Fluentd, Prometheus, Jaeger and Grafana with quick commands and Helm charts, shows using kubectl apply… | ||
| Observability 2.0 - Much more than just logs,metrics and traces | Neel Shah | 11m |
Claims that OpenTelemetry collector (receiver → processor → exporter) cuts downtime by standardizing telemetry and routing to multiple back ends, that eBPF… | ||
| Navigating the What, Where, and When of Your Frontend App | Vadim Tsaregorodtsev | 16m |
A Confluence observability passport collects concrete checks: SLI/SLO/SLA (example SLA 99.9% with a 0.1% error budget), an SLO like 95% of requests under 200… | ||
| Building Zero-Instrumentation Observability | Isala Piyarisi, Nilushan Costa | 38m |
Builds a Kubernetes-attached observability stack using fluent bit, open search and Prometheus, with Fluentbit as a DaemonSet, OpenSearch as distributed storage… | ||
| Beyond the Dashboard: Build End-to-End O11y | Ashwin Das Gururaja, Devang Gaur | 30m |
Claims concrete outcomes and actions: an end to end observability stack at Adobe scales millions of transactions, detects a 2% payment failure trend that would… | ||
| Triple Threat: AI Technologies Reduce Testing Costs | Jyotheeswara Reddy Gottam | 06m |
Three concrete claims: generative AI autonomously produces comprehensive test scripts, predictive analytics focus tests on high‑risk modules using historical… | ||
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