This post is the first in a three-part series on leveraging database observability.
Observability has evolved into an essential information technology component, offering advanced insights into system performance beyond traditional monitoring. While monitoring aims to identify problems, observability helps understand and resolve them. Businesses prioritizing observability experience less downtime, leading to enhanced user experiences and improved ROI.
Indeed, Splunk’s The State of Observability 2023 report quantified the financial impact of downtime—more than $150,000 per hour. Furthermore, observability leaders reported 33% fewer outages and achieved eight times better ROI than new adopters.
Throughout this series, we’ll define database observability at MongoDB, explore our suite of tools, delve into third-party integrations, and discuss everyday use cases. We will also establish a shared methodology and vocabulary for discussing observability at MongoDB and highlight the tools and features that have delivered value for our customers.
Observability and MongoDB’s strategy
Monitoring involves using tools to track real-time operations and alert teams to issues. As defined by Gartner, observability evolves monitoring into a process that provides deep insights into digital business applications, enhancing innovation and customer experience. The key difference is that monitoring detects the presence of issues, while observability gathers detailed information to understand and resolve them, which is crucial for modern IT infrastructure needs.
Databases, in particular, play a critical role in this IT ecosystem, where performance and resilience directly impact business outcomes. This advancement is essential for DevOps, Database Administrators, and economic buyers responsible for these databases, as it enhances system reliability, encourages innovation, and supports financial objectives. Ultimately, observability provides comprehensive insights into system performance, health, and reliability by seamlessly integrating and contextualizing telemetry data.
MongoDB leverages a unique observability strategy with out-of-the-box tools that automatically monitor and optimize customer databases. Explicitly designed for MongoDB environments, our system provides continuous feedback and answers critical questions—What is happening? Where is the issue? Why is it occurring? How do I fix it?—to enhance performance, increase productivity, and minimize downtime.
Supporting MongoDB Atlas (our fully managed platform), Cloud Manager, and Ops Manager, as well as tailored monitoring solutions for the full range of developer data platform products (from enhanced search functionalities to app services and search nodes). Our approach meets the evolving needs of customer applications by:
Leveraging MongoDB expertise: The MongoDB observability suite integrates efficiency and best practices from the beginning of the development cycle. As MongoDB platform experts, we use our deep knowledge to provide top-tier optimization insights. We apply our extensive understanding of our tools to ensure our customers benefit from a high-performing and resilient database.
Offering streamlined metrics: We integrate our metrics seamlessly into our customers’ central observability stacks and workflows. This creates a ‘plug-and-play’ experience that effortlessly aligns with popular monitoring systems like Datadog, New Relic, and Prometheus. Thus, it provides a unified view of customer application performance and deep insights into their database within a comprehensive dashboard.
Breaking down MongoDB’s observability offerings
Tailored database performance management
MongoDB employs automated tools for comprehensive database performance management, focused on real-time optimization, strategic scaling, and best practices in schema design. Using out-of-the-box tools ensures high-performing, scalable, and cost-efficient database environments ideal for modern applications.
Key features include:
Performance Advisor: Provides index recommendations to improve read and write performance, significantly boosting overall efficiency.
Schema Advisor: Supports flexible schema design and query execution analysis to enhance performance, scalability, and validation rules for schema compliance.
Opt-in Autoscaling (only available in Atlas): Optimizes resource use, manages operational costs, ensures continuous availability, and adjusts resources based on demand, preventing downtimes.
Performance Advisor in action
Foundational monitoring for in-depth insights
MongoDB provides foundational monitoring tools and out-of-the-box insights for optimal cluster health and performance after initial database setup. These tools both help reduce the burden of performing manual tasks while laying the groundwork for detailed and granular analysis of metrics and system performance aimed at enhancing query performance, reducing execution times, and lowering resource usage.
These tools include:
Monitoring Charts: These charts offer detailed metrics on hardware, database operations, replication status, sharded, and search/vector search with a fine-grained metric resolution to identify issues and track trends.
Real-Time Performance Panel: This panel displays live network traffic, database operations, and hardware stats, helping to identify critical operations, evaluate query times, and monitor network load and throughput.
Query Insights: The recently announced Namespace Insights provides users with collection-level latency statistics. At the same time, the enhanced cluster-centric Query Profiler gives an expanded view of query performance, significantly enhancing visibility and operational efficiency across the cluster. Learn more about both!
Comprehensive alerting and seamless integrations
MongoDB Atlas’s sophisticated alerting system offers over 200 event types, providing teams with comprehensive control and visibility over their environments. Users can fine-tune their alerting strategy with customization options to fit their specific requirements. Additionally, MongoDB Atlas enhances team collaboration and ensures a unified view of application performance through seamless integrations with third-party tools like Slack, PagerDuty, and DataDog. These integrations simplify management tasks and leverage existing workflows for optimum operational effectiveness.
What’s next? Enhanced database observability
Observability is more than just a technical requirement—it’s a strategic asset that enhances operational efficiency and economic viability. Through MongoDB’s observability suite, organizations can optimize and scale system performance and fuel innovation. MongoDB is dedicated to continuously improving this suite to manage large-scale data better and meet demanding performance standards. Our commitment is reflected in our efforts to advance MongoDB’s observability features, providing specific insights that deliver actionable intelligence tailored to our customers’ needs.
Look for the next post in this series, where we’ll explore various tools and their integration, illustrated through common use cases.
Sign up for MongoDB Atlas, our cloud database service, to see database observability in action. For more information, see Monitor Your Database Deployment.
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