The article explains why Kubernetes, once praised for cost savings, now incurs high operational expenses due to container replication, sidecar overhead, and slow startup, and shows how serverless and WebAssembly approaches can dramatically reduce those costs while preserving reliability.
The article explains how AutoMQ, a cloud‑native Kafka built on a shared‑storage architecture and Alibaba Cloud services such as OSS, ESSD, ESS and preemptible instances, achieves up to ten‑fold cost savings, high performance, elastic scaling, and robust disaster‑recovery capabilities.
FinOps combines finance and DevOps to create a culture of transparent, predictable cloud spending, guiding enterprises through preparation, strategy alignment, shared responsibility, cost insight, optimization tactics, and ongoing control, enabling them to balance agility with disciplined cost management in cloud-native environments.
2023 saw a wave of high‑profile tech leaders—Google’s engineers, Amazon Prime Video, and DHH—questioning the microservices paradigm, presenting data‑driven case studies that show dramatic latency and cost reductions when moving to monolithic or runtime‑managed architectures, and urging architects to reassess scalability versus complexity trade‑offs.
This article presents a year‑long, white‑box cost‑governance practice for big‑data platforms, detailing the data‑governance framework, engine auto‑tuning (HBO), compression algorithm replacement, operator analysis, data‑warehouse white‑boxing, duplicate‑computation reduction, link‑depth minimisation, automation of routine governance, benefit analysis, and future plans.
In 2023, leading tech companies like Google and Amazon publicly criticized the microservices model, presenting new architectural approaches that combine logical monoliths with automated runtimes, dramatically cutting latency and cost while prompting many other firms to abandon microservices in favor of simpler, more efficient monolithic designs.
Amid economic growth and frequent continuity incidents, major internet firms are redefining SRE roles, emphasizing cost reduction, system resilience, risk management, AI‑driven operations, and close collaboration with development teams, as revealed by a detailed analysis of recent job postings from Ant Group, Alibaba, ByteDance and others.
In 2023, major tech companies such as Google and Amazon publicly questioned the benefits of traditional microservice architectures, presenting new "microservice 2.0" concepts, monolithic alternatives, and cost‑performance analyses that highlight a broader industry shift toward more pragmatic, cloud‑native design approaches.
This article compares the advantages and disadvantages of cloud storage, on‑premises storage, and the hybrid cloud‑near storage model, explaining how each impacts scalability, cost, control, security, and integration for modern data platforms, and helps organizations select the most suitable solution.
In this round‑table discussion, industry experts analyze Alibaba Cloud's historic price reductions, compare self‑built IDC versus public cloud economics, share iReader's phased migration experience, explore the broader value of cloud services beyond raw resources, and examine how large‑model AI workloads reshape cost and innovation strategies.
This article outlines the rapid growth of data in the smart automotive sector and details Changan's big data platform challenges—high cost, data accessibility, and operational complexity—and the practical migration from a Lambda to a unified Kappa architecture that delivers significant storage, compute, and maintenance efficiencies.
This guide shows how to use Alibaba Cloud Container Compute Service (ACS) to create a private Palworld game server with Kubernetes resources, cost‑effective serverless scaling, and optional best‑effort instances, including step‑by‑step commands and YAML configurations.
This article details Volcano Engine DataLeap's comprehensive data governance system for e‑commerce platforms, covering the key challenges of SLA quality, model stability, cost control, and low efficiency, and presenting a five‑part framework that includes top‑level architecture, systematic stability and cost governance, tool‑driven automation, SLA assurance processes, and future outlooks.
Baidu’s Qianfan Large Model Platform provides a one‑stop enterprise solution with 54 pre‑installed models, advanced fine‑tuning, comprehensive evaluation metrics, and optimized deployment that cuts costs up to 90% and boosts throughput 3‑5×, enabling rapid, affordable AI application development.
This article explains how enterprises can leverage cloud‑native architectures and FinOps practices to gain financial accountability, visualize multi‑dimensional cost data, optimize resource usage, and implement systematic cost governance across Kubernetes environments, covering cost insight, optimization, and operational stages with practical recommendations and example algorithms.
This guide explains how to quickly select a ModelScope open‑source LLM, deploy it to Alibaba Cloud Function Compute using the SwingDeploy one‑click feature, enable reserved idle billing, and evaluate the cost savings compared with traditional GPU provisioning.
X (formerly Twitter) cut monthly cloud spending by 60% by shifting workloads and storage to on‑premises infrastructure, igniting a debate over whether de‑clouding is viable for all enterprises, how it signals a potential inflection point in cloud computing, and what strategies—balancing high availability, disaster recovery, and cost efficiency—should guide firms, as highlighted in the upcoming TVP Tech Sleepless Nights series featuring leading industry experts.
This article presents a detailed case study of a leading AI‑driven quant investment firm that leveraged Alibaba Cloud ACK's FinOps suite to tackle planning, allocation, management, and optimization challenges in Kubernetes‑based container workloads, achieving up to 25% cost reduction and significantly higher resource utilization.
This article presents a systematic approach for technology leaders to reduce and control cloud‑related expenses through cost‑optimization, detailed analysis, team organization, project planning, communication, and long‑term fine‑grained operational practices.
NetEase Cloud Music’s self‑built FinOps platform tackles rising cloud spend by unifying cost data, visualizing and allocating expenses, rating resource utilization, and empowering platform providers, business units, and developers with data‑driven governance to curb the Andy‑Bill effect and enable scalable, long‑term cost control.
MiHoYo’s data platform team details their migration of Spark workloads to Alibaba Cloud’s ACK Kubernetes service, describing how the Spark‑on‑K8s + OSS‑HDFS architecture delivers elastic compute, up to 50% cost reduction, and true compute‑storage separation, while addressing operational challenges through custom operators, Celeborn, and robust monitoring.
This article outlines the challenges of ultra‑large e‑commerce data warehouses—such as SLA pressure, model instability, soaring resource costs, low governance efficiency, and fragmented processes—and presents a one‑stop, tiered data‑governance framework with stability, cost, and efficiency subsystems that drives distributed autonomous governance and measurable business value.
Facing massive data volumes and strict SLA requirements during the Double 11 shopping festival, a major e‑commerce platform built a systematic data‑governance framework that addresses quality, stability, cost, and efficiency through multi‑layered grading, digital cost models, automated tools, and full‑lifecycle management.
The host‑lifecycle platform (mmachine) standardizes and automates machine onboarding, maintenance, and decommissioning in DiDi’s elastic cloud by using a four‑layer architecture, custom asynchronous scheduler, backup‑machine pool, cloud‑native batching, and idle‑resource governance, turning a manual, day‑level process into a reliable, minute‑level workflow while cutting costs.
This article details how a fast‑growing HR SaaS company analyzed MaxCompute billing spikes, identified five key cost drivers, leveraged tenant‑level Information Schema to extract task metadata, applied SQL‑based cost formulas, and implemented targeted optimizations that stabilized their cloud data‑processing expenses.
The article examines how 37signals' cloud repatriation initiative, along with broader industry trends at companies like Snap, Twitter, and major cloud providers, is driving significant cost savings, prompting a resurgence of on‑premises hardware and reshaping cloud cost‑optimization strategies across the sector.
This article explains how video on‑demand cost is dominated by CDN bandwidth, how player‑side optimizations—such as reducing cache waste, using dynamic buffering levels, smarter range requests, precise preloading, and resolution adjustments—can cut bandwidth by 8% and overall costs by 20% while preserving user experience.
In this interview, Volcano Engine’s president Tan Dai explains how the rise of large models reshapes the AI landscape, why training thresholds now favor a pyramid of ultra‑large, medium‑size, and vertical models, and how a cloud‑first, multi‑model approach can address cost, security, and scalability challenges for enterprises.
This article introduces the fundamentals of enterprise architecture, defining its scope, reference models, and maturity stages, and explains how architects manage complexity, control costs, ensure SLA compliance, and apply iterative, partitioning, and simplification techniques to modernize enterprise IT systems.
This article explains how Renliji's data warehouse team leveraged MaxCompute's Transaction Table2.0 to dramatically reduce incremental data deduplication costs and execution time, while also introducing efficient small‑file merging, time‑travel queries, and future data‑sync strategies for a high‑growth HR SaaS platform.
This article details how ZEEK automotive tackled rapid growth challenges by redesigning its cloud‑native infrastructure, adopting Alibaba Cloud ACK FinOps and ACK One for multi‑cluster management, and implementing cost‑visibility, intelligent allocation, and configuration checks that yielded significant resource savings and operational stability.
An in‑depth analysis of Amazon Prime Video’s monitoring service reveals how the team abandoned a costly serverless micro‑service architecture in favor of a streamlined monolith on EC2/ECS, cutting infrastructure expenses by over 90% while improving scalability, prompting industry leaders to reassess cloud‑native design assumptions.
KubeCost, developed by NetEase Cloud Music, is a low‑intrusion, scalable Kubernetes cost analysis system that allocates resource expenses using peak‑or‑usage billing models, supports hybrid‑multi‑cloud pricing, aggregates per‑pod CPU/memory/GPU costs, and stores data efficiently in ClickHouse for reliable, business‑oriented financial insight.
This article summarizes Zhang He’s Bilibili SRE talk on building a capacity‑management system that visualizes resource usage, reduces costs, improves stability, and leverages Kubernetes VPA, HPA, pooling, and quota management to support massive live‑stream events and rapid feature releases.
This article presents a comprehensive case study of NetEase Cloud Music's data governance practice, covering data background, governance philosophy, detailed solutions across metadata, storage, compute, and model design, practical implementations, measurable cost savings, and future planning for sustainable data management.
The Prime Video engineering team replaced a costly, scaling‑limited serverless microservice architecture with a streamlined monolithic solution on EC2/ECS, achieving more than a 90% reduction in infrastructure expenses while improving scalability, sparking widespread debate about the true value of microservices and serverless approaches.
A detailed case study reveals how Amazon Prime Video replaced a costly, serverless micro‑service monitoring system with a streamlined monolithic architecture on EC2/ECS, slashing infrastructure expenses by over 90 % and sparking a broader debate on the true merits of microservices versus monoliths.
This article provides a detailed guide to cloud migration, covering evaluation and analysis, pilot projects, assessment strategies, planning and design with cloud services, verification and implementation steps, continuous measurement, and cost optimization through FinOps to ensure successful and secure migration.
Alibaba Cloud's PAI‑EAS now supports Spot Instances, letting users run latency‑tolerant inference tasks on pre‑emptible compute resources and achieve up to 90% cost savings compared with on‑demand instances, while offering flexible bidding, protection periods, multi‑spec selection, and automatic scaling.
Amazon Prime Video’s engineering team revealed that moving from a distributed micro‑service architecture to a single‑process monolith on EC2 and ECS slashed infrastructure expenses by over 90% while improving scalability, challenging the prevailing belief that serverless and micro‑services are always the most cost‑effective cloud solutions.
A Prime Video case study shows that moving from a costly serverless micro‑service architecture to a streamlined monolith on EC2/ECS reduced infrastructure expenses by over 90% while improving scalability, sparking a heated debate about the true value of microservices and serverless in large‑scale video streaming.
This article examines the challenges of scaling log storage and retrieval for high‑traffic services, analyzes the cost and performance limits of traditional ELK‑based pipelines, and presents a streamlined, UDP‑driven architecture using ClickHouse that dramatically reduces hardware expenses while handling hundreds of gigabytes per second.
The article analyzes the operational, stability, and cost challenges of Haro’s AI platform, explains why a serverless FaaS architecture—specifically Knative—was selected, and details the implementation steps, performance gains, and future scenarios for AI workloads.
This article details Bilibili's journey from a late‑started, reactive big‑data platform to a mature, proactive governance system that combines asset metadata, metric‑driven strategies, cost‑aware billing, and automated tooling to achieve massive storage savings and operational efficiency across the organization.
This article presents an in‑depth overview of Bilibili’s big data development governance platform, detailing its architecture, the pain points of platform construction, data‑driven methodology, product strategy, and practical solutions for data integration, quality, cost, and security governance across large‑scale data operations.
This article introduces FinOps, explains its definition and cultural significance, illustrates the concept with a personal household billing story, and outlines five concrete steps—cost allocation, target setting, budget control, operational management, and intelligent automation—to achieve cloud cost optimization.
Since 2021, 得物 has built a FinOps practice that combines finance and DevOps to allocate, forecast, and optimize multi‑cloud spend, delivering over ¥100 million in annual savings through cost‑center platforms, container‑utilization improvements, custom PaaS services, automated analysis, and a cross‑functional virtual team governed by visibility, optimization, and governance KPIs.
This article explains the motivation, design, and implementation of Alibaba Cloud's SLS Schema‑on‑Read scanning mode, showing how it enables SQL analysis on raw log data without pre‑built indexes, improves flexibility for evolving schemas, and reduces storage and index costs in various log‑analysis scenarios.
Bilibili implements a FinOps‑driven, closed‑loop process that combines detailed cost insight, multi‑cloud optimization, and continuous operational controls—using dashboards, TCO models, SKU pricing, and automated billing—to cut IT spending by billions of yuan while maintaining performance and supporting business growth.
This article presents a detailed case study of Gaotu's migration of its on‑premises big‑data platform to Tencent Cloud, covering background challenges, a phased migration plan, implementation lessons, cost‑control measures, and future optimization strategies, with practical insights for similar enterprises.
This article explores Alibaba's DataWorks platform and its comprehensive data governance practices, covering application efficiency, security controls, cost optimization, organizational structure, and cultural initiatives that together enable scalable, secure, and cost‑effective data management across the enterprise.
Alibaba’s DataWorks team shares extensive experiences in building and operating a large‑scale data platform, covering data governance across stages—from data stability and quality to security, cost control, and organizational culture—illustrating how systematic practices and tools drive efficiency, reliability, and value for enterprises.
This article compares DevOps and FinOps, outlines their ten major differences, and explains how integrating the two practices can create a more efficient and financially optimized software development lifecycle.
This article outlines ZuanZuan’s capacity management approach, covering its objectives, development stages, water‑level metrics, resource optimization techniques, cluster capacity assessment, stress‑test indicators and standards, as well as scaling strategies, demonstrating how systematic capacity management reduces costs while ensuring service stability.
Pigsty is an open‑source platform that upgrades PostgreSQL across six dimensions—observability, reliability, availability, maintainability, extensibility, and interoperability—delivering enterprise‑grade features, built‑in monitoring, automatic failover, backup, and performance tuning while cutting cloud database costs dramatically.
To cut the hundreds‑of‑thousands‑yuan monthly bill of a commercial HTTPDNS service, the team built a multi‑region, self‑hosted HTTPDNS platform, estimated to slash costs by up to 90%, then resolved unexpected TLS bandwidth waste by improving connection reuse, ultimately achieving over 80% savings and planning a hybrid‑cloud deployment.
FinOps is a cloud‑focused operating model that unites technology, finance, and business teams to analyze spend, set usage standards, and continuously monitor and optimize resources through visualization tools, ticket‑based ownership, and metric‑driven processes, as demonstrated by 三七’s integrated cost‑optimization practice.
At QCon 2022, NetEase’s AI experts detailed their end‑to‑end approach for digital content risk control, covering data acquisition, semi‑supervised training, dynamic inference, cost‑effective deployment, and future directions, highlighting how AI can boost efficiency while managing escalating operational expenses.
This article details NetEase Cloud Music's year‑long data governance initiative, covering data background, governance strategy, project plan, practical actions, results, and future outlook, and shows how metadata‑driven management reduced storage by over 30% while improving reliability and efficiency.
This article explains what Spot (preemptible) instances are, compares them with on‑demand and reserved instances, details AWS Spot pricing and signals, and provides practical strategies—including node‑group design, Kubernetes scheduling, health checks, and rollback plans—to reliably reduce cloud costs while maintaining application availability.
This article presents a comprehensive, three‑part guide on the current state of full‑stack operations monitoring, common challenges and solutions, and a real‑world use case, illustrating how Alibaba Cloud Elasticsearch can improve observability, boost performance, and cut costs for complex distributed systems.
Facing rapid growth, our team evaluated ClickHouse’s hot‑cold storage and tiered‑disk policies to replace Elasticsearch, designing partitioning, TTL, and multi‑level storage strategies—including hot, cold, and archive disks, custom storage policies, and OSS integration—to achieve higher write throughput, better compression, and over 50% cost reduction.
This presentation details Huolala's end‑to‑end cloud‑native cost‑optimization strategy, covering the company's infrastructure basics, Kubernetes‑based server cost‑saving techniques, a tailored optimization roadmap, practical Spot Instance usage, and a custom CronHPA‑driven scheduled scaling solution to boost resource utilization.
This article provides a comprehensive guide for technical leaders on reducing and managing technology costs through a two‑stage approach of cost optimization and fine‑grained operations, covering team formation, current‑state analysis, discount and storage tactics, project planning, communication, and long‑term process and system support.
Sky Computing, introduced by Ant Technology Research Institute, proposes a cloud‑agnostic platform that abstracts heterogeneous public and private clouds into a unified service layer, enabling applications to seamlessly migrate workloads across clouds, reduce costs, avoid vendor lock‑in, and support AI training via the SkyML prototype.
The article details Cloud Music’s data‑governance journey, covering early modeling standards, self‑service data tools, quality and metadata management, asset‑reuse improvements, and cost‑saving Spark optimizations, while sharing concrete metrics, processes, and the team’s systematic methodology.
This article introduces the first industry model for estimating total Serverless function costs, analyzes key cost factors such as memory, concurrency, and execution time, and proposes five optimization strategies along with Huawei Cloud's transparent, one‑click Cost Research Center to help users achieve economical Serverless deployments.
This article presents a three‑year workforce planning model that balances hiring, retraining, part‑time staffing, and layoffs while minimizing costs and attrition, using detailed demand forecasts, attrition rates, and constraints to guide optimal decisions for unskilled, semi‑skilled, and skilled workers.
AWS switched S3 log compression from gzip to Zstandard, saving roughly 30% of storage space—equivalent to exabytes—by changing the internal storage method, a move confirmed by employee comments and a coinciding 31% price drop in late 2021.
This article presents Huya's big data platform evolution, detailing cost‑saving measures, SLA practices, multi‑datacenter architecture, containerized resources, metadata‑driven intelligence, and future directions such as hybrid‑engine materialized views to improve efficiency and service reliability.
This newsletter curates the latest industry insights on smart manufacturing, Kubernetes security, cloud cost optimization, cloud‑native education, technical case studies, e‑books on cloud‑native adoption, an AI modeling video, and recent cloud‑native networking updates, providing concise summaries and direct links for deeper exploration.
This article presents a comprehensive, data‑driven case study of how Tencent’s internal Kubernetes/TKE platform reduced monthly CPU usage by up to 70% and memory usage by 50% through systematic cost data collection, VPA/HPA enhancements, custom scheduling, node‑level over‑commit, and safe node decommissioning, while maintaining zero‑incident reliability.
This article analyzes the low server utilization problem in modern cloud‑native environments, presents industry survey data, and outlines a four‑step framework—including observability, optimal public‑cloud usage, elasticity sharing, and remote deployment—to help enterprises dramatically reduce cloud costs while maintaining performance.
This article examines the design principles, challenges, and implementation details of a multi‑active architecture for hybrid cloud environments, covering stability, cost, efficiency, network topology, container orchestration, service discovery, traffic scheduling, and data storage, and outlines practical solutions used by the Zuoyebang platform.
This article examines the motivations, stability and cost considerations, technical challenges, and design principles of a multi‑active hybrid cloud architecture, illustrating how container orchestration, service governance, traffic scheduling, and data storage are coordinated to achieve high availability and cost efficiency across multiple cloud providers.
This article introduces Huya's offline job scheduling platform, covering its positioning, evolution, system architecture, baseline scheduling techniques, cost‑optimization strategies, resource‑balancing methods, and future intelligent data‑warehouse directions, illustrating how data‑driven automation improves YARN utilization and SLA compliance.
The article presents NetEase's internal data governance experience, outlining past challenges, current pain points, a comprehensive product strategy covering scope, value quantification, and feature implementation, and shares initial results and future plans to build an automated, end‑to‑end big‑data optimization platform.
Wolai’s shift to a Serverless architecture using Alibaba Cloud Function Compute cut operational costs by over 50%, accelerated development cycles, and enabled reliable real‑time collaborative editing through a snapshot system, illustrating how small teams can leverage cloud functions for scalable, cost‑effective services.
Web Functions, which support native HTTP/WebSocket protocols, traditionally handle each request with a dedicated instance, but this single‑request concurrency wastes resources and raises costs for I/O‑intensive workloads; enabling multi‑request concurrency—either static or dynamic—consolidates many requests onto fewer instances, cutting latency by up to 80 % and reducing billing by as much as 98.8 %.
During the 2022 China Internet Industry Application Salon, JD Cloud’s product manager explained how the Color gateway, an API gateway handling billions of daily requests, overcomes stability, high‑availability, reliability, and performance challenges during peak sales by adopting a cloud‑native ClickHouse data warehouse that boosts processing speed, reduces costs, and provides real‑time analytics.
Zuoyebang’s shift to cloud‑native architecture leveraged Alibaba Cloud’s Kubernetes Serverless virtual nodes, achieving a 22.5% cost reduction during peak traffic by dynamically scaling workloads, while addressing scheduling, observability, and performance challenges through custom schedulers, enhanced monitoring, and careful testing.
Developer Xiao Wang evaluates three deployment options—traditional SLB + ECS, Kubernetes, and Alibaba Function Compute—to build a highly elastic, low‑cost, low‑maintenance architecture for two online apps, then adopts FC’s reserved‑instance mode and idle‑billing feature to eliminate cold‑starts and reduce expenses.
Zhang's team at Zuoyebang details their journey to serverless Kubernetes virtual nodes, explaining how elastic scaling, fine-grained scheduling, and cost‑effective resource utilization transformed high‑peak online services, while addressing challenges in scheduling, observability, performance, and multi‑cloud resilience.
Huolala’s architecture team shares a detailed walkthrough of their cloud‑native cost‑optimization journey, covering public‑cloud server pricing models, Kubernetes request/limit tuning, HPA and CronHPA scheduling, spot instance integration, intelligent pod placement, and practical lessons learned from scaling a global on‑demand logistics platform.
NetEase’s cloud‑native operations team shares how they confront new challenges of Kubernetes adoption—ranging from technical stack shifts and knowledge‑base gaps to capacity planning, automated diagnostics, monitoring, alerting, and cost‑saving strategies—offering practical insights for building efficient, stable, and scalable ops systems.
During the 2022 Chinese New Year, WeChat leveraged Serverless cloud functions and cloud development to handle the explosive demand of red‑packet cover creation, achieving sub‑ten‑thousand‑yuan costs, supporting over 100 million daily calls, and delivering rapid, scalable, and cost‑effective deployment for developers.
This article details Ctrip’s large‑scale use of AWS Spot instances on Kubernetes, explaining the cost benefits, the challenges of spot interruptions, and the architectural and operational strategies—including multi‑AZ deployment, scheduling policies, autoscaling group design, and observability—that enable a 50% reduction in container costs while maintaining system stability and reliability.
This article explains Kuaishou's comprehensive approach to data governance, detailing the background challenges, a standardized evaluation framework, practical solutions for model, quality, and cost issues, scoring strategies, operational mechanisms, measurable benefits, and future plans for continuous improvement.
This article presents Xiaomi's comprehensive data management practice, detailing the design and evolution of its metadata platform, the implementation of full‑domain metadata, real‑time lineage, precise measurement, and the subsequent applications such as data maps, governance, cost control, and quality assurance, while outlining future development directions.
The article describes Liulishuo's Cloud Infra team's end‑to‑end automation of cloud resource provisioning, scaling, and cost governance using Terraform, a custom Luban platform, GitLab CI/CD, and chat‑bot integrations, highlighting the architectural design, implementation steps, and measurable benefits for both operations and business teams.
This article explores the strategic management and engineering practices required to build an effective AI research department, detailing organizational structures, performance metrics, cost-reduction strategies, and practical educational AI solutions that bridge theoretical algorithms with scalable industrial applications.
This guide explains what Application Portfolio Management (APM) is, why it’s essential for modern enterprises, the benefits it delivers, typical stakeholder concerns, and step‑by‑step practices for building and maintaining an effective application portfolio.
This article details Ctrip’s migration of its hotel direct‑connect service to AWS, describing the background challenges, cloud‑native architectural redesign with EKS, bandwidth and latency optimizations, use of spot instances, DNS caching, cross‑AZ traffic reduction, and the resulting performance and cost benefits.
At Youzan, data governance evolves from massive data assets to AI readiness through systematic data assetization, quantitative quality scoring, cost measurement, and targeted operational tactics, enabling precise quality monitoring, cost allocation, and continuous improvement that drive both data value and cost efficiency.
This article explains how Kubernetes' built‑in autoscaling mechanisms—Horizontal Pod Autoscaler, Vertical Pod Autoscaler, and Cluster Autoscaler—work, when to use each, and best‑practice tips to reduce cloud costs while maintaining application performance.
This article presents a comprehensive case study of Meituan's hotel‑travel data governance, covering the background, challenges, strategic goals, standardized processes, technical systems, cost and security optimizations, measurable outcomes, and future plans for automated governance.
Datadog’s 2022 Serverless report shows a rapid expansion of Lambda usage worldwide, with call frequencies 3.5 times higher than two years ago, average daily runtimes of 900 hours, shorter execution times, growing adoption of Azure Functions and Google Cloud Functions, and detailed cost analyses that highlight both the economic benefits and optimization challenges of serverless architectures.
This article introduces the fundamentals of distributed database architectures, compares Shared‑Nothing and Shared‑Storage designs, explains their three‑tier structure, core engine components, SQL execution flow, performance and cost optimizations, and showcases a real‑world high‑traffic deployment in Douyin’s Spring Festival event.
The talk outlines a next‑generation cloud‑native data lake that leverages elastic Kubernetes compute, object‑storage, and Apache Iceberg to cut costs 3‑10× while boosting performance, and presents Tencent’s Data Lake Compute and Data Lake Fabric solutions that address scalability, reliability, and operational challenges through serverless, unified, multi‑engine architecture.
The article analyzes how cloud‑native concepts such as DevOps, micro‑services, continuous delivery, and containerization can be applied to big‑data foundations, outlining four guiding principles—industrialized delivery, cost quantification, load‑adaptive scaling, and data‑centric design—and describing concrete Hadoop‑based architectures and Tencent Cloud solutions that lower cost while boosting performance.
