[{"data":1,"prerenderedAt":566},["ShallowReactive",2],{"content-svc-lambda-guides-aws-lambda-operator-guide-visualization":3},{"markdown":4,"frontMatterAttributes":5,"bodyRaw":8,"menu":9,"menuType":563,"isCollapseableMenu":12,"nextDocItem":450,"previousDocItem":440,"contributorPaths":564,"contentName":565,"slug":449,"readingTime":58},"\u003Cp>In the queries shown so far, you can export the results to markdown or CSV format. You can also create \u003Ca href=\"https:\u002F\u002Fdocs.aws.amazon.com\u002FAmazonCloudWatch\u002Flatest\u002Flogs\u002FCWL_Insights-Visualizing-Log-Data.html\">visualizations from queries\u003C\u002Fa>, providing there is at least one aggregation function. The stats function allows you to define aggregations and grouping. Since Lambda functions always provide a timestamp, you can also produce time series charts, grouped into intervals using the bin function.\u003C\u002Fp>\n\u003Cp>The previous \u003Cem>logInsightsJSON\u003C\u002Fem> example filtered on upload size and upload time and excluded first invocations. This resulted in a table of data. For monitoring a production system, it may be more useful to visualize minimum, maximum, and average file sizes to find outliers. To do this, apply the stats function with the required aggregates, and group on a time value such as every minute:\u003C\u002Fp>\n\u003Cpre>\u003Ccode class=\"language-sql\">fields @message\n| filter @message like \u002FINFO\u002F\n| filter uploadedBytes > 1000000\n| filter uploadTimeMS > 1000\n| filter invocation != 1\n| stats min(uploadedBytes), avg(uploadedBytes), max(uploadedBytes) by bin (1m)\n\u003C\u002Fcode>\u003C\u002Fpre>\n\u003Cp>After running the query, switch to the \u003Cem>Visualization\u003C\u002Fem> tab to see the results:\u003C\u002Fp>\n\u003Cp>\u003Cimg src=\"\u002Fassets\u002Fexternal\u002Fservice\u002Flambda\u002Fguides\u002Faws-lambda-operator-guide\u002Fassets\u002Fimages\u002Fmonitoring-observability-figure-14.png\" alt=\"\">\u003C\u002Fp>\n\u003Cp>After you have finished building the visualization, you can optionally add the graph to a CloudWatch dashboard. To do this, choose \u003Cem>Add to dashboard\u003C\u002Fem> above the visualization. This adds the query as a widget and enables you to select automatic refresh intervals, making it easier to continuously monitor the results:\u003C\u002Fp>\n\u003Cp>\u003Cimg src=\"\u002Fassets\u002Fexternal\u002Fservice\u002Flambda\u002Fguides\u002Faws-lambda-operator-guide\u002Fassets\u002Fimages\u002Fmonitoring-observability-figure-15.png\" alt=\"\">\u003C\u002Fp>\n",{"title":6,"order":7},"Log visualization and dashboard",71,"In the queries shown so far, you can export the results to markdown or CSV format. You can also create [visualizations from queries](https:\u002F\u002Fdocs.aws.amazon.com\u002FAmazonCloudWatch\u002Flatest\u002Flogs\u002FCWL_Insights-Visualizing-Log-Data.html), providing there is at least one aggregation function. The stats function allows you to define aggregations and grouping. Since Lambda functions always provide a timestamp, you can also produce time series charts, grouped into intervals using the bin function.\n\nThe previous _logInsightsJSON_ example filtered on upload size and upload time and excluded first invocations. This resulted in a table of data. For monitoring a production system, it may be more useful to visualize minimum, maximum, and average file sizes to find outliers. To do this, apply the stats function with the required aggregates, and group on a time value such as every minute:\n\n```sql\nfields @message\n| filter @message like \u002FINFO\u002F\n| filter uploadedBytes > 1000000\n| filter uploadTimeMS > 1000\n| filter invocation != 1\n| stats min(uploadedBytes), avg(uploadedBytes), max(uploadedBytes) by bin (1m)\n```\n\nAfter running the query, switch to the _Visualization_ tab to see the results:\n\n![](\u002Fassets\u002Fexternal\u002Fservice\u002Flambda\u002Fguides\u002Faws-lambda-operator-guide\u002Fassets\u002Fimages\u002Fmonitoring-observability-figure-14.png)\n\nAfter you have finished building the visualization, you can optionally add the graph to a CloudWatch dashboard. To do this, choose _Add to dashboard_ above the visualization. This adds the query as a widget and enables you to select automatic refresh intervals, making it easier to continuously monitor the results:\n\n![](\u002Fassets\u002Fexternal\u002Fservice\u002Flambda\u002Fguides\u002Faws-lambda-operator-guide\u002Fassets\u002Fimages\u002Fmonitoring-observability-figure-15.png)",[10,21,139,247,314,384,486,555],{"title":-1,"collapsible":11,"isCollapsed":12,"content":13},false,true,[14],{"title":15,"order":16,"time":17,"path":18,"id":19,"link":20},"Introduction",1,"4 min","intro","intro.md","\u002Fcontent\u002Fservice\u002Flambda\u002Fguides\u002Faws-lambda-operator-guide\u002Fintro",{"title":22,"collapsible":12,"isCollapsed":12,"content":23},"Event-driven architectures",[24,30,37,43,49,55,62,68,74,80,86,92,98,104,110,116,122,128,133],{"title":22,"order":25,"time":26,"path":27,"id":28,"link":29},2,"1 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