India: A Cornerstone of Growth for MongoDB Technical Services

Ankit Kakkar
November 29, 2023

India has emerged as a cornerstone in our MongoDB Technical Services growth story, marked by the team’s 100% growth in just two years. Bengaluru has been at the forefront of our expansion, witnessing an incredible increase in personnel and the addition of new teams and functions to support our developer data platform. This highlights Bengaluru’s emerging role in providing critical technical assistance to our customers and partners.

Gurugram has also played a crucial role in the growth of Technical Services in India. This growth underscores Gurugram’s increasing significance as a thriving hub for MongoDB Technical Services. MongoDB’s continuing investment in expanding Technical Services in India reflects the substantial impact the team has had on MongoDB's customer success.

A look into Technical Services

We have multiple customer-facing Technical Services teams in India, each with unique roles and responsibilities. From specific product support to support for MongoDB services and Atlas cluster deployments, each team seeks individuals with strong critical thinking skills who can quickly detect, resolve, or escalate complex issues that may span various aspects of MongoDB's products and services. Our Technical Services teams are committed to delivering exceptional support to our customers through each team’s unique focus.

Building together across teams and departments

As part of their role, Technical Services Engineers (TSEs) need to partner with other supporting functions within MongoDB to ensure seamless operations and exceptional customer support.

TSEs proactively identify issues that may require escalation and involve Escalation Managers accordingly. They also identify opportunities for improvement within the MongoDB product ecosystem and pass on any feedback, feature requests, and customer insights to our Product Management and Customer Success teams.

The Technical Services team is highly collaborative and works together to solve customer problems. While each sub-team within Technical Services focuses on specific areas of expertise, there are numerous intersections that require cross-team collaboration. This collaborative approach enables team members to learn and build new skills by exploring different areas of interest.

Excellence centers

We also take pride in the technical excellence centers that we have built between our teams in India. These centers are part of our global Technical Experts ecosystem. Technical Experts help us train the Technical Services team, liaise with the development teams, and highlight pain points to the Product Management team, amongst other responsibilities.

Learning and development

We believe that an engineer's journey goes beyond a career and is about gaining knowledge, skills, and experiences. MongoDB is an integral part of this journey, offering a platform for continuous growth and development.

New hires undergo comprehensive onboarding and training to gain a holistic understanding of the MongoDB ecosystem. Engineers are encouraged to participate in cross-team rotations and have access to various learning platforms, including O’Reilly Learning and internal Product Readiness training. We collaborate closely with our Technical Services Knowledge and Training teams to deliver training sessions, fostering both technical and presentation skills and an observational learning culture.

Engineers are also provided with “protected time” to focus on their individual learning plan, allowing them to focus on delivering projects, prepping for certifications, growing their expertise in a specific area, or working in collaborative cross-skill focus groups.

Periodic hackathons offer a platform for innovation, encourage collaboration, and contribute to team-wide problem-solving efforts. In addition, MongoDB User Groups and .local events allow the team to showcase and share their knowledge externally.

By creating a learning environment where engineers can grow and achieve their goals, both our team members and the business thrive.

Enhancing support across time zones

An exciting development in our Technical Services journey is the introduction of the Swing Shift in India. This strategic initiative leverages India's engineering talent to enhance support during India and EMEA hours, further augmenting support for the surrounding regions and improving service continuity for APAC and EMEA customers.

We continue to hire in both our Bengaluru and Gurugram offices. If you’re someone who is technically talented, enjoys problem-solving, loves working with customers, and values your personal and professional growth, I encourage you to explore open roles on our careers site.

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MongoDB助力腾讯游戏优化游戏开发体验

客户简介腾讯游戏提倡超级数字场景连接数亿游戏玩家作为“超级数字场景”理念的倡导者和实践者，腾讯游戏致力于为用户创造高品质数字生活体验，为产业和社会发展创造更多建设性的价值。腾讯游戏为全球知名的游戏开发与服务运营商，在全球连接超过8亿的用户。在开放发展的模式下，腾讯游戏采取自主研发和多元化的外部合作相结合的方式，在网络游戏众多细分市场领域形成专业化布局，打造覆盖全品类的产品阵营，为全球网络游戏玩家提供休闲游戏平台、大型网游、中型休闲游戏、桌面游戏、对战平台五大类。另外，腾讯游戏与全球顶级游戏开发公司建立深度合作，将国外优质的前沿产品体验带到中国，也将中国的游戏带向世界。 2021年3月，腾讯游戏针对国际业务推出了在线游戏开发平台Level Infinite PGOS（Level Infinite Game Online Service）。Level Infinite PGOS是一种游戏在线服务解决方案，旨在降低游戏后端开发和维护的难度，同时降低成本，从而使开发者专注于游戏玩法与核心逻辑开发。业务挑战产品力主导游戏行业竞争游戏出海面临多重挑战全球游戏市场规模不断扩大，游戏产业已成为一种重要的文化产业。据市场调查机构 Newzoo 最新数据显示，2023年全球游戏市场规模预计将超过1877亿美元，同比增长2.6%。游戏市场潜力巨大、前景看好，与此同时游戏开发竞争也变得异常激烈。游戏品类越来越多、玩法越来越多，给游戏开发带来更高要求：游戏设计和架构越来越复杂，游戏开发成本水涨船高，游戏复用性较低，新项目启动门槛更高等等。尤其对于腾讯游戏海外业务来说，研发更需要具备全球发行、全球部署的能力，直接拉升了对于底层数据架构的要求，当中包括：需要提供多租户SaaS模式；能够物理隔离每个游戏大区，满足全球各个区域的隐私保护；以及可在全球各个地区进行分布式部署、自动扩容、缩容等。解决方案深度契合游戏业务场景为了应对游戏行业的最新趋势和海外市场的挑战，腾讯游戏推出为海外游戏而设的Level Infinite PGOS通用平台。Level Infinite PGOS是一套多租户SaaS游戏后台解决方案，采用全球化分布式架构，在欧洲、北美、日韩、东南亚等游戏发行热点区域部署运行。数据库是游戏软件的核心组件，游戏玩家的各种信息、运营数据、游戏场景数据等都需要借助数据库来保存。对于数据存储系统，Level Infinite PGOS根据自身场景进行了严格的测试选型，最终采用MongoDB作为核心存储组件，成为一整套覆盖游戏各个维度、各个生命周期的解决方案。玩家数据存储 – 与传统游戏开发有所不同，使用MongoDB去存储玩家的基础数据，不会将MongoDB直接暴露给游戏去使用，开发者无需关心底层的数据细节，即可直接灵活定义数据，例如，不同游戏可定义不同数据模板。此外，MongoDB 支持多种数据类型和数据原子运算，易于实现幂等操作；而且基于MongoDB的分片可横向扩容，对于一些爆款游戏来说，这一点很重要，可以不用担心玩家规模的快速增加。智能对局匹配 – 在很多游戏中，都需要在平台上匹配两名玩家去进行对局竞技。以腾讯游戏为例，如果是一款全球发行的游戏，就有可能在不同游戏大区匹配到两名玩家，这种匹配看似随意，但却需要后台具备强有力的数据处理能力。技术调度要同时满足不同区域的服务器集群，也就是满足不同场景需求下的服务器扩容。腾讯游戏底层通过MongoDB实现原子化操作，经过玩家各种属性的对比，找到一个距离各个玩家最近的服务器，并进行服务器分配，最终形成一个对局。游戏内经济系统闭环 – 假设把游戏内的经济系统理解为一个特殊的交易场景，在处理游戏交易的过程中，涉及到订单、退款、跟踪回溯等多个环节，而通过MongoDB的原子化、事务性操作可以将整个交易流程一次性完成。虽然游戏内交易是虚拟的、复杂的，但采用MongoDB可以保证交易是规范的、完整的。数据流能力 – 游戏开发者需要跟踪玩家各种行为事件，以便形成流水日志，同时要保证玩家的所有事件是可追溯、可查询的。MongoDB的数据库实例，可将这些流水日志存储起来，并基于灵活的文档结构，让开发者不论是在开发期间、还是游戏已经发行的期间，都可以快速检索玩家的所有事件流。客户价值优化开发体验拉升运维能力根据数据显示，2023年一季度，腾讯的游戏领域收入达到483亿元，而其中132亿元来自国际市场，占游戏整体收入的27%，可见腾讯在海外市场的巨大潜力和影响力。对腾讯游戏而言，全球化协作体系已然成型。在多元化布局和全球化视野之下，中国游戏既要在内容创新、玩法创新上学习更多，也要将支持大规模玩家在线的后台技术越做越强。回顾与MongoDB的合作历程，腾讯海外游戏Level Infinite PGOS平台负责人谢磊谈到，无论在功能还是性能上，MongoDB都很好地契合了游戏业务场景，带给腾讯游戏的不只是功能价值，还有运维价值：简单、易用的控制台实现全面托管服务，即时自动扩缩容的专用服务器，为实时游戏提供低延迟和高可靠性。丰富的可视化监控提供实时可视化日志、监控面板，研发人员、管理人员可以实时监控业务运行状态。一键升配、降配能力在访问量突增时，一键自动扩容保障业务的正常运行；在流量低谷，一键自动缩容以节约成本。多维告警能力提供运行时间、状态异常等多维度告警能力，使问题可以在最短的时间内被捕捉并通知到用户。客户证言腾讯海外游戏Level Infinite PGOS平台负责人谢磊： “游戏行业的发展越来越由产品力主导。Level Infinite PGOS平台最大的使命是要能够将更新、更现代化的开发模式与腾讯已有能力结合在一起，形成开发体验良好的平台，其中尤为重要的是需要符合海外开发人员开发习惯。正是在这样的背景之下，我们的底层技术选择使用MongoDB。可以说，MongoDB让腾讯游戏Level Infinite PGOS如虎添翼。”

November 29, 2023

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MongoDB Database Observability: Integrating with Monitoring Tools

This post is the final in a three-part series on leveraging database observability. Welcome back to our series on Leveraging Database Observability! Our previous post showcased a real-world use case highlighting how MongoDB Atlas’s observability tools effectively tackle database performance challenges. Whether you’re a developer, DBA, or DevOps engineer, our mission is to empower you to harness the full potential of your data through our observability suite . Integrating Atlas metrics with your central enterprise observability tools can simplify your operations. By seamlessly working with popular observability tools, our approach helps teams streamline workflows and enhance visibility across systems. Integrating MongoDB Atlas with third-party monitoring tools MongoDB’s developer data platform combines all essential data services for building modern applications within a unified experience. Our purpose-built observability tools for Atlas environments offer automatic monitoring and optimization, guiding diagnostics tailored specifically for MongoDB. Additionally, we extend Atlas metrics into your existing enterprise observability stack, enabling seamless integration without replacing your current tools. This creates a consolidated, single-pane view that unifies Atlas telemetry with other tech and application metrics, ensuring comprehensive visibility into both database and full-stack performance. This integration empowers you to monitor, receive alerts, and make data-driven decisions within your existing workflows, driving greater efficiency. Below is a quick guide to modifying integration settings through the Atlas UI and the popular integrations we support: Navigate to the Project Integrations page in Atlas. Choose the organization and project you want to configure from the navigation bar. On the Project Integrations page, select the third-party services you’d like to integrate. Configure the chosen services with the required API keys and regions. Critical integrations for your observability platform With Atlas’s Datadog and Prometheus integrations, you can send critical MongoDB metrics to these platforms, empowering detailed, real-time monitoring. Through Datadog , you can track database operation counts, query efficiency, and resource usage, ideal for pinpointing bottlenecks and managing resources. Similarly, Prometheus enables you to monitor essential metrics like query times, connection rates, and memory usage, supporting flexible tracking of database health and performance. Both integrations facilitate proactive detection of issues, alert configuration for resource thresholds, and a cohesive view of Atlas data when visualized in Grafana. Atlas’s integration with PagerDuty streamlines incident management by sending metrics like performance alerts, billing anomalies, and security events directly to PagerDuty. This integration records incidents automatically, notifies teams upon alerts, and supports two-way syncing, ensuring resolved alerts in Atlas are reflected in PagerDuty. It enables efficient incident response and resource allocation to maintain system stability. With Atlas integrations for Microsoft Teams and Slack, you can route key metrics—such as query latency, disk usage, and throughput—to these channels for timely updates. Teams can use these insights for real-time performance monitoring, incident response, and collaboration. Notifications through these platforms ensure your team stays informed on database performance, storage health, and user activity changes as they occur. Use case: Centralized observability with MongoDB Atlas, Datadog, and Slack Let’s walk through a hypothetical scenario for ShopSmart, an e-commerce company that leverages MongoDB Atlas to manage its product catalog and customer data. As traffic surges, the DevOps team faces challenges in monitoring application performance and database health effectively. To tackle these challenges, the team leverages MongoDB Atlas’ integration with Datadog and Slack, creating a powerful observability ecosystem. Integrating MongoDB Atlas with Datadog: The team pushes key MongoDB Atlas metrics into Datadog, such as query performance, connection counts, and Atlas Vector Search metrics. With Datadog, they can visualize these metrics and correlate overall MongoDB performance with their other applications. Out-of-the-box monitors and dedicated dashboards allow the team to track metrics like throughput, average read/write latency, and current connections. This visibility helps pinpoint bottlenecks in real time, ensuring optimal database performance and improving overall application responsiveness. Setting up alerts in Datadog: The team configures alerts for critical metrics like high query latency and increased error rates. When thresholds are breached, Datadog instantly notifies the team. This proactive approach allows the team to address potential performance issues before they impact customers. Integrating Datadog with Slack: To ensure fast communication, alerts are sent directly to the dedicated Slack channel, “ShopSmart-Alerts.” This integration fosters seamless collaboration, enabling the team to discuss and resolve issues in real-time. With these integrations, ShopSmart’s engineering team can monitor performance quickly and address issues efficiently. The unified observability approach enhances operational efficiency, improves the customer experience, and supports ShopSmart’s competitive edge in the e-commerce industry. By leveraging MongoDB Atlas, Datadog, and Slack, the team ensures scalable performance and drives continuous innovation. Conclusion MongoDB Atlas empowers developers and organizations to achieve unparalleled observability and control over their database environments. By seamlessly integrating with central enterprise observability tools, Atlas enhances your ability to monitor performance metrics and ensures you can do so within your existing workflows. This means you can focus on building modern applications confidently, knowing you have the insights and alerts necessary to maintain optimal performance. Embrace the power of MongoDB Atlas and transform your approach to database management—because your applications can thrive when your data is observable. And that wraps up our Leveraging Database Observability series! We hope you learned something new and found value in these discussions. Sign up for MongoDB Atlas , our cloud database service, to see database observability in action. To dive deeper and expand your knowledge, check out this learning byte for more insights on the MongoDB observability suite and how it can enhance your database performance.

November 14, 2024