Synthetic monitoring is an invaluable technique for monitoring the availability and performance of modern digital platforms. By proactively simulating user journeys, synthetic monitoring identifies issues before they impact customers and revenue.
This comprehensive guide explores everything you need to know about synthetic monitoring in 2024, including:
- Detailed overview of how it works
- Analysis of key benefits
- Practical use cases
- Comparison to real user monitoring
- Types of synthetic tests
- Leading tools and vendors
- Best practices for implementation
Let‘s dive in and see how synthetic monitoring is becoming essential for digital businesses today.
What is Synthetic Monitoring and How Does it Work?
Synthetic monitoring automatically emulates user traffic to proactively identify performance issues and outages. Rather than passively monitoring real user interactions, synthetic monitoring relies on scripted scenarios that simulate common customer pathways through an application.
These scripts contain checkpoints that perform specified actions and collect data to assess:
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Application availability – Is the website or app accessible?
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Functionality – Are all features working as expected?
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Performance – How fast are pages loading? Are there any slow elements?
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Transactions – Can the script complete an entire user journey?
As checkpoints are executed, metrics are measured and results reported back to the synthetic monitoring platform. Alerts are triggered if transactions fail or performance degrades below configured thresholds.
Synthetic monitoring platforms offer options for scripting like waterfall, Har files, Selenium IDE, or reusable vs. unique scripts. Scripting methods should be chosen strategically based on monitoring objectives.
Key Benefits of Synthetic Monitoring
Synthetic monitoring provides major benefits over traditional uptime monitoring or reliance on customer reports:
- Early detection – Issues can be identified proactively before impacting users
- Simulate user conditions – Scripts can emulate different locations, browsers, and devices
- Full journey visibility – Transaction scripts exercise all steps in complex processes
- Isolate performance – Granular web performance metrics identify slow elements
- Establish baselines – Historical data enables performance benchmarking
- Monitor 3rd parties – Confirm CDNs, APIs, payment gateways meet SLAs
According to Gartner, synthetic monitoring can lower incident resolution time by 50-75%. With the costs of downtime often reaching thousands per minute, the ROI is significant.
Common Use Cases and Applications
Synthetic monitoring supports several vital use cases:
- SLA monitoring – Confirm web and mobile apps meet uptime and performance SLAs
- Release validation – Test new versions have no regressions before launch
- Regional performance – Check performance in different geographic locations
- Third-party monitoring – Monitor partner web services and APIs you depend on
- Frontend vs backend tracing – Pinpoint whether issues originate in frontend or backend
- Session simulation – Emulate full user sessions across multiple pages/functions
It is a versatile technique that can monitor virtually any digital touchpoint, including:
- Websites
- Mobile apps
- APIs
- Microservices
- Serverless functions
- Third-party web services
Public-facing assets and mission-critical customer journeys should be prioritized for synthetic testing.
Synthetic vs. Real User Monitoring
Real user monitoring (RUM) is another vital monitoring technique. RUM passively collects performance data from actual user sessions versus synthetic scripts.
| Synthetic Monitoring | Real User Monitoring |
|---|---|
| Active monitoring via scripts | Passive monitoring of real users |
| Simulates user journeys | Collects live production data |
| Proactive outage identification | Confirms real user impact |
| Tests apps without traffic | Requires actual user activity |
RUM provides valuable real-world data but lacks ability to test scenarios without traffic. Synthetic and RUM together provide complete monitoring coverage. RUM validates that synthetic data mirrors real user experience.
According to Gartner, organizations should utilize both RUM and synthetic monitoring for comprehensive assessment.
Types of Synthetic Monitoring Tests
Synthetic monitoring encompasses various types of scripted tests:
Availability Testing
Checks if assets are up and accessible for end users. Simple but critical for monitoring uptime.
Transaction Testing
Mimics entire user journeys across multiple functions to identify failures. Emulates workflows like account sign-up.
Web Performance Testing
Measures page load times, isolating performance by page elements. Checks for regressions after changes.
API Testing
Validates API functionality, performance, and reliability. Essential for modern microservices architectures.
Implementing Synthetic Monitoring Best Practices
Here are best practices to consider when implementing synthetic monitoring:
- Focus scripts on business KPIs – Align monitoring to critical workflows that impact revenue, conversions, etc.
- Balance simplicity and realism – Scripts should be realistic but simple enough to maintain.
- Monitor from multiple regions – Check performance in locations where users are concentrated.
- Alert intelligently – Set dynamic thresholds based on baselines to avoid false positives.
- Validate across environments – Use same scripts across dev, test, stage, and prod for consistency.
- Correlate with real user data – Review synthetic and RUM data together for complete picture.
- Automate script updates – Use CI/CD integration to update scripts after application changes.
Well-architected synthetic monitoring provides maximum benefits.
Leading Synthetic Monitoring Tools
All major APM vendors offer synthetic monitoring capabilities:
| Provider | Key Features |
|---|---|
| SmartBear | Synthetic API testing, advanced alerting |
| Catchpoint | Full-stack monitoring, root cause analysis |
| Dynatrace | Combined RUM and synthetic |
| New Relic | Integrated via New Relic One APM |
| AppDynamics | Scripting via Selenium IDE access |
| ThousandEyes | External web monitoring |
There are also SaaS monitoring tools like Pingdom or Uptime.com focused specifically on synthetic testing.
Open source options include Locust and Selenium for test creation. Solutions like Prometheus and Grafana can collect and visualize results.
Getting Started With Synthetic Monitoring
Here are steps to start leveraging synthetic monitoring:
- Identify critical business workflows – Map journeys that mimic real user interactions.
- Develop reusable scripts – Scripts should be parameterized and modular for reuse.
- Configure synthetic monitoring tool – Most APM or SaaS monitoring tools support synthetic testing.
- Set dynamic thresholds – Establish baseline-based alert thresholds to avoid false alerts.
- Expand monitoring reach – Monitor internally and externally facing assets across various environments.
- Analyze results – Review synthetic data alongside RUM and other signals for comprehensive monitoring.
Well-instrumented synthetic monitoring provides actionable data to drive digital experience improvements.
The Future of Synthetic Monitoring
While extremely useful, synthetic monitoring has room for innovation. Emerging capabilities like:
- Intelligent scripting – ML to automatically generate scripts modeling real user behavior
- Advanced integration – Leveraging distributed tracing data for contextual synthetic monitoring
- Automated validation – Using synthetic scripts for CI/CD testing automation
- Multilayer emulation – Modeling entire stacks from app to network level
As digital ecosystems grow more complex, synthetic monitoring must also evolve to remain a key monitoring technique.
Conclusion
Synthetic monitoring delivers immense value by enabling proactive identification of digital experience issues before they affect customers.
Sophisticated simulation of real user journeys across critical apps, web services, and APIs provides actionable data to resolve problems. When combined with real user intelligence, it becomes a foundational monitoring technique.
Organizations should strategically leverage synthetic monitoring to drive visibility, reliability and continuous improvement across their digital delivery ecosystem.
