Cloud Database Monitoring for AWS, Azure & GCP

Once something only “nice-to-have” now for businesses that serve high volume and mission-critical apps, Cloud adoption has become an absolute “must-have”. With companies continuing to increase their usage of cloud offerings from Amazon Web Services (AWS), Microsoft Azure and Google Cloud Platform (GCP), it is only logical that the databases storing their application data are being moved with them to support their eCommerce, ERP, healthcare application services, fintech apps, SaaS based products and other globally available customer-facing systems and applications.

However, just like with all of the other things listed here previously, cloud databases don’t run themselves. Cloud databases need continual visibility into performance, availability, security threats from those who have access to them, how well they are storing their data, how well their data is being replicated, and how much they cost.

Failure to establish a monitoring structure means that when something breaks, the problem will most likely be hidden in the noise of all other things running, until the issues cause the service provided to fail, slow down user experience and resource utilization, or drive up the user’s cloud bill(s).

Cloud database monitoring gives users a solution to the biggest challenges that they face:

• Provides real-time reporting of database performance
• Alerts you to potential problems prior to them affecting an end-user
• Provides detail on slow running queries that will degrade user experience
• Shows you the amount spent on cloud resources by databases

Identifies abnormal behaviors (anomalies) that are the result of: cyber threats, failed deployment(s) and unhealthy database nodes

Let’s break down how to use Cloud Monitoring solutions across AWS, Azure and GCP, as well as which types of tools and/or services you should implement to achieve optimal performance from your databases.

Cloud Database Monitoring on AWS

AWS leads the cloud market with a massive suite of managed database services. Monitoring needs slightly vary depending on which database you choose, but the core principles remain the same: metrics, logs, events, dashboards, and automated alerts.

Common AWS Database Services

Amazon CloudWatch

• CloudWatch monitors key metrics in real-time, including CPU, Memory, and FreeStorageSpace, Read/Write Latency, Network Throughput, Disk Queue Depth, and Database events.
• Enhanced RDS Monitoring (Enhanced RDS Monitoring) provides additional OS-level metrics that cannot be seen in the default views of CloudWatch.
• AWS X-Ray: With X-Ray, you can visually trace requests through microservices and pinpoint performance issues that stem from database performance issues.
• AWS Trusted Advisor: Trusted Advisor helps to identify misconfigured resources that can put your organization at risk and lead to overspending on resources.

AWS Monitoring Can Prevent:

• An instance failing due to storage capacity
• An application receiving too many 503 (service unavailable) response codes due to over-use of the database connection pool
• An application degrading in performance due to slow-running queries
• A shopping cart, booking system, or other Application Programming Interface (API) breaking due to excessively high latency
• A dynamic database experiencing throttling as the result of exceeding the addressable write/read capability

Azure Monitoring for Cloud Databases

Azure leads enterprise cloud adoption, especially for organizations invested in Microsoft technologies.Its monitoring tools focus on observability and performance. It provides diagnostics, query insights, log tracing, and error reporting to help teams detect issues early and scale confidently.

Common Azure Database Services

Azure Monitoring Tools are used for monitoring databases. Below is a summary of the various methods of Azure monitoring tools:

• Azure Monitor – Allows you to monitor all database metrics associated with your Azure database workload. It provides the ability to see events and how your database is performing when scaling over time.
• Application Insights – Tracks an end user’s route through the UI or API all the way down to the execution of a database query.
• Query Performance Insight – Provides visibility into the SQL Queries that are consuming the most resources within an Azure SQL DB.
• Azure Log Analytics – Collects all diagnostics logs from within your organization. It can be used to detect any spikes, errors or abnormal trends in log numbers.

Azure Monitoring Powers

• Monitoring trigger-based automatic scaling
• Query insights are built into Azure SQL DB.
• Logging enterprise-level hybrid + regulated workloads.
• Diagnostics deeply tied to APIM, UI, and microservices.

Problems/obstacles Azure Monitoring can solve for You

• DTU over-consumption.
• Long-running queries blocking transactions.
• Index problems preventing quick access in highly relational workloads.
• Overselling partitions on CosmosDB leads to concurrency issues.
• Storage or connections may spike and affect SLAs.

Google Cloud’s Cloud Database Monitoring (GCP)

GCP has been built for the scale of distributed systems, AI pipelines, analytical workloads, and containers. Therefore, monitoring services for GCP focus heavily on Big Data, observability, and Intelligently designed dashboards.

Common GCP Database Services

When it comes to the top monitoring tools for GCP, Google Cloud Monitoring (formerly known as Stackdriver) is the first choice as it can monitor performance, downtime, log files and incidents/error codes, all in one view across many clouds or microservices. Moreover, Google Cloud Trace allows users to trace back any slowness within their application, while Google Cloud Logging & Error Reporting will show failures, noise, and logs that are atypical as compared to normal traffic patterns.

For those organizations that use BigQuery, the monitoring provided by BigQuery Monitoring with Billing Export shows the costs associated with each query, which is essential for data analytics.

The Advantages of Monitoring with GCP Include:

• GCP provides intelligent dashboards designed for distributed systems.
• Monitoring with GCP gives you real-time alerts for infrastructure problems as well as query execution failures.
• With GCP monitoring, users have access to deep insights into their logs, including the ability to spot anomalies within their data.
• Monitoring with GCP allows users to get the cost-per-query metric for heavy analytical queries.
• GCP provides full stack (multiple layers or services) monitoring for GKE and Firebase containers.

Monitoring with GCP Keeps You from Experiencing Failures Such as:

• Delays in the execution of BigQuery (slot exhaustion)
• Issues related to locked partitions that impact workloads across global instances on Spanner
• Running out of storage that causes Cloud SQL instances to go down
• Sluggish behaviour during document indexing, which results in latency with Firestore
• Memory pressure causing the eviction of cached objects

Strategies to develop a winning monitoring strategy for Databases in a multi-cloud environment:

• Consolidating dashboards so that teams do not have to switch between many different consoles
• Simultaneously tracking both query performance and infrastructure performance metrics
• Provide a way to monitor all of the costs associated with cloud databases linked with read/write/storage/compute
• Create alert thresholds for latency, storage, CPU use, and connection pool size
• Use Log-Based Anomaly Detection to help identify bad deployments and/or possible threats
• Monitor replication health to ensure there are no stale or failed nodes

Integrate your monitoring efforts with your DevOps teams so that they are working collaboratively to support and improve their database experience.

Best Multi-Cloud Database Monitoring Platforms (Optional Add-Ons)

If you run distributed or multi-cloud database environments, third-party observability platforms offer game-changing benefits:

Important Considerations

Database monitoring can either establish a stable, fast and secure platform for data storage, or a system that crashes under heavy loads or sudden intrusions.

While AWS, Azure and GCP offer a variety of monitoring products for their database systems, the one thing they all offer in common is the assurance that by “eliminating blind spots,” you can avoid experiencing downtime and create the opportunity for continued growth.

If you have:

• A high-traffic web store → Monitor your average latency and connection status
• An enterprise regulated database system → Monitor all query logs for errors and time to process, as well as for data consistency and durability
• A Distributed NoSQL database → Monitor all aspects of your database including replication, partitioning, and throughput
• A Big Data analytics pipeline (data lake) → Monitor query cost, available slots for processing, and any anomalies in processing large data volumes

When you invest in monitoring your cloud-based database, you also have the following advantages:

• No unexpected downtime
• Faster ability to troubleshoot any issues
• Faster application response times
• Lower cost for using your cloud service for database storage
• Increased trust from customers

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