Foglight for MongoDB ensures the health of your MongoDB infrastructure
Rapidly detect, diagnose and resolve performance issues — wherever, whenever and however they occur. Foglight for MongoDB delivers comprehensive database, storage and virtualization monitoring, as well as advanced workload analytics. Intuitive, web-based dashboards provide a consolidated view of your physical, virtual and cloud-based databases, so you can quickly fix problems that might affect database performance or availability.
Foglight offers unattended 24x7 data collection. Its agentless architecture and minimal footprint ensure overhead is negligible on monitored hosts. Foglight deploys quickly and easily, too.
Get quick access to health information, key performance metrics and critical alarms for all your database instances. Take immediate action to resolve performance issues on MongoDB servers and their host systems.
Easily track the number of current connections and the associated memory requirements. Receive alerts when the number of connections exceeds normal limits.
Review a robust set of metrics that shed light on all aspects of memory utilization, including allocated memory and resident memory. Get alerts if allocated memory is insufficient to store all indexes, or is insufficient for peak performance.
Receive alerts when the number of page faults is high or increasing, so you can consider increasing allocated memory.
Track and analyze the load on your database with a complete set of database operation statistics, including details on replication and sharding.
Get comprehensive monitoring for all profiled operations, aggregated into groups for statistical analysis. Include your own queries in the aggregation. View operation-specific information by simply selecting a row. (This feature requires system profiling to be enabled on the MongoDB server.)
Automatically discover and monitor MongoDB replica sets, including member status, health, optime date and timeouts. Get alerts if members become unreachable or their status changes, and when optimes are out of sync.
Identify lagging in the sharding process and quickly troubleshoot the root cause, such as high lock percentages.
Ensure MongoDB resiliency by monitoring multiple metrics about commits to the journal, as well as background flushes and total time writing the data to disk.
Resolve MongoDB concurrency issues in record time with historical lock analysis.
Easily identify discrepancies by comparing node configurations against standard configuration templates, objects and historical data.
Avoid false alerts with adaptive Intelliprofile thresholds, which ensure alarms are only triggered when baselines are breached. Easily manage and annotate alarms, including scheduling blackouts for maintenance periods.
Speed problem resolution and discover chronic issues with embedded expert advice, and easy search of your history of alarms and solutions.
Monitor hundreds of MongoDB database servers from a single management server.
Execute data collection through remote agents that ensure minimal overhead (no more than 2% CPU) is added to monitored database instances.
Ensure high-integrity data collection with frequent collections, or customize collection frequency to meet your business requirements.
Store historical monitoring data in the embedded data warehouse — without needing to purchase or install additional database instances for storage of monitoring data. External repositories can be leveraged in larger deployments.
Rapidly detect, diagnose and fix issues across physical, virtual and cloud-based servers.
With the rise of autonomous databases – and all the other scary changes in database management systems – you, as a DBA may be wondering whether you’re in the midst of a DBApocolypse. You are. And this is your definitive survival guide.
A common challenge in many IT teams is the “blame game” where developers blame DBAs for stability and performance issues and vice versa. What if you had complete visibility and continuous monitoring to understand the root cause of database issues?
This technical brief outlines the top five complications faced by DBAs amid the rush of new database technologies in recent years. For each challenge it provides background, context and the benefits Foglight for Databases brings in addressing them.
To gain insight into the evolving challenges for DBAs, Quest commissioned DBTA to survey DBAs and those responsible for the management of the corporate data management infrastructure. The results are in and the thought-provoking findings are now available
Databases evolve fast and smart database administrators (DBAs) evolve even faster. As the landscape shifts from reliance on relational database management systems (RDBMS) to public-cloud Database as a Service (DBaaS), so do the responsibilities of the DBA
Research reveals how continued data growth, evolving responsibilities and cloud technology are affecting DBAs.
Envision Healthcare staffs emergency rooms and clinical departments with doctors. Their Services extend to as many as 1,800 clinical departments and 25 million patient encounters a year. To manage it all safely, they rely on Foglight for Databases.