Hello friend, are you adopting serverless architectures for your applications? That‘s great! Going serverless enables increased flexibility, auto-scaling capabilities and pay-per-use cost savings. However, the dynamic nature of serverless also introduces new challenges in monitoring and debugging compared to traditional applications.
This is where advanced tools become critical for peeking inside the black box, understanding how your functions execute in production and catching issues quickly.
In this comprehensive guide, we‘ll cover the top tools available specifically for serverless monitoring and debugging along with best practices for production visibility.
Why Care About Monitoring Serverless?
But before we jump into the tools, it‘s important to understand why monitoring and debugging requires specialized solutions for serverless environments.
As per 2022 State of Serverless survey by LambdaLabs, over 70% of teams are now adopting serverless for its benefits:
Serverless Adoption in 2022 (Source)
However, traditional monitoring approaches don‘t work well here due to unique aspects of serverless like:
✅ Ephemeral function instances
✅ Flexible scaling
✅ Dependence on event triggers
✅ No visibility into runtime environments
This makes it harder to trace issues and find root causes. Important metrics like cold starts and execution contexts are not captured at all!
Specialized tools are thus needed that tightly integrate with serverless platforms and provide deeper insights.
Let‘s look at the key capabilities to check when choosing any serverless monitoring solution:
Now that you know what to evaluate, let me introduce you to some great options available for every need and budget!
1. Thundra
Thundra is an end-to-end solution providing advanced debugging, observability and security capabilities for serverless.
Here‘s a quick overview of what it offers across monitoring, troubleshooting and more:
Key Highlights of Thundra:
⛅️ See performance metrics for all functions
🔬 Distributed tracing showing complete request flows
⚙️ Debug code locally or remotely with breakpoints
🔔 Alerting for errors and anomalies via Slack, PagerDuty
🔒 Security checks for credentials, policies
📊 Customizable dashboards
Thundra is tightly integrated with serverless runtimes like AWS Lambda, enabling deep insights even into cold starts. The local debugging support is comparable to offerings like SLS Dev Tools discussed later.
In addition, the production monitoring, distributed tracing and security capabilities make Thundra a fairly complete solution.
Pricing starts at $29/month after a 15-day free trial. Well suited even for mid-size production workloads.
Thundra‘s Serverless Debugger
2. Lumigo
Lumigo focuses strongly on tracing and debugging of serverless applications on AWS, Azure and GCP.
It enables deep monitoring into functions and external services using the following key features:
What Lumigo Provides:
🔬 Distributed end-to-end tracing
🔎 Detect bottlenecks and critical paths
📄 Log search with filtering
⏱ Performance metrics
💵 Cost visibility and right sizing
📌 Debugging via execution traces
The complete transaction tracing is extremely useful for understanding waits and dependencies across cloud resources trigged by serverless executions. This helps diagnose tough issues beyond just stack traces.
The generously tiered free plan makes it easy to get started with monitoring your functions.
Lumigo Serverless Monitoring Dashboard
3. Epsagon
Epsagon provides an intuitive observability platform for gaining a unified view across complex serverless environments.
Notable aspects of their offering include:
What Epsagon Provides:
📊 Pre-built and custom metrics dashboards
🗺 Service maps
🔗 End-to-end transaction tracking
💰 Cost visibility with right sizing recommendations
⚙️ Anomaly detection using AI
📢 Smart alerting to catch issues proactively
🔬 Log aggregation from all sources
Epsagon uses automated instrumentation to trace requests across services without requiring code changes. This works even for monitoring existing applications immediately.
The AI powered features provide actionable recommendations that act as a free tuner! Generous free tier to get started.
Epsagon Serverless Monitoring
Developer Focused Debugging Tools
The options covered above provide production monitoring capabilities critical for SREs and Ops teams.
But for developers building and testing serverless apps locally, more debugging focused tools are more useful.
Let‘s look at some excellent choices available:
4. SLS Dev Tools
SLS Dev Tools is an open-source tool focused primarily on local debugging of serverless applications before deployment.
Key highlights:
💻 Local breakpoint debugging
📟 Step through code execution
🔎 Inspect variable values
📊 Metrics and log panes
🪄 Integrates with Serverless Framework
This tool provides the closest experience to debugging traditional apps by enabling developers to simulate different events and test execution flows.
SLS Dev Tools Debugger
However, SLS Dev Tools lacks production monitoring capabilities that commercial platforms offer. The keyboard friendly UI takes some learning. Overall a great open source solution for testing locally.
5. Stackery
Stackery provides cloud-based debugging, monitoring and management for serverless applications on AWS.
Key highlights:
👩💻 Live debug remote Lambda functions
⚙️ Pause executions and step through code
🗃 Log aggregation from various sources
🔗 Distributed tracing
📈 Performance metrics per function
The workflow editor gives a graphical way to build applications which can then be deployed and managed end-to-end.
The integrated Stackery Status Center aids collaborative incident response – very useful for teams operating serverless at scale.
Stackery Visual Workflow Editor
Open Source vs Commercial Tools
We‘ve covered both open source tools like SLS Dev Tools as well as commercial platforms so far. Let‘s compare them across key aspects:
| Capability | Open Source | Commercial |
|---|---|---|
| Cost | Free | Paid plans |
| Features | Core debugging/monitoring capabilities | More advanced like AI assisted alerting, security checks etc |
| Scalability | Varies across projects | Enterprise grade |
| Learning Curve | Developer friendly | Some initial setup needed |
| Support | Community based | Official customer support |
Open source tools work well for developers getting started while commercial platforms are recommended once you reach 20+ functions in production.
Combining both allows complementing debugging during build with observability post deployment!
Key Considerations for Picking Tools
Here are top things to factor when deciding monitoring solutions for your serverless environment:
Your Skill Sets
- Developer teams might prefer advanced debugging capabilities while SRE teams focus on production monitoring.
Complexity of Architecture
- Aggregated views work well if using 10+ services. If scope is limited, start small.
Organization Maturity
- Beginners can rely on basic vendor tools while industrialized setups require advanced solutions.
Budget Availability
- Balance value vs price. Weigh free tiers generously offered by many tools.
Learning Curve
- Developer tools have lower overheads to get started quickly compared to platforms needing more setup.
Best Practices for Serverless Monitoring & Alerting
Tools provide the data but actionable alerting and wisdom to interpret metrics comes from best practices around monitoring.
Here are key aspects to incorporate:
1. Have a Monitoring & Alerting Strategy
Document what metrics to track, thresholds for alerts and notification channels based on priorities.
2. Configure Alerts Thoughtfully
Strike a balance between sensitivity vs. noise based on contexts. Leverage predictive capabilities.
3. Review Metrics Regularly
Spot trends proactively. Is there a gradual increase in invocation errors for example?
4. Democratize Dashboards
Enable teams to create their own views by function/services monitored vs. central bottlenecks.
5. Invest in Visualization
Charts and graphs enable faster anomaly detection through pattern recognition compared to raw data.
6. Trace Regressions to Code Changes
Integrate deployments with monitoring to correlate production issues with commits.
7. Practice Incident Management Muscle Memory
Document postmortems periodically to train diagnosis skills even if on simulated failures through GameDays.
Key Takeaways
We‘ve covered a variety of capable tools to monitor and debug your serverless applications with. Here‘s a quick summary:
- 🛠 SLS Dev Tools & Thundra – Advanced debugging support
- 📈 Lumigo & Epsagon – End-to-end transaction tracing
- 👩💻 Stackery – Workflow management platform
- 💰 Dashbird & Lumigo – Cost visibility and rightsizing
- 📊 CloudWatch – Basic vendor native metrics
- 🔨 Combine multiple tools – For complete observability
Hopefully this guide gives you a framework to evaluate options matching your specific requirements and constraints.
Getting the right monitoring visibility ensures you extract maximum leverage from the serverless paradigm while minimizing surprises! Combine it with security best practices, CI/CD pipeline and thoughtfully managing dependencies to productionize serverless successfully.
Let me know if you have any other questions!
