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Monitoring microservices
- 3. An average production system Database • Is the web server up? • Is the database up? • Can the webserver talk to the db?
- 4. What are you actually monitoring? Business Capability Application Infrastructure Are my servers running?Is my application process running?Can users place an order? Monitoring Area
- 5. Monitoring Concerns Capacity Performance Health Is the server up?Is there high CPU?Do I have enough disk space? Is my application generating exceptions? How quickly is my system processing messages? Can I handle month end batch jobs? Is the server up? Is there high CPU? Do I have enough disk space? Application Infrastructure Can users access the checkout cart? Are we meeting our SLAs? What is the impact of adding another customer? Business Capability
- 6. Interaction Type Proactive Reactive Passive The monitoring system can display metrics The monitoring system alerts me when something happens The monitoring system automatically takes actions to repair the system
- 7. A Monitoring Philosophy Business Capability Application Infrastructure Capacity Performance Health Monitoring Area Monitoring Concern Proactive Reactive Passive Interaction Type
- 8. Recap: What are we monitoring? Database • Is the web server up? • Is the database up? • Can the webserver talk to the db? Infrastructure PassiveHealth
- 10. 27 28 29 30 31 32 33 34 35 37 40 41 42 43 45
- 11. Recap: What are we monitoring? • Warn me with the queue length exceeds 50 Infrastructure ReactivePerformance
- 12. A Monitoring Philosophy Business Capability Application Infrastructure Capacity Performance Health Monitoring Area Monitoring Concern Proactive Reactive Passive Interaction Type
- 13. What happens when we distribute the systems?
- 18. Let’s look at queue length
- 19. Queue Length • Queue length is an indicator of work still outstanding • High queue length doesn’t necessarily indicate a problem though Stable or decreasing is good Increasing is bad
- 22. Processing Time • Processing Time is the time taken to successfully process a message • Processing Time does not include error handling time • It is independent of queue wait time Stable or decreasing could be good Increasing is bad
- 26. ✔⌛ ⏱️ Critical time ⏱️ Critical time = The entire time taken to process a message successfully
- 27. • Critical Time is the total duration between when a message is created to when it is processed Critical Time = Time in Queue + Processing Time + Retry Time + Network Latency Time Critical Time Stable or decreasing could be good Increasing is bad
- 28. Putting these together • Each of these metrics presents a piece of the puzzle • Look at them from an endpoint’s perspective, not per message • Looking at them together gives great insight into your system Critical Time Processing Time Queue LengthCritical Time Processing Time Queue LengthCritical Time Processing Time Queue Length
- 30. Detecting Connectivity • Distributed systems typically work when other parts aren’t available • How do you know the endpoint you’re sending messages to is actually processing messages?
- 31. Detecting Connectivity Peer-to-peer connectivity tells us if an endpoint is actually processing messages from another
- 34. How do we collect all this info? ⏱️ • Processing Time • Critical Time • Queue Length • Connectivity • Reporting Metric • Message Type • Timestamp • Value • Reporting Metric (N bytes) • Message Type (N bytes) • Timestamp (8 bytes) • Value (8 bytes)
- 35. How do we collect all this info? • Epoch time (8 bytes) • Dictionary of Metric Types (n* (N + 4) bytes) • Dictionary of Message Types (n * (N + 4) bytes) • An array of: • Reporting Metric index (4 bytes) • Message Type index (4 bytes) • Epoch offset (4 bytes) • Value (8 bytes)
- 36. Getting all the data
- 37. Getting all the data
- 38. Getting all the data