Site Reliability Engineering (SRE) 2025
2025-04-17
-- online --
who it's for
site reliability engineers, platform engineers, observability engineers, incident managers, devops engineers, engineering managers, cloud architects
topics
sub-50ms IAM architectures; ml model monitoring and drift detection; OpenTelemetry instrumentation; ai-powered anomaly detection and self-healing; chaos engineering with ai; serverless with Kafka integrations; eBPF for cloud-native observability; slo-based reliability management; gitops for delivery pipelines; event-driven microservices migration; cloud security posture management; zero data loss architectures
| title | author | length |
|---|---|---|
| What Real Housewives Taught Me About Postmortem Meetings | Paige Cruz | 25m |
Seven concrete practices and one incident name: attach bring receipts—link dashboards, traces, and exact time ranges so anyone can replay the timeline; pair… | ||
| Zero Downtime ML Deployments | Payal Godhani | 21m |
Claims a concrete deployment pattern: an ML monitoring service sits next to the prediction service, ingesting raw inputs and emitted predictions and computing… | ||
| Zero to Fifty: Sub-50ms IAM Architecture for Gaming Platforms | Aditi Mallesh | 08m |
Claims a sub‑50ms authentication baseline with measured 32 ms average and business lifts (18% drop in abandonment, 27% higher retention). Architecture uses… | ||
| Application Resilience - Whose Job Is It Anyway? | Veliswa Boya | 13m |
Claim: application resilience and rapid innovation coexist only when teams adopt a shared responsibility model and concrete practices rather than slogans. The… | ||
| SRE Principles for High-Speed Infrastructure Monitoring | Jena Abraham | 12m |
Concrete metrics and mechanisms decide: claims of 85% faster detection and 65% fewer false alerts, 93% SLO coverage, 68% of extended outages tied to visibility… | ||
| Applying SRE Principles to SDOH: Resilient Healthcare Systems | Roja Perumandla | 15m |
Claims concrete numbers and runnable steps: rural pilots report 86% screening completion after embedding standardized SDOH questionnaires in EHRs, and 28%… | ||
| Navigating SRE/Incident Management | Shaalmali Raychaudhury | 13m |
Claims that incident, problem and change processes integrate to cut downtime by enforcing SLAs and a priority matrix, illustrated by a Black Friday outage and… | ||
| AI-Driven Self-Healing Infrastructure | Vijaybhasker Pagidoju | 13m |
Claims include 85% incident healing accuracy, concrete tools like Netflix ChAP, and measured outcomes: Netflix cuts MTTR 30–50% and prevents 200+ outages in… | ||
| Ensuring Sustainable Digital Inclusion for Elderly Users | Rinku Mohan | 14m |
Dataset covers 2019–2023 across five high‑income and five middle‑income countries and claims three principal causes of exclusion: socioeconomic, health, and… | ||
| Scaling Financial Inclusion: High-Performance Payment Systems | Utham Kumar | 07m |
Claims concrete outcomes: a rural healthcare payments platform moves from 78% to over 99% transaction reliability using an offline-first architecture with… | ||
| AI and Chaos Engr: Smarter Failure Testing for Resilient Systems | Rahul Amte | 09m |
Claims that AI auto-generates and prioritizes chaos scenarios, ties into observability (EC2, Prometers, OpenTelemetry) and injects faults via tools like chaos… | ||
| Contextual understanding using Generative Artificial Intelligence | Pushpalatha KR | 03m |
Pipeline converts uploaded documents to text, produces high-dimensional embeddings, stores vectors in a vector DB, and runs semantic similarity search to pull… | ||
| SRE vs DevOps: The Difference & Why It Matters | Tajudeen Oyindamola Tajudeen | 08m |
Claims that SRE originated at Google and that error budget policy can block releases are backed by specifics: an example of 43 minutes of downtime becomes a… | ||
| SRE Challenges and Solutions for High-Availability CCAI Systems | Raghu Chukkala | 11m |
Targets 99.99% uptime and sub‑300 ms latency, claims automation cut MTR by 73% and cost by 30–40% through SLO‑driven rightsizing. Shows a four‑layer… | ||
| AI-Powered Mainframe Modernization | Sanath Chilakala | 16m |
30-year-old core banking system with 5.2 million lines of COBOL and ~400 dependent apps undergoes AI-driven modernization using automated dependency mapping… | ||
| AI-Driven Cloud Solutions: Overcoming Challenges | Sanjeev Pellikoduku | 09m |
Claims include a 35.6% market growth, 68% adoption and 31% efficiency gains, plus concrete outcomes like 92% reductions in privacy instance and a 78% reduction… | ||
| Human-AI Symbiotic Robotics | Rajarshi Tarafdar | 13m |
A surgical robotic platform with pyramidal architecture—advanced sensor fusion, ML prediction engines, precision actuators and bidirectional interfaces—claims… | ||
| Synthetic Data in AI | Pradeep Kumar Vattumilli | 10m |
Claims include 60% of data synthetically generated by 2025 and models trained on synthetic data reaching 84% accuracy while cutting development cycles by 40%… | ||
| Leveraging Serverless architecture with Confluent Kafka | Vlad Onetiu | 36m |
A real system is built: AWS Lambda producers and consumers wired to Confluent Kafka topics and partitions, backed by DynamoDB and SQS dead‑letter queues… | ||
| Architecting Resilient Multi-Cloud Infrastructure | Sai Prasad Mukala | 19m |
Claims concrete outcomes: MTR reduction 68%, operational cost savings 47%, 3.2x incident response acceleration from an AI diagnostic and triage stack… | ||
| Transforming SaaS with Serverless Architectures | Srikar Kompella | 36m |
Claims list concrete numbers tools and outcomes: AWS Lambda, Aurora Serverless, API Gateway, EventBridge, Kinesis and QuickSight power event driven pipelines… | ||
| Transforming Enterprise Frontends with Micro-Frontend Architectures | Nasir Sayed | 11m |
Micro-frontend migration claims concrete wins: teams cut deployment time by 60%, report 70% more autonomy, and see regressions drop ~40% while release cadence… | ||
| Revolutionizing Data Engineering for Space Exploration | Siddhartha Parimi | 08m |
Claims concrete workloads and numbers: hundreds of gigabytes per mission per day, ISS nearly a terabyte daily, James Webb about 40 GB/day, and systems handling… | ||
| Integrating Automation, BPM, and SRE for Digital Enterprise | Mohit Sachdeva | 09m |
Slides claim 73% of organizations are already on an intelligent automation journey, 58% scale AI-enabled automation, and many see ROI in ~11 months with… | ||
| Using Oracle Tech for Digital Inclusion in Rural Areas | Vasipally Nagireddy | 15m |
Uses Oracle Cloud Infrastructure, Oracle database and analytics, Oracle SOA suit, AEX and e-business suit to build offline-capable EHRs, agricultural… | ||
| Managing Multi-Cloud Complexity | Arun Pandiyan Perumal | 13m |
Claims that SRE practices measurably cut operational overhead and improve performance across clouds by combining SLIs SLOs and error budgets with unified… | ||
| Azure Load Testing in action | Peter De Tender | 29m |
Azure Load Testing is a managed Azure service that runs URL, JMeter and Locust tests against web apps or APIs, exporting JMeter JMeter JMX files and accepting… | ||
| High Availability & Low Latency in Distributed Systems Using K8s | Nikhil Kassetty | 13m |
Kubernetes plus an AI layer collects live metrics and runs LSTM forecasting for proactive autoscaling, isolation forest for anomaly detection, PPO placement RL… | ||
| Revolutionizing Legacy Systems with .NET and Microservices | Asif Mehboob | 16m |
Case study shows a core banking migration that delivers 50% operational cost reduction, 30% faster response times and 75% faster deployments, all after… | ||
| Building Resilient Cloud Infrastructure for Higher Education ERPs | Sanjiv Kumar Bhagat | 20m |
Claims concrete outcomes: a containerized microservices ERP with Kubernetes service mesh, 99.99% uptime during registration, Terraform and Packer pipelines for… | ||
| What Can We Learn from Formula 1 Incident Management | Ricardo Castro | 13m |
Red Bull moves an entire garage onto the track and reassembles a crashed car using pit tools and spare parts, diagnosing a likely transmission fault from… | ||
| Building Resilient Digital Infrastructures | Sharanya Prasad | 19m |
Claims a 15% reduction in breach cost from unifying networking and security and projects the SSE market nearly triples by 2028, backed by a finance-sector… | ||
| Modern Database Architecture: From SQL to NoSQL & Distributed SQL | Andrei Manakov | 29m |
A clear claim: distributed SQL preserves full transactional semantics while scaling across dozens or hundreds of nodes, using automatic sharding and consensus… | ||
| Navigating Managed Databases for Over a Decade as a Non-DBA | Renato Losio | 37m |
Ten years of running Amazon RDS since 2011 yields concrete, actionable lessons: 100,000 records inserted single threaded shows MySQL on RDS takes ~5m49s versus… | ||
| Amazon Aurora DSQL: Scalable, Distributed Relational Databases | Samuel Baruffi | 35m |
Claim: Amazon Aurora DSQL gives virtually unlimited scalability with single‑region HA ~99.99% and active multi‑region five‑nines availability, currently in… | ||
| Unified Observability | Sivasubramanian Bagavathiappan | 22m |
Claims a working reference architecture: OpenTelemetry collectors push traces metrics logs and ebpf profiles into an enterprise telemetry data lake where a… | ||
| Designing Robust and Scalable Distributed Applications | Ashis Chowdhury | 23m |
Claims real experience building realtime and near realtime BI and data pipelines at Mastercard and other large orgs with 23 years in the field, not vague… | ||
| Optimizing Salesforce for Scalable, Real-Time Performance | Balaji Bodicherla | 15m |
Claims a runnable integration stack: MuleSoft with 300+ connectors as middleware, Salesforce APIs (REST, SOAP, Bulk) and platform events and CDC for… | ||
| PaC in Jenkins for DevOps Pipelines | Sarathe Krisshnan Jutoo Vijayaraghavan | 25m |
Claims that embedding Policy as Code into Jenkins pipelines catches misconfigurations early and prevents breaches, supported by concrete metrics: 60% of… | ||
| Beyond REST: Exploring Modern API Paradigms | Gokul Babu Kuttuva Ganesan | 06m |
GraphQL cuts data transfer by 60–70% so clients fetch exactly what they need, event‑driven systems stream state changes for near‑real‑time reactions and loose… | ||
| The Future of GitOps in Modern DevOps | Kowshik Sakinala | 09m |
Claims concrete outcomes: a 2023 report shows 52% adoption of GitOps; one project reports 40% fewer post-deploy incidents in a quarter; Spotify-like case cites… | ||
| The Evolution of AI-Enhanced Automotive Infotainment Systems | Ravinder Katla | 18m |
Claims concrete numbers and implemented pieces: voice recognition reaches 99.99% voice accuracy and response latency drops to a few seconds; vehicle compute… | ||
| SRE and Healthcare Data Compliance | Sidhartha Velishala | 08m |
A case study shows an AI-based SRE stack—trained anomaly-detection models, dashboards, forecasting and predictive maintenance with remaining useful life… | ||
| Optimizing Financial Accuracy | Jaya Krishna Vemuri | 13m |
Cloud-based reconciliation for investment banking claims a working microservices ETL and high-performance matching engine that cuts exception handling from… | ||
| Reliability Excellence with SLO Management Products | Siddharth Joshi | 19m |
Claims a concrete SLO management lifecycle for an e‑commerce user journey: identify services, set individual SLOs for availability and latency, and build… | ||
| Beyond Optimization: Resilient Cloud Microservices at Scale | Sudhakar Reddy Narra | 32m |
A layered resilience framework combines architecture, engineering practices and business goals and delivers measurable wins: using Kubernetes and terraform… | ||
| AI-Powered Anomaly Detection & Self-Healing Systems | Venkata Anil Kumar Nilisetty | 08m |
Concrete claims, tools and results: graph neural networks achieve 92.7% accuracy and cut false positives 68.3%, self‑healing workflows with Apache Airflow drop… | ||
| Enhancing Security, Reliability, and Global Scalability in FinTech | Likhit Mada | 32m |
Claims concrete adoption numbers — "hundreds of millions in each country" and "billions of dollars" — and concrete fixes: idempotency key plus duplication… | ||
| Real-Time Fraud Prevention at Scale | Sasidhar Reddy Somula | 10m |
A real-time streaming system screens MCCA claims subsecond and flags suspected fraud before payout, using CNN for image tamper detection and transformer models… | ||
| SRE Principles in SAP S/4HANA Implementation | Pavan Kumar Bollineni | 17m |
Financial SAP S/4HANA work centers show concrete claims and outcomes: spike from 2s→30s latency at close triggers real-time monitoring, predictive anomaly… | ||
| AI-Powered Risk Management | Lokeshkumar Madabathula | 07m |
Built a metadata-driven pipeline platform using Azure Data Factory with parameterized JSON templates, reusable components, and streaming feeds into PowerBI for… | ||
| Building Financial Fortresses: Real-Time Fraud Detection | Prakash Vanga | 13m |
Claims real subsecond detection using Kafka Streams and a feature store, microservices with autoscaling, circuit breakers and rule‑based fallbacks; deploys… | ||
| Overcome Interconnect Bottlenecks in HPC Clusters | Murali Krishna Reddy Mandalapu | 10m |
Claims and measured wins focus decision making not topic labels: GPU clusters suffer 30–50% execution overhead from interconnect latency, RDMA promises 55%… | ||
| Streamlining AI Infrastructure for Enterprises | Venkatachala Nivas Chainuru | 15m |
Claims concrete numbers: a Dell VMware Nvidia collaboration delivers virtualized GPUs with about 18% average overhead and near‑linear scaling from 1 to 8 GPUs… | ||
| Resilient Health Monitoring | Bhushan Gopala Reddy | 17m |
System claims clinical-grade vital sampling with field results: BLE connection reliability improves from 92.4% → 99.7%, mesh routing sustains links at signal… | ||
| Ensuring Reliability in Healthcare Data Engineering | Santhosh Kumar Rai | 11m |
Concrete metrics and systems here: claims of 140–240 CPU hours per comprehensive variant analysis, early warning 5–12 hours before clinical deterioration, NLP… | ||
| Revolutionizing Healthcare with Big Data and ML | Arun Vivek Supramanian | 08m |
Healthcare data hits 2500 xabytes by 2025 with 80% unstructured, so concrete wins matter: Apache Spark and Hadoop underpin pipelines, AWS Redshift and cloud… | ||
| Implementing AI-Driven Observability in Healthcare | Peeyush Khandelwal | 28m |
Case studies report a 78% reduction in MTTR and a 92% variance detection rate after deploying AI observability; model incidents fall ~72% and clinical… | ||
| From Complexity to Clarity | Tarun Kumar Chatterjee | 16m |
An organization migrates monoliths to a serverless stack using AWS Lambda, DynamoDB, API Gateway, S3, CloudWatch Logs, Secret Manager, Docker and EKS, builds… | ||
| Enhancing Enterprise Security with AI | Venkata Krishna Ramesh Kumar Koppireddy | 14m |
Claims concrete results: an AI security framework that implements automated incident response, integrates ML and NLP for threat feeds and dark‑web monitoring… | ||
| Edge Intelligence: Real-Time Analytics at the Source | Srinivas Vallabhaneni | 18m |
Claims specific impact numbers and concrete tools: 37% downtime reduction from on-device predictive models, 23% defect cut and ~80% lower cloud transfer cost… | ||
| AI and Human Expertise for Excellence in Insurance | Balakrishna Sudabathula | 14m |
Clear metrics and tools appear: AI reduces claim processing from 3–5 days to minutes using automated document extraction and OCI-style pipelines, telematics… | ||
| Harnessing AI for Underwriting in Insurance | Harsha Vardhan Reddy Yeddula | 22m |
Claims concrete performance numbers: Microsoft Cloud AI pipelines process 1,200+ data points per application vs 40–50 traditionally, Random Forest >85%… | ||
| From Alerts to Action: AI-Powered Incident Response Systems | Smita Verma | 19m |
Claims a reproducible 60% MTTR reduction in case studies, a 5% false positive rate, and examples of 95% ROI in year one while showing an autonomous pipeline… | ||
| Mastering Monitoring & Alerting: Key to Seamless Performance | Rishabh Srivastava | 23m |
Claims a real e‑commerce case where monitoring plus automated responses cut downtime by 60% downtime reduction and cut response time by 40% response… | ||
| IT Infrastructure Reliability Through Monitoring and Alerting | Sanjeev Kumar | 17m |
Evaluates Prometheus, Datadog, New Relic across AWS Azure and Google Cloud and in a real health‑insurance deployment on Microsoft Azure, claiming measurable… | ||
| Building Predictive Analytics Data Warehouses in Healthcare | Vishal Kumar Jaiswal | 22m |
Claims include measurable gains: 18,000 events/sec stream processing with 90% critical‑event detection in 250 ms, ETL at 1.8 million records per minute, and… | ||
| From Fragmented Logs to Unified Insights: Scaling O11y | Alok Ranjan | 28m |
Dropbox moves from SSHing to a production logging pipeline built on Grafana Loki, ingesting about 10 GB/s and storing ~10 PB for 30 days across ~1,000 tenants… | ||
| Optimizing System Performance: O11y in Distributed Environments | Hardik Patel | 13m |
Claims reduce root cause time by 60%, improve MTTR 25% and increase uptime 30% plus concrete tracing example with a 200 ms span breach and guidance to track… | ||
| Leveraging Blockchain for Test Data Integrity | Sridhar Dachepelly | 12m |
Claims concrete outcomes: 99.97% success rate in healthcare data integrity, 961% reduction in unauthorized access attempts, a reported 86.3% drop in finance… | ||
| Beyond Uptime: Revolutionizing Fintech Reliability | Srinivas Reddy Mosali | 41m |
Specific claims and concrete fixes: Kubernetes plus MIG partitioning on NVIDIA A100/H100 yields up to 7x GPU utilization, CUDA memory tuning gives 15–30%… | ||
| Building Resilient Test Automation: A Universal Framework | Sujeeth Manchikanti | 15m |
Claims a Universal Automation Framework that is tool-agnostic and generates tests from a virtual application modeling layer into a keyword-driven data sheet… | ||
| Bridging Legacy and Cloud-Native Systems | Suman Neela | 15m |
Claims that a middleware layer actually bridges legacy and cloud-native stacks and reports measurable outcomes: cloud native adoption 30→85%, service… | ||
| Unlocking Observability with React & Node.js | Mohit Menghnani | 17m |
Claims that unified fullstack observability for React and Node.js cuts MTTR by linking user actions to backend spans, demonstrates trace propagation using… | ||
| Network X-Ray Vision: eBPF for Cloud-Native Observability | Sai KR Pentaparthi | 19m |
eBPF runs small verified programs in the Linux kernel to capture continuous event‑driven network and syscall data at microsecond resolution and feed real‑time… | ||
| Building Self-Healing Microservices for Modern SRE Practices | Krishna Rao Vemula | 14m |
Claims a concrete toolchain and outcomes: Spring Boot DevTools auto-reloads classes, Dockerfile with OpenJDK image produces consistent containers, and Lombok… | ||
| Implementing AI-Powered O11y with Splunk | Prabhu Govindasamy Varadaraj | 14m |
Claims concrete outcomes using Splunk: ingest via Splunk universal forwarders and OpenTelemetry, inject correlation IDs, baseline behavior with ML and detect… | ||
| SRE Principles in AI-Driven Retail Logistics Platforms | Srinivas Ankam | 16m |
Claims concrete targets and tools: micro‑fulfillment centers aim for 98.7% order accuracy and 1‑hour delivery windows, backed by an AI layer for predictive… | ||
| Zero Data Loss at Scale | Vignesh Kuppa Amarnath | 11m |
Claims a production system that achieves zero data loss during a regional outage by combining message replication across regions, replay-based recovery and… | ||
| Adaptive Power Optimization: Battery-Operated Chip Design | Puneet Gupta | 21m |
Claims adaptive recalculation using statistical models plus runtime measurements yields concrete improvements and an EDA integration path: a reported 37% power… | ||
| Leveraging Digital Innovation for Environmental Compliance | Sneha Deepika Kalagarla | 24m |
Digital platforms claim measurable outcomes: 35% cost reduction in monitoring, 42% faster incident response, and 67% faster permit processing, backed by cloud… | ||
| Designing for Failure using AWS: Resilient Systems | Sai Sahiti Nemalikanti | 10m |
Claim: failures are inevitable so design to limit blast radius and recover fast. Concrete techniques include redundancy across availability zones and multiple… | ||
| Engineering Failure-Resilient Systems | Onyebuchi Mark Irozuru | 16m |
Claims concrete outcomes: deliberate failure testing with Chaos Monkey 2 and controlled instance terminations proves recovery patterns; circuit breaker design… | ||
| Deployments, Downtime, Unexpected Fires: an SRE Survival Story | Pradeep Gaddamidi | 11m |
GCP object replication fails during a data center fire with GCS dual-region 99.9%/12h guarantees, prompting adoption of turbo replication under 15 minutes; SSL… | ||
| The Curious SRE: Cultivating a Mindset for System Resilience | Saurabh Phaltane | 29m |
Claims that reliability must match company stage with concrete moves: optimize for delivery speed at seed, add SLOs and observability at growth, and target 99%… | ||
| Ransomware Readiness: Backup and Recovery in the Cloud | Srihari Pakalapati | 50m |
Cloud readiness hinges on specifics: reported SOFOS 2024 numbers show 59% of orgs hit and 94% report backups targeted, with 32% suffering data theft and an… | ||
| Leveraging AI and Microsoft Ecosystem for Talent Acquisition | Sudeep Shanubhog | 11m |
A concrete system is described: an AI pipeline that combines NLP resume parsing, AI‑powered voice engagement, automated personalized skill assessments… | ||
| To observe or Not, is not the question | Swapnil Kulkarni | 18m |
Claim: observability only matters when it produces actionable answers tying system health to business outcomes. Describes collecting logs metrics traces and… | ||
| AI-Driven Claims Adjudication: Healthcare Efficiency & Fraud Prevention | Uday Bag | 16m |
Claims: AI shortens adjudication time up to 75%, cuts error rates by 80%, and yields ROI in 12–18 months. Tools listed: RPA, machine learning, and NLP with an… | ||
| Harnessing GenAI to Optimize Hybrid Cloud Workloads | Vijayakumar Jayaseelan | 14m |
Claims concrete wins: generative models drive predictive scaling that yields ~35% infrastructure cost reduction, analyze logs to trigger self‑healing and… | ||
| Cloud-Native Reliability Strategies: Practices Ensuring Uptime | Viralkumar Ahire | 05m |
Claims a system that prevents outages before they occur by combining Kubernetes Terraform Anible for self healing, multi‑region redundancy validated with chaos… | ||
| AI in SRE: Unlocking Prometheus Insights with Natural Language | David Asamu | 37m |
Built a web and Slack tool called PromptChart that turns questions into PromQL, runs them against Prometheus, and translates results back to natural language… | ||
| Enhance System Resilience and Efficiency with Microservices | Suresh Kumar Gundala | 26m |
Claims specific operational gains: 74% of organizations run microservices, development velocity up ~35–56%, infrastructure costs drop ~28–35%, and… | ||
| Resilient Cloud-Native Integration | Tejaswi Katta | 11m |
Claims concrete outcomes and repeatable practices: a migration yields 3,000 APIs and 500M daily transactions with 99.99% availability, incident response drops… | ||
| Harnessing Blockchain in Modern Enterprises | Sharath Chandra Adupa | 11m |
Claims include concrete metrics: settlement times drop from days to minutes and cross-border settlements cut from 3–5 days to minutes, verification costs fall… | ||
| Ensuring Manufacturing Reliability: Strategic SRE Roadmaps | Kumar Nayan | 37m |
Claims that applying SRE yields concrete wins: 45–47% reduction in unplanned downtime, 62% drop in mean time to recovery, and about $3.2 million annual savings… | ||
| Data-Driven Migration from Monoliths to Event-Driven Microservices | Amlan Ghosh | 25m |
A datadriven migration framework claims a measurable path from monolith to event-driven microservices: domain decomposition, event sourcing with 47 distinct… | ||
| Reliability Patterns in Permissioned Blockchain Systems | Umegbewe Nwebedu | 22m |
Covers concrete patterns for Hyperledger Fabric deployments: recommended cluster sizes (three orderers for Raft, three-plus for BFT to tolerate f failures)… | ||
| Leveraging AI & Predictive Analytics in Enterprise Architecture | Vikas Vallakonda | 07m |
Claims concrete outcomes and infrastructure: AI-powered forecasting reports 45% reduction in forecasting error and 92% accuracy on the data, dynamic pricing… | ||
| Enhancing Cybersecurity with Multi-Factor Authentication | Sandeep Jarugula | 08m |
Global breaches cost averages $4.45 million and 83% tie to identity compromise while integrating MFA and zero trust claims $3.92 million in annual savings for… | ||
| A Comprehensive Approach to Cloud Security Posture Management | Santosh Bompally | 31m |
Demos show concrete controls and outcomes not abstractions: predeployment IaC scanning plugged into CI/CD, an Azure Policy deny TLS 1.2 that flips from audit… | ||
| Tackling Alert Fatigue with SLOs | Mandi Walls | 33m |
Teams declare an alert cleanup sprint, examine the 10 most noisy alerts, and disable or defer anything nonactionable or success-only; many environments show… | ||
| Proactive Failure Prediction Through Anomaly Detection | Gaurav Mittal | 26m |
Claims that systems go from reactive to predictive maintenance with ML, showing concrete wins: Netflix uses anomaly detection to prevent streaming outages… | ||
| Reliability at Scale: How AutoML is Transforming Enterprise SRE | Swapna Anugu | 19m |
Claims concrete outcomes: AutoML drives automated alert tuning and self‑healing restarts, forecasts capacity for autoscaling, and performs root‑cause… | ||
| Ensuring Robustness in Hybrid Quantum Neural Networks | Karthikeyan Rajamani | 15m |
Claims hybrid quantum-classical networks outperform classical nets on noisy high‑dimensional tasks and show 200+ training ops 2% variance in one benchmark… | ||
| From Reactive to Resilient: Agentic AI | Balaprabunath Coimbatore Ramalingam | 18m |
Claims a working Agent TK-style agentic framework that wires a self-healing orchestrator to hundreds of task-specific agents (validation, translation… | ||
| Building More Resilient Cloud-Native Platforms | Umamaheswarareddy Chintam | 17m |
Claims concrete numbers and tools: anomaly detection using machine learning with dynamic thresholds and continuous model refinement, NLP for postmortem… | ||
| nothing matches | ||