Last modified by Eva Torken on 2023/10/06 15:17
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1 {{container}}{{container layoutStyle="columns"}}(((
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3 {{warning}}
4 Please note that this microlearning is for the new monitoring stack only.
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6
7 Assessing the health of your systems is critical in a stable and robust integration solution. One of the aspects of assessing the health of your systems is looking at the runtime statistics.In this microlearning, we will educate you on the Runtime Statistics overview within the Manage phase of eMagiz.
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9 == 1. Prerequisites ==
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11 * Basic knowledge of the eMagiz platform
12 * Understanding of the Runtime statistics Dashboard pages
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14 == 2. Key concepts ==
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16 This microlearning centers around interpreting runtime statistics. With interpreting we mean: Analyzing the patterns based on the information presented to you. With runtime statistics we mean: Various information elements on system (runtime) level that will help to understand the health of the runtime.
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18 === 2.1 General interaction principles
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20 All graphs in the Manage phase are created with the aim to provide an easy interaction for users to slice the information as needed. Here are some general guidelines for that interaction.
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22 * Runtime, Queue and HTTP metrics are send to the Manage phase every minute and that interval is runtime specific
23 * Logs and error messages are send instantly to the Manage phase
24 * The average value of the last minute of each metric is sent to the Manage phase
25 * You can select the time dimension via the graph itself or via the top right menu. Other graphs will also respond to this selection
26 * You can return to the main dashboard via the top right button called "Show Main Dashboard"
27 * The main dashboard contains filter options to select specific runtimes or queues
28
29 == 3. Interpreting Runtime Statistics Key metrics ==
30
31 Assessing the health of your systems is critical in a stable and robust integration solution. One of the aspects of assessing the health of your systems is looking at the runtime statistics. Further to the Crash Course Microlearning around the Runtime Statistics Dashboard, this section will explain the Key metrics graphs.
32
33 === 3.1 Key Metric Graphs ===
34 When the runtime statistics are accessed, the first page shows a dashboard of the runtime statistics. An example is mentioned below.
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36 [[image:Main.Images.Microlearning.WebHome@intermediate-emagiz-monitoring-runtime-stats-keymetrics-1]]
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38 === 3.2 Memory usage - Heap ===
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40 The heap memory section displays the way in which message traffic is impacting heap memory. Heap memory is used for processing messages including transformation and transport of messages through channels. Whenever the heap memory is high in % used, it means the assigned heap memory might be insufficient for the message traffic.
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42 [[image:Main.Images.Microlearning.WebHome@intermediate-emagiz-monitoring-runtime-stats-keymetrics-2]]
43
44 === 3.3 CPU Usage ===
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46 This graph shows the usage percentage of the CPU assigned to the process (in this case runtime). The CPU is relevant for eMagiz as that component processes the message transformation, transport etc. A high percentage indicates that the CPU is very busy handling the message traffic of that process, which indicates that other processes handled by that same CPU(s) might experience delays or issues. The graph also shows the System CPU usage - this is the CPU of the system where the runtime is running in (usally the docker instance of machine).
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48 [[image:Main.Images.Microlearning.WebHome@intermediate-emagiz-monitoring-runtime-stats-keymetrics-3]]
49
50 === 3.4 Log events ===
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52 This graph shows the occurrences of log entries through time - the different colored lines represent the type of log entry (Log, Warning, etc.). Please make sure that you can see the colors of each type by scrolling down on the graph level. This information can be helpful to identify the timings and rhythym of log entries.
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54 [[image:Main.Images.Microlearning.WebHome@intermediate-emagiz-monitoring-runtime-stats-keymetrics-4]]
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56 === 3.5 Threads ===
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58 The graph shows the number of live threads that are currently running on your JVM (runtime). Each thread represents a task that is executed on that JVM. This could be the consumption of a message, the registration of a queue, etc. An ever-growing number of live threads indicates that there might be something wrong.
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60 [[image:Main.Images.Microlearning.WebHome@intermediate-emagiz-monitoring-runtime-stats-keymetrics-5]]
61
62 == 4. Key takeaways ==
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64 * There are 4 dashboard graphs that will help the more detailed analysis of a runtime(s)
65 * Next to CPU and memory consumption, a first view of logs and threads can be helpful to asses the health of a runtime
66 * The added value lies in combining the information from each of them into a coherent interpretation
67
68 == 5. Suggested Additional Readings ==
69
70 If you are interested in this topic and want more information on it please read the help text provided by eMagiz.
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